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task_116Retail trade

18 verifiers · 15 core · 3 secondary · 18 LLM-graded

TaxonomyRetail tradeGeneral and operations managers

All trialsGPT-5.6 SolcodexTrial 03

83%

Trial reward

GPT-5.6 SolFail

Trial 03 — 1st of 4 by reward score. This model averages 69% across 4 trials on this task.

  • 12/15Core verifiers passed
  • 15/18All verifiers passed
  • 3Core failed
  • 68Turns
  • 55Tool calls
  • $5.26Cost
  • 26.7mTime
  • 70kOutput tokens

Missed 3 of 15 core — traffic_profit, scope_control and capacity.

core (15)

  • sushi_routeLLMPass
    Why it matters

    Sushi is the most tempting vendor-led trap because supplier notes conflict with signed launch terms.

    How to pass

    Checks whether the memo makes the correct route-limited sushi recommendation.

    Reads

  • capacityLLMPass
    Why it matters

    A professional reset recommendation must catch the specific physical overfills before Space Planning releases the case set.

    How to pass

    Checks whether the memo identifies the exact buyer-proposal capacity conflicts by cluster and amount.

    Reads

  • vegetarian_roleLLMPass
    Why it matters

    Retail food-to-go resets must protect mission coverage while avoiding a poor substitute.

    How to pass

    Checks whether the memo protects credible vegetarian coverage with the correct item logic.

    Reads

  • seasonalLLMPass
    Why it matters

    Keeping or ambiguously deferring an unsupported winter perishable in July would create avoidable shrink and execution confusion.

    How to pass

    Checks whether the memo makes a concrete all-cluster zero-facing decision for the winter seasonal SKU.

    Reads

  • traffic_profitLLMFail
    Why it matters

    The task requires a decision that protects lunch traffic and profit, not just deletes weak SKUs.

    How to pass

    Checks whether the memo prioritizes the core traffic and profitable launch items.

    Reads

    Failure mode Required Rationale or Authority Statement Omitted

    Why it failed

    The memo protects Chicken Caesar Wrap and gives Protein Snack Box launch space but never states the full required rationale together: OOS pressure for Caesar, and pilot performance, low waste, code date, and scan credit for Protein Snack Box.

    Justification

    The memo clearly protects Chicken Caesar space (2 facings in every cluster; 'protects the high-volume lunch anchors' and 'use the recovered space for the stronger Caesar lunch anchor') and gives Protein Snack Box launch space with the required support rationale ('1.84-5.60 U/SPW,' '2.6%-7.8% waste,' 'five-day code,' and signed '$0.35 scan support'). However, it does not explicitly identify Chicken Caesar’s priority as driven by OOS pressure, which the rubric requires.

  • trust_hierarchyLLMPass
    Why it matters

    The task's central trap is that supplier projections and proposal comments conflict with the authoritative demand and vendor-term sources.

    How to pass

    Checks whether the memo substantively applies the source hierarchy instead of merely naming it.

    Reads

  • scope_controlLLMFail
    Why it matters

    The first four weeks must be executable using only the already available items, case capacity, and signed operating terms.

    How to pass

    Checks whether the memo avoids invented SKUs, capacity, delivery days, credits, and route assumptions.

    Reads

    Failure mode Unsupported Permission or Source Fact Introduced

    Why it failed

    The memo counts a $149 Caprese scan allowance that is not among the signed vendor credits the packet documents.

    Justification

    The assortment stays within the listed SKUs and live slot limits, and it does not add delivery days or expand sushi beyond Metro M-11. But the memo explicitly includes an extra Caprese vendor credit—e.g., 'Caprese scan support is included... remove that $149 allowance' and '$149 scan allowance ... is included'—which is not among the rubric’s allowed credits (Sakura sushi waste, Urban Spoon $0.35 Snack Box scan credit, and GreenFork credit only where 4+ delivery days apply).

  • executionLLMPass
    Why it matters

    The senior merchant needs a first-four-week reset decision that Space Planning and field operations can execute without interpreting generic advice.

    How to pass

    Checks whether the memo provides an executable revised cluster-level assortment with slot totals.

    Reads

  • workbook_structureLLMPass
    Why it matters

    The workbook must support the memo with granular decisions, not just summary prose.

    How to pass

    Checks whether the workbook contains a complete cluster-SKU decision matrix.

    Reads

  • core_final_facingsLLMPass
    Why it matters

    This keeps the load-bearing final allocation check while avoiding double-counting the Egg Salad, Turkey Cranberry, Caprese, and Hummus decisions.

    How to pass

    Checks workbook final facing allocations for core traffic, base assortment, profit-launch, and route-limited SKUs not separately covered by weak-SKU or vegetarian-distribution checks.

    Reads

  • capacityLLMFail
    Why it matters

    A capacity-constrained reset must prove both that the original proposal was corrected and that the final plan fits live case capacity.

    How to pass

    Checks whether the workbook numerically reconciles proposal capacity conflicts and final capacity compliance.

    Reads

    Failure mode Quantity, Cost, Capacity, or Rate Calculation Wrong

    Why it failed

    The workbook correctly shows live capacity and the buyer-proposal overages, but the final reconciled tray-slot totals per cluster do not match the required final values.

    Justification

    The workbook does include a numeric 'Capacity by cluster' table with the correct live capacities (12, 10, 10, 8, 7) and separate proposal overages for COM/CAM/HWY/RUR (10.5/10.5/8.5/7.5 vs 10/10/8/7). However, Metro is not reconciled as the required single final 12.0 tray-slot use: it shows 'Final Default 10.5', a separate 'M-11 Variant 12', and only 'Final Headroom 1.5'. That does not fully satisfy the required final tray-slot/variance reconciliation for every cluster.

  • dropsLLMPass
    Why it matters

    Leaving these SKUs in the final workbook would contradict the economics and handoff.

    How to pass

    Checks whether the workbook removes the two weak legacy/seasonal SKUs.

    Reads

  • vegetarian_roleLLMPass
    Why it matters

    This captures the nuanced vegetarian tradeoff that generic models often miss.

    How to pass

    Checks whether the workbook handles Caprese and Hummus distribution correctly.

    Reads

  • vendor_termsLLMPass
    Why it matters

    Vendor-term accuracy is essential because unsupported credits or route eligibility would make the reset economics and execution plan unusable.

    How to pass

    Checks whether the workbook applies each signed vendor term with exact item, cluster, and credit constraints.

    Reads

  • calculationsLLMPass
    Why it matters

    A supporting workbook must let reviewers verify margin, shrink, credit, OOS, and capacity logic instead of trusting unexplained conclusions.

    How to pass

    Checks whether the workbook includes auditable numeric economics and calculation evidence behind the decisions.

    Reads

secondary (3)

  • capacity_disciplineLLMPass
    Why it matters

    Perishable reset discipline means avoiding shrink even when that leaves small amounts of capacity unused.

    How to pass

    Checks whether the memo accepts specific underfilled capacity rather than force-filling weak perishables.

    Reads

  • proposal_reconciliationLLMPass
    Why it matters

    The requested decision is not only a final assortment; it must show which proposed changes were accepted, changed, or rejected.

    How to pass

    Checks whether the workbook provides a substantive accept/change/reject reconciliation against the buyer proposal.

    Reads

  • scope_controlLLMPass
    Why it matters

    Extra assumptions or unrelated operational actions can make the recommendation unusable even when the core analysis appears complete.

    How to pass

    Checks workbook scope control and absence of materially unsolicited tabs, assumptions, or side actions.

    Reads

2 deliverables · what this trial produced

grab_go_reset_memo.docx19 KB

REFRIGERATED GRAB-AND-GO RESET

First-four-week merchant recommendation

To: L. Moreno, Senior Merchant - Prepared Foods From: Category Planning

Date: Pre-release review; source pack current through June 12, 2026 Decision: Approve with required changes

RECOMMENDATION

Do not release the buyer proposal as written. Release the revised cluster sets below, with a separate Metro M-11 sushi variant and the route/store controls completed before load.

Why the proposal must change

The proposal is operationally infeasible in four clusters and overstates signed route support. The revised set protects the high-volume lunch anchors, keeps a credible vegetarian option everywhere, accepts the strongest new item, and removes the most avoidable short-code shrink.

Risk

Proposal conflict

First-four-week decision

Internal / signed evidence

Capacity

Four clusters are over the live case limit.

COM, CAM, HWY, and RUR each use 0.5 more tray slot than available. A partial facing is not allowed.

Replace with the final facings below. Leave 0.5 slot open in HWY and 1.0 slot open in RUR.

Capacity file + handoff. Proposal: 10.5/10.0, 10.5/10.0, 8.5/8.0, and 7.5/7.0 slots.

Sushi route

Proposal scope is not signed.

Buyer adds two MET facings and one each in COM/CAM. Signed terms cover only Metro M-11 daily-route stores.

Reject COM/CAM; cut MET to one facing in route-verified M-11 stores only. Default MET planogram has no sushi.

COM pilot waste 32.5%; CAM 26.1%; MET 10.6%. One-day code and case pack 12.

Vegetarian swap

Caprese does not win everywhere.

Proposal removes Hummus broadly and adds Caprese in MET/COM/CAM/HWY.

Add Caprese only in MET/CAM. Keep Hummus in COM/CAM/HWY/RUR; reject Highway Caprese.

COM: Hummus 2.18 U/SPW and 8.7% waste vs. Caprese 1.83 and 16.4%. Highway route is explicitly excluded.

Legacy / seasonal

Weak items lack protection.

Proposal keeps Turkey Cranberry in HWY and Egg Salad in RUR.

Reject both. Also remove Rural Southwest Bowl for the first four weeks.

HWY Cranberry: 1.12 U/SPW, 22.4% waste, no post-Jan. billback. RUR Egg: 0.72, 24.3%; Bowl: 1.38, 19.3%, 1.5 slots.

Protein Snack Box

Good item; proposed space is too broad.

Proposal assigns two facings in every cluster.

Accept two in MET/COM/CAM; use one in HWY/RUR.

Internal pilots: 1.84-5.60 U/SPW, 2.6%-7.8% waste; five-day code; signed $0.35 scan allowance on all routes.

Decision count: 32 proposal rows accepted, 7 changed, and 11 rejected. The workbook contains the complete 50-row reconciliation.

Revised cluster assortment

Facings are per store and use only the live July tray capacity. Additional facings are space decisions only; the economic projection does not assume that duplicate facings create incremental demand.

Cluster / cadence

Final facings

Used / live slots

Vegetarian and execution note

MET

18 stores | 5 deliveries/wk

2x Chicken Caesar Wrap

1x Turkey Club

2x Southwest Chicken Bowl

1x Cobb Salad

1x Caprese Ciabatta

2x Protein Snack Box

1x Spicy Tuna Sushi - M-11 only

10.5 / 12.0

default / route variant

Caprese. Publish a non-sushi default and a separate M-11 variant; exact signed roster must be matched before load.

COM

26 stores | 4 deliveries/wk

2x Chicken Caesar Wrap

2x Turkey Club

1x Southwest Chicken Bowl

1x Hummus Veggie Wrap

1x Cobb Salad

2x Protein Snack Box

10.0 / 10.0

Hummus. Do not launch Caprese or sushi; use the recovered space for the stronger Caesar lunch anchor.

CAM

11 stores | 5 deliveries/wk

2x Chicken Caesar Wrap

1x Turkey Club

1x Southwest Chicken Bowl

1x Hummus Veggie Wrap

1x Cobb Salad

1x Caprese Ciabatta

2x Protein Snack Box

10.0 / 10.0

Hummus + Caprese. Retain both because local meatless demand supports them; reject sushi expansion.

HWY

15 stores | 3 deliveries/wk

2x Chicken Caesar Wrap

2x Turkey Club

1x Southwest Chicken Bowl

1x Hummus Veggie Wrap

1x Protein Snack Box

7.5 / 8.0

0.5 open

Hummus. Leave the half-slot open; do not use a partial facing, winter item, or unrouted Caprese.

RUR

14 stores | 2 deliveries/wk

2x Chicken Caesar Wrap

2x Turkey Club

1x Hummus Veggie Wrap

1x Protein Snack Box

6.0 / 7.0

1.0 open

Hummus. Remove Egg Salad and Southwest Bowl; keep the first-four-week set deliberately clean.

Capacity bridge

Cluster

Live

Proposal

Final default

M-11 variant

Resolution

Metro Core

12.0

12.0

10.5

12.0

Default excludes sushi; M-11 variant fits exactly.

Commuter Suburban

10.0

10.5

10.0

-

Proposal over by 0.5; final fits.

Campus / Hospital

10.0

10.5

10.0

-

Proposal over by 0.5; final fits.

Highway / Travel

8.0

8.5

7.5

-

Final leaves 0.5 open.

Rural North

7.0

7.5

6.0

-

Final leaves 1.0 open.

Metro control: The signed offer authorizes only M-11 stores, but the source pack does not contain the exact store roster. The workbook uses the nine observed Metro pilot stores for economics; that count is not a substitute for route verification. Default every unverified Metro store to the non-sushi set.

Supporting economics

The model uses the eight internal weeks from April 6 through May 25, 2026. Sales and waste are divided by ranged store-weeks, then scaled to the final store scope for four weeks. Supplier projections and proposal comments are excluded as demand inputs.

Cluster

Retail sales

Waste units

Net GP incl. support

Scope note

Metro Core

$13,010

112.5

$7,360

Includes sushi at the nine observed Metro pilot stores only; route match is still required.

Commuter Suburban

$15,318

132.1

$8,612

Hummus retained; no Caprese or sushi launch.

Campus / Hospital

$8,848

73.7

$5,030

Both vegetarian lunches retained; no sushi.

Highway / Travel

$6,301

71.0

$3,535

No Turkey Cranberry or Caprese; one Snack Box facing.

Rural North

$3,946

50.8

$2,218

Four-item set; no Bowl or Egg Salad.

Chain total

$47,423

440.1

$26,754

6.0% waste rate; includes $658 of signed support.

What is included in net GP

$26,096

base GP after $1,327 of shrink cost

$574

signed scan allowances

$84

eligible documented-waste credits

Support cap check: Caprese projects 373 scans against the 5,500-unit cap; Protein Snack Box projects 1,214 against the 8,000-unit cap. Caprese scan support is included only for July 13-August 9. If the launch dates move, remove that $149 allowance.

Decision evidence on the contested items

Item / issue

Decision

Internal demand and waste

Terms / operating interpretation

Caprese

Accept MET/CAM; reject COM/HWY

MET 3.17 U/SPW, 8.4% waste; CAM 3.30, 6.4%; COM 1.83, 16.4%

$149 scan allowance plus eligible GreenFork waste credit is included. HWY route is not signed.

Hummus

Keep COM/CAM/HWY/RUR

COM 2.18 U/SPW, 8.7% waste; CAM 3.10, 7.1%

Required credible vegetarian answer in HWY/RUR. No GreenFork waste credit below four delivery days.

Protein Snack Box

Add all; 2/2/2/1/1 facings

1.84-5.60 U/SPW; 2.6%-7.8% waste

Five-day code and $0.35 scan support. Projected 1,214 scans remain below the 8,000-unit cap.

Spicy Tuna Sushi

One MET M-11 facing only

MET 3.15 U/SPW, 10.6% waste; COM 32.5% and CAM 26.1% waste

No scan allowance. Modeled waste credit applies only to the nine observed pilot stores if they match M-11.

Rural and shrink read-through: Remove Egg Salad (0.72 U/SPW; 24.3% waste) and Southwest Bowl (1.38 U/SPW; 19.3% waste; 1.52 weeks of ending inventory). On proposal rows with local internal records, the revised set reduces projected four-week waste by about 122 units (562.3 to 440.1). A complete proposal dollar comparison is not valid because Highway Caprese has no local demand record and several proposed sushi placements are not signed routes.

Release instructions and execution risks

Space Planning: issue the five cluster sets exactly as shown. For Metro, publish a default planogram without sushi and a one-facing M-11 variant. Do not solve any variance with a partial facing.

Operations: obtain and match the exact signed M-11 store roster before sushi item load. Any unverified Metro store receives the default set. Sushi requires daily delivery, a one-day code, no holdover, and documented waste.

Replenishment: set zero forward orders for Highway Turkey Cranberry, Rural Egg Salad, and Rural Southwest Bowl before reset. Do not treat added facings as demand uplift or add delivery stops.

Short-code controls: Caprese and Hummus carry two-day codes. GreenFork's 30% waste credit applies only where delivery is at least four days per week; Highway and Rural Hummus receive no modeled credit.

Credit capture: preserve scan and documented-waste support files. Caprese scans qualify only July 13-August 9; Sushi's M-11 waste credit runs through August 16; Snack Box support covers the first six reset weeks.

Week-four review: compare actual sales U/SPW, waste rate, OOS store-days, and ending inventory with the workbook. Do not expand Caprese or sushi routes without a new signed addendum and local evidence.

Release gates

Owner

Required before field release

Pass condition

Space Planning

Load revised facings and both Metro variants; verify all planograms against live slots.

No cluster above capacity; all facings are whole numbers.

Prepared Foods / Operations

Match the exact M-11 roster to the sushi variant.

Only signed M-11 daily-route stores receive sushi.

Replenishment

Remove three rejected legacy/low-repeat items and set conservative initial short-code orders.

No residual auto-replenishment; no extra stops or trays assumed.

Finance / Vendor admin

Set signed scan and waste-credit windows and evidence requirements.

No supplier projection, informal credit, or post-window billback enters the model.

Method and source hierarchy

Merchant handoff rules were applied first. Internal POS, waste, OOS, receipts, and inventory are the only demand signal. The signed offer letters control route eligibility, launch support, credits, and handling. Item-master tray slots, case packs, costs, retail, and shelf life control unit economics and space. The capacity file controls July tray limits and delivery cadence. The buyer proposal is treated only as the set of requested changes.

Source files: merchant_handoff_prepared_foods.docx; weekly_pos_inventory_waste.csv; item_master_unit_economics.csv; store_cluster_capacity.csv; buyer_reset_proposal.csv; signed_vendor_offer_letters.pdf.

User prompt → 68 turns · 55 tool calls → final responsecodex

  1. 1systemskills instructions · Skills A skill is a set of instructions provided through a SKILL.md source. Below is the list of s…

    skills instructions

    Skills

    A skill is a set of instructions provided through a SKILL.md source. Below is the list of skills that can be used. Each entry includes a name, description, and source locator. file locators are on the host filesystem, executor package locators are owned by their execution environment, orchestrator package locators are opaque package identifiers, and custom resource locators use their provider's access mechanism.

    Available skills

    • imagegen: Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas. (file: /tmp/codex-home/skills/.system/imagegen/SKILL.md)
    • openai-docs: Use for Codex models/pricing, scheduled tasks, skills, settings, setup, troubleshooting, customization, automations, and self-knowledge—including 'you,' 'your,' 'this app,' or 'this coding agent' when they refer to Codex—and for OpenAI APIs/products and ChatGPT Work. Also use for model choice/migration, prompting, SDKs, Responses, Realtime, agents, evals, and Chat/Work/Codex comparisons. Do not use for generic app/software tasks that merely mention Codex. (file: /tmp/codex-home/skills/.system/openai-docs/SKILL.md)
    • plugin-creator: Create and scaffold plugin directories for Codex with a required .codex-plugin/plugin.json, optional plugin folders/files, valid manifest defaults, and personal-marketplace entries by default. Use when Codex needs to create a new personal plugin, add optional plugin structure, generate or update marketplace entries for plugi

    … 3,403 more characters in the raw trajectory.

  2. 2systemYou are /root, the primary agent in a team of agents collaborating to fulfill the user's goals. At the start of your tur…

    You are /root, the primary agent in a team of agents collaborating to fulfill the user's goals.

    At the start of your turn, you are the active agent.
    You can spawn sub-agents to handle subtasks, and those sub-agents can spawn their own sub-agents.
    All agents in the team, including the agents that you can assign tasks to, are equally intelligent and capable, and have access to the same set of tools.

    You can use spawn_agent to create a new agent, followup_task to give an existing agent a new task and trigger a turn, and send_message to pass a message to a running agent without triggering a turn.
    Child agents can also spawn their own sub-agents.
    You can decide how much context you want to propagate to your sub-agents with the fork_turns parameter.

    You will receive messages in the analysis channel in the form:

    Message Type: MESSAGE | FINAL_ANSWER
Task name: <recipient>
Sender: <author>
Payload:
<payload text>

    They may be addressed as to=/root

    Note that collaboration tools cannot be called from inside functions.exec. Call spawn_agent, send_message, followup_task, wait_agent, interrupt_agent, and list_agents only as direct tool calls using the recipient shown in their tool definitions, such as to=functions.collaboration.spawn_agent, since they are intentionally absent from the functions.exec tools.* namespace. Available tools in functions.exec are explicitly described with a tools namespace in the developer message.

    All agents share the same directory. In detail:

    • All agents have access to the same container and filesystem as you.
    • All agents use the same current working directory.
    • As a result, edits made by one agent are immediately visible to all other agents.

    When calling wait_agent, prefer longer waits (minutes) to avoid busy polling.

    There are 4 available concurrency slots, meaning that up to 4 agents can be active at once, including you.

    Full-history forks (fork_turns omitted or "all") inherit the parent mod

    … 264 more characters in the raw trajectory.

  3. 3systemmulti agent mode · Any earlier instruction enabling proactive multi-agent delegation no longer applies. Do not spawn sub…

    multi agent mode

    Any earlier instruction enabling proactive multi-agent delegation no longer applies. Do not spawn sub-agents unless the user or applicable AGENTS.md/skill instructions explicitly ask for sub-agents, delegation, or parallel agent work.

  4. 4userenvironment context · /workspace bash 2026-08-20 Etc/UTC /workspace

    environment context

    cwd
    /workspace
    shell
    bash
    current date
    2026-08-20
    timezone
    Etc/UTC
    root
    /workspace
  5. 5userYou are a category planning analyst at Blue Mesa Market, an 84-store convenience/grocery retailer. The prepared-foods me…

    You are a category planning analyst at Blue Mesa Market, an 84-store convenience/grocery retailer. The prepared-foods merchant has asked you to review a July reset proposal for the refrigerated grab-and-go case before it is released to Space Planning and field operations. The proposal came out of vendor line reviews and includes several new items, but the case is capacity-constrained and the first four weeks of the reset must work with the delivery network that is already signed.

    Using the attached materials, decide which proposed item and cluster changes should be accepted, changed, or rejected for the first four weeks of the reset. Your recommendation should protect lunch traffic and gross profit while reducing avoidable shrink and avoiding store-level execution problems. The senior merchant needs a practical decision, not a theory memo: identify the highest-risk parts of the proposal, state the revised cluster-level assortment, and show the supporting economics and capacity reconciliation.

    Work only from the attached materials. Treat the merchant handoff as authoritative for business rules and trust hierarchy. Treat internal sales, waste, and inventory records as the demand signal; do not rely on supplier projections or proposal comments as proof of demand. Treat signed vendor offer letters as authoritative for credits, route eligibility, and launch support. Do not invent additional case capacity, delivery days, vendor credits, or substitute items that are not in the files. Where the proposal conflicts with the handoff, internal records, or signed terms, explain the conflict and resolve it using the more authoritative source.

    Produce the following deliverables in /workspace/output/:

    • grab_go_reset_memo.docx - a merchant-facing memo with the revised reset recommendation, the major proposal changes, business rationale, and execution risks.
    • reset_decision_workbook.xlsx - a supporting workbook showing the cluster-level final decisions, item economics, pro

    … 67 more characters in the raw trajectory.

  6. 6I’m using the Word and spreadsheet skills because the requested outputs are a merchant memo and an auditable decision wo…

    I’m using the Word and spreadsheet skills because the requested outputs are a merchant memo and an auditable decision workbook. I’ll first read their requirements, then inventory the source files and build the recommendation strictly from the stated trust hierarchy.

  7. 7Shell1

    Tool execution only — no assistant text

    Shellvia exec21k chars

    Arguments

    const p = await tools.update_plan({plan:[
  {step:"Read the document and spreadsheet skill instructions",status:"in_progress"},
  {step:"Inventory and analyze all attached source materials",status:"pending"},
  {step:"Resolve item and cluster decisions, economics, and capacity",status:"pending"},
  {step:"Build and validate the decision workbook",status:"pending"},
  {step:"Draft, render, and validate the merchant memo",status:"pending"}
]});
const r = await tools.exec_command({cmd:"sed -n '1,260p' /root/.agents/skills/docx/SKILL.md && sed -n '1,320p' /roo

    … 135 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.1 seconds
Output:

---
name: docx
description: "Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation."
license: Proprietary. LICENSE.txt has complete t

    … 20,328 more characters of output in the raw trajectory.

  8. 8Shell1

    Tool execution only — no assistant text

    Shellvia exec12k chars

    Arguments

    const rs = await Promise.all([
  tools.exec_command({cmd:"wc -l /root/.agents/skills/docx/SKILL.md","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":1000}),
  tools.exec_command({cmd:"wc -l /root/.agents/skills/xlsx/SKILL.md","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":1000}),
  tools.exec_command({cmd:"sed -n '261,620p' /root/.agents/skills/docx/SKILL.md","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":30000}),
  tools.exec_command({cmd:"sed -n '321,620p' /root/.agents/skills/xlsx/SKILL.md","w

    … 145 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.1 seconds
Output:

RESULT 1
590 /root/.agents/skills/docx/SKILL.md

RESULT 2
291 /root/.agents/skills/xlsx/SKILL.md

RESULT 3
  new Bookmark({ id: "chapter1", children: [new TextRun("Chapter 1")] }),
]})
// 2. Link to it
new Paragraph({ children: [new InternalHyperlink({
  children: [new TextRun({ text: "See Chapter 1", style: "Hyperlink" })],
  anchor: "chapter1",
})]})
```

### Footnotes

```javascript
const doc = new Document({
  footnotes: {
    1: { children: [new Paragraph("Source: Annual Report 2024")] },
    2: { children: [new Paragraph("See appendix for methodology")] },
  },
  sections: [{
    children: [new Paragraph({
      children: [
        new TextRun("Revenue grew 15%"),
        new FootnoteReferenceRun(1),
        new TextRun(" using adjusted metrics"),
        new Footnot

    … 10,666 more characters of output in the raw trajectory.

  9. 9exec1

    Tool execution only — no assistant text

    execconst p = await tools.update_plan({explanation:"The two required output skills are fully reviewed. I’m moving into source-file inventory and evidence extraction.",plan:[ {step:"Read the document and spreadsheet skill instructions",status:"completed"}, {step:"Inventory and analyze all attached source materials",status:"in_progress"}, {step:"Resolve item and cluster decisions, economics, and capacity",status:"pending"}, {step:"Build and validate the decision workbook",status:"pending"}, {step:"Draft, render, and validate the merchant memo",status:"pe

    Arguments

    const p = await tools.update_plan({explanation:"The two required output skills are fully reviewed. I’m moving into source-file inventory and evidence extraction.",plan:[
  {step:"Read the document and spreadsheet skill instructions",status:"completed"},
  {step:"Inventory and analyze all attached source materials",status:"in_progress"},
  {step:"Resolve item and cluster decisions, economics, and capacity",status:"pending"},
  {step:"Build and validate the decision workbook",status:"pending"},
  {step:"Draft, render, and validate the merchant memo",status:"pe

    … 206 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.1 seconds
Output:

data/buyer_reset_proposal.csv
data/item_master_unit_economics.csv
data/merchant_handoff_prepared_foods.docx
data/signed_vendor_offer_letters.pdf
data/store_cluster_capacity.csv
data/weekly_pos_inventory_waste.csv
  10. 10One source is a signed offer-letter PDF, so I’m also applying the PDF skill to extract and verify its terms. That eviden…

    One source is a signed offer-letter PDF, so I’m also applying the PDF skill to extract and verify its terms. That evidence will control credits, route eligibility, and launch support exactly as the handoff directs.

  11. 11Shell1

    Tool execution only — no assistant text

    Shellvia exec9k chars

    Arguments

    const a = await tools.exec_command({cmd:"wc -l /root/.agents/skills/pdf/SKILL.md","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":1000});
text(a.output);
const b = await tools.exec_command({cmd:"sed -n '1,360p' /root/.agents/skills/pdf/SKILL.md","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":30000});
text(b.output);

    Output

    Script completed
Wall time 0.1 seconds
Output:

314 /root/.agents/skills/pdf/SKILL.md

---
name: pdf
description: Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
license: Proprietary. LICENSE.txt has complete terms
---

# PDF Processing Guide

## Overview

This guide covers essential PDF processing operations using Python libraries and command-line tools. For advanced features, JavaScript libraries, and detailed examples, see REFERENCE.md. If you need to fill out a PDF form, read FORMS.md

    … 7,564 more characters of output in the raw trajectory.

  12. 12Shell1

    Tool execution only — no assistant text

    Shellvia exec5k chars

    Arguments

    const rs = await Promise.all([
  tools.exec_command({cmd:"ls -lh data","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":5000}),
  tools.exec_command({cmd:"wc -l data/*.csv","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":5000}),
  tools.exec_command({cmd:"pandoc --track-changes=all data/merchant_handoff_prepared_foods.docx -t gfm","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":30000}),
  tools.exec_command({cmd:"pdfinfo data/signed_vendor_offer_letters.pdf","workdir":"/workspace","yield_time_m

    … 276 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 1.2 seconds
Output:

RESULT 1
total 84K
-rw-r--r-- 1 root root 5.5K Aug 19 23:31 buyer_reset_proposal.csv
-rw-r--r-- 1 root root 1.3K Aug 19 23:31 item_master_unit_economics.csv
-rw-r--r-- 1 root root  38K Aug 19 23:31 merchant_handoff_prepared_foods.docx
-rw-r--r-- 1 root root 4.7K Aug 19 23:31 signed_vendor_offer_letters.pdf
-rw-r--r-- 1 root root  833 Aug 19 23:31 store_cluster_capacity.csv
-rw-r--r-- 1 root root  33K Aug 19 23:31 weekly_pos_inventory_waste.csv

RESULT 2
   51 data/buyer_reset_proposal.csv
   11 data/item_master_unit_economics.csv
    6 data/store_cluster_capacity.csv
  369 data/weekly_pos_inventory_waste.csv
  437 total

RESULT 3
/bin/bash: line 1: pandoc: command not found

RESULT 4
Title:           (anonymous)
Subject:         (unspecified)
Keyw

    … 3,757 more characters of output in the raw trajectory.

  13. 13The signed terms extracted cleanly. The Word handoff extractor recommended by the skill is not installed, so I’m switchi…

    The signed terms extracted cleanly. The Word handoff extractor recommended by the skill is not installed, so I’m switching to the skill’s raw-DOCX unpack workflow and will preserve headings/tables while extracting the business rules.

  14. 14Shell1

    Tool execution only — no assistant text

    Shellvia exec5k chars

    Arguments

    const rs = await Promise.all([
  tools.exec_command({cmd:"rg --files /root/.agents/skills/docx | sort","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":10000}),
  tools.exec_command({cmd:"command -v docx2txt","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":1000}),
  tools.exec_command({cmd:"command -v libreoffice","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":1000}),
  tools.exec_command({cmd:"command -v xmllint","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":1000})
]);

    … 62 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.1 seconds
Output:

RESULT 1
/root/.agents/skills/docx/LICENSE.txt
/root/.agents/skills/docx/SKILL.md
/root/.agents/skills/docx/scripts/__init__.py
/root/.agents/skills/docx/scripts/accept_changes.py
/root/.agents/skills/docx/scripts/comment.py
/root/.agents/skills/docx/scripts/office/helpers/__init__.py
/root/.agents/skills/docx/scripts/office/helpers/merge_runs.py
/root/.agents/skills/docx/scripts/office/helpers/simplify_redlines.py
/root/.agents/skills/docx/scripts/office/pack.py
/root/.agents/skills/docx/scripts/office/schemas/ISO-IEC29500-4_2016/dml-chart.xsd
/root/.agents/skills/docx/scripts/office/schemas/ISO-IEC29500-4_2016/dml-chartDrawing.xsd
/root/.agents/skills/docx/scripts/office/schemas/ISO-IEC29500-4_2016/dml-diagram.xsd
/root/.agents/skills/docx/scripts/office/schemas/ISO-IEC29500-4_2016/dml-lockedCanvas.xsd
/root/.agents/skills/docx/scripts/office/schemas/IS

    … 4,024 more characters of output in the raw trajectory.

  15. 15Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"mktemp -d -p /tmp merchant_handoff.XXXXXX","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":1000});
text(r.output);

    Output

    Script completed
Wall time 0.1 seconds
Output:

/tmp/merchant_handoff.brhRdA
  16. 16Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"python /root/.agents/skills/docx/scripts/office/unpack.py data/merchant_handoff_prepared_foods.docx /tmp/merchant_handoff.brhRdA","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":5000});
text(r.output);

    Output

    Script completed
Wall time 0.7 seconds
Output:

Unpacked data/merchant_handoff_prepared_foods.docx (16 XML files), simplified 0 tracked changes, merged 0 runs
  17. 17Shell1

    Tool execution only — no assistant text

    Shellvia exec10k chars

    Arguments

    const r = await tools.exec_command({cmd:"sed -n '1,280p' /tmp/merchant_handoff.brhRdA/word/document.xml","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":30000});
text(r.output);

    Output

    Script completed
Wall time 0.1 seconds
Output:

<?xml version="1.0" encoding="UTF-8"?><w:document xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:mo="http://schemas.microsoft.com/office/mac/office/2008/main" xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" xmlns:mv="urn:schemas-microsoft-com:mac:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" xmlns:m="http://schemas.openxmlformats.org/officeDocument/2006/math" xmlns:v="urn:schemas-microsoft-com:vml" xmlns:wp14="http://schemas.microsoft.com/office/word/2010/wordprocessingDrawing" xmlns:wp="http://schemas.openxmlformats.org/drawingml/2006/wordprocessingDrawing" xmlns:w10="urn:schemas-microsoft-com:office:word" xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" xmlns:w14="http://schemas.microsoft.com/office/

    … 8,921 more characters of output in the raw trajectory.

  18. 18Shell1

    Tool execution only — no assistant text

    Shellvia exec3k chars

    Arguments

    const r = await tools.exec_command({cmd:"sed -n '281,620p' /tmp/merchant_handoff.brhRdA/word/document.xml","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":30000});
text(r.output);

    Output

    Script completed
Wall time 0.1 seconds
Output:

          </w:tcPr>
          <w:p>
            <w:r>
              <w:rPr>
                <w:sz w:val="17"/>
              </w:rPr>
              <w:t>Protein Snack Box</w:t>
            </w:r>
          </w:p>
        </w:tc>
        <w:tc>
          <w:tcPr>
            <w:tcW w:type="dxa" w:w="3456"/>
            <w:vAlign w:val="top"/>
          </w:tcPr>
          <w:p>
            <w:r>
              <w:rPr>
                <w:sz w:val="17"/>
              </w:rPr>
              <w:t>The SKU is new but has longer code date, low waste, and lunch/snack mission relevance.</w:t>
            </w:r>
          </w:p>
        </w:tc>
        <w:tc>
          <w:tcPr>
            <w:tcW w:type="dxa" w:w="3456"/>
            <w:vAlign w:val="top"/>
          </w:tcPr>
          <w:p>
            <w:r>
              <w:rPr>

    … 2,349 more characters of output in the raw trajectory.

  19. 19Shell1

    Tool execution only — no assistant text

    Shellvia exec12k chars

    Arguments

    const rs = await Promise.all([
  tools.exec_command({cmd:"sed -n '1,120p' data/item_master_unit_economics.csv","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":10000}),
  tools.exec_command({cmd:"sed -n '1,120p' data/store_cluster_capacity.csv","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":10000}),
  tools.exec_command({cmd:"sed -n '1,140p' data/buyer_reset_proposal.csv","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":20000}),
  tools.exec_command({cmd:"sed -n '1,40p' data/weekly_pos_inventory_wast

    … 156 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.1 seconds
Output:

RESULT 1
sku,item,status,vendor,role,diet_flag,shelf_life_days,case_pack,tray_slots_per_facing,retail_price,unit_cost,order_multiple_cases,first_available_date,current_core
GGS-84QJ,Chicken Caesar Wrap,Current,EatWell Foods,Core wrap,Meat,3,12,1.0,5.99,2.38,1,2024-03-18,Yes
GGS-2VWK,Turkey Club Sandwich,Current,EatWell Foods,Core sandwich,Meat,3,10,1.0,6.49,2.64,1,2023-08-07,Yes
GGS-9PQL,Southwest Chicken Bowl,Current,Urban Spoon,Bowl meal,Meat,3,8,1.5,7.99,3.45,1,2024-09-09,Yes
GGS-5MTC,Hummus Veggie Wrap,Current,GreenFork Kitchen,Vegetarian lunch,Vegetarian,2,8,1.0,6.29,2.75,1,2023-05-01,No
GGS-7DNL,Cobb Salad,Current,FreshPack Deli,Salad meal,Meat,3,6,1.5,8.49,3.72,1,2024-01-22,No
GGS-1KFV,Egg Salad Croissant,Current,FreshPack Deli,Legacy sandwich,Egg vegetarian,2,8,1.0,5.49,2.28,1,2022-06-13,No
GGS-4HBP,Turkey Cranberry Sandwich,Current season

    … 10,934 more characters of output in the raw trajectory.

  20. 20I now have the controlling rules: full facings only, live July tray limits, internal records as demand, and signed terms…

    I now have the controlling rules: full facings only, live July tray limits, internal records as demand, and signed terms as the sole authority for support and route eligibility. I’m checking the POS file’s coverage and pilot structure before comparing each proposed facing by cluster.

  21. 21Shell1

    Tool execution only — no assistant text

    Shellvia exec8k chars

    Arguments

    const r = await tools.exec_command({cmd:"python - <<'PY'\nimport pandas as pd\np='data/weekly_pos_inventory_waste.csv'\ndf=pd.read_csv(p, parse_dates=['week_start'])\nprint(df.info())\nprint('\\nDate range:', df.week_start.min().date(), 'to', df.week_start.max().date())\nprint('\\nRange types / rows:')\nprint(df.groupby('range_type').size().to_string())\nprint('\\nRows and observed weeks by SKU/cluster:')\ng=(df.groupby(['sku','item','cluster_code','range_type']).agg(rows=('week_start','size'),weeks=('week_start','nunique'),first=('week_start','min'),last=('week_start

    … 396 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.9 seconds
Output:

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 368 entries, 0 to 367
Data columns (total 12 columns):
 #   Column                Non-Null Count  Dtype         
---  ------                --------------  -----         
 0   week_start            368 non-null    datetime64[ns]
 1   cluster_code          368 non-null    object        
 2   cluster_name          368 non-null    object        
 3   sku                   368 non-null    object        
 4   item                  368 non-null    object        
 5   range_type            368 non-null    object        
 6   stores_ranged         368 non-null    int64         
 7   net_sales_units       368 non-null    int64         
 8   waste_units           368 non-null    int64         
 9   oos_store_days        368 non-null    float64       
 10  receipts_units        368 non-null    int64         
 11  e

    … 6,553 more characters of output in the raw trajectory.

  22. 22Shell1

    Tool execution only — no assistant text

    Shellvia exec10k chars

    Arguments

    const r = await tools.exec_command({cmd:"python - <<'PY'\nimport pandas as pd\npos=pd.read_csv('data/weekly_pos_inventory_waste.csv')\nmaster=pd.read_csv('data/item_master_unit_economics.csv')\ncap=pd.read_csv('data/store_cluster_capacity.csv')\nprop=pd.read_csv('data/buyer_reset_proposal.csv')\ng=(pos.groupby(['cluster_code','cluster_name','sku','item','range_type'],as_index=False)\n   .agg(stores_ranged=('stores_ranged','max'),store_weeks=('stores_ranged','sum'),sales=('net_sales_units','sum'),waste=('waste_units','sum'),oos_days=('oos_store_days','sum'),receipts=('receipts

    … 1,785 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.8 seconds
Output:


### MET
cluster_code      sku                      item       range_type  stores_ranged sales_u_spw waste_u_spw waste_rate oos_days_spw gp_after_waste_spw gp_after_waste_per_slot
         MET GGS-84QJ       Chicken Caesar Wrap      Current set             18        5.50        0.28       4.9%         0.25              19.18                   19.18
         MET GGS-6BGH         Protein Snack Box Controlled pilot              9        4.14        0.11       2.6%         0.28              15.61                   15.61
         MET GGS-9PQL    Southwest Chicken Bowl      Current set             18        4.51        0.32       6.6%         0.16              19.39                   12.93
         MET GGS-2VWK      Turkey Club Sandwich      Current set             18        3.09        0.12       3.9%         0.05              11.57                   11.57
         M

    … 8,574 more characters of output in the raw trajectory.

  23. 23Shell1

    Tool execution only — no assistant text

    Shellvia exec7k chars

    Arguments

    const r = await tools.exec_command({cmd:"python - <<'PY'\nimport pandas as pd\np=pd.read_csv('data/weekly_pos_inventory_waste.csv')\nm=pd.read_csv('data/item_master_unit_economics.csv')\ng=(p.groupby(['cluster_code','sku','item','range_type'],as_index=False)\n   .agg(stores=('stores_ranged','max'),store_weeks=('stores_ranged','sum'),sales=('net_sales_units','sum'),waste=('waste_units','sum'),receipts=('receipts_units','sum'),eoh_sum=('ending_on_hand_units','sum'),oos=('oos_store_days','sum')))\ng=g.merge(m[['sku','case_pack','shelf_life_days','unit_cost','retail_price']],on='s

    … 1,125 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.8 seconds
Output:


 MET
cluster_code      sku                  item       range_type  shelf_life_days  case_pack sales_spw waste_spw waste_rate receipts_spw avg_eoh_per_store eoh_weeks_supply  oos
         MET GGS-3RZA      Caprese Ciabatta Controlled pilot                2          8      3.17      0.29       8.4%         3.56              1.71             0.54  3.8
         MET GGS-6BGH     Protein Snack Box Controlled pilot                5         10      4.14      0.11       2.6%         4.46              2.36             0.57 20.2
         MET GGS-8XUY Spicy Tuna Sushi Roll Controlled pilot                1         12      3.15      0.38      10.6%         3.75              2.56             0.81  6.2

 COM
cluster_code      sku                  item       range_type  shelf_life_days  case_pack sales_spw waste_spw waste_rate receipts_spw avg_eoh_per_store eoh_weeks_supply

    … 6,102 more characters of output in the raw trajectory.

  24. 24Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"pdftoppm -png -r 120 data/signed_vendor_offer_letters.pdf /tmp/vendor_offer_page","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":2000});
text(r.output);

    Output

    Script completed
Wall time 0.5 seconds
Output:
  25. 25exec1

    Tool execution only — no assistant text

    execconst rs = await Promise.all([ tools.view_image({path:"/tmp/vendor_offer_page-1.png",detail:"original"}), tools.view_image({path:"/tmp/vendor_offer_page-2.png",detail:"original"}) ]); rs.forEach((r)=>image(r.image_url,"original"));296k chars

    Arguments

    const rs = await Promise.all([
  tools.view_image({path:"/tmp/vendor_offer_page-1.png",detail:"original"}),
  tools.view_image({path:"/tmp/vendor_offer_page-2.png",detail:"original"})
]);
rs.forEach((r)=>image(r.image_url,"original"));

    Output

    Script completed
Wall time 0.0 seconds
Output:

    … 294,758 more characters of output in the raw trajectory.

  26. 26Shell1

    Tool execution only — no assistant text

    Shellvia exec3k chars

    Arguments

    const r = await tools.exec_command({cmd:"python - <<'PY'\nimport pandas as pd\npos=pd.read_csv('data/weekly_pos_inventory_waste.csv')\nmaster=pd.read_csv('data/item_master_unit_economics.csv')\ncap=pd.read_csv('data/store_cluster_capacity.csv')\ng=(pos.groupby(['cluster_code','sku'],as_index=False)\n   .agg(store_weeks=('stores_ranged','sum'),sales=('net_sales_units','sum'),waste=('waste_units','sum')))\ng=g.merge(master,on='sku').merge(cap[['cluster_code','store_count','deliveries_per_week']],on='cluster_code')\ng['sales_spw']=g.sales/g.store_weeks; g['waste_spw']=g.waste/g

    … 2,453 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.8 seconds
Output:

Cluster totals
         stores_scope_sum    units   waste     sales  base_gp  support  waste_credit   net_gp
cluster                                                                                      
CAM                    77  1288.60   73.70   8848.23  4867.37   144.32         17.87  5029.56
COM                   156  2221.50  132.12  15317.78  8453.24   141.05         17.74  8612.02
HWY                    75   958.00   71.00   6300.62  3478.02    57.22          0.00  3535.24
MET                   117  1800.50  112.50  13010.40  7115.52   195.50         48.56  7359.58
RUR                    56   621.75   50.75   3945.68  2181.81    36.14          0.00  2217.95

Chain total
units            6890.35
waste             440.08
sales           47422.72
base_gp         26095.96
scan              574.23
waste_credit       84.16
net_gp          26754.35

V

    … 1,773 more characters of output in the raw trajectory.

  27. 27Shell1

    Tool execution only — no assistant text

    Shellvia exec1k chars

    Arguments

    const r = await tools.exec_command({cmd:"python - <<'PY'\nimport pandas as pd\npos=pd.read_csv('data/weekly_pos_inventory_waste.csv')\nmaster=pd.read_csv('data/item_master_unit_economics.csv')\ncap=pd.read_csv('data/store_cluster_capacity.csv')\nprop=pd.read_csv('data/buyer_reset_proposal.csv')\ng=pos.groupby(['cluster_code','sku'],as_index=False).agg(sw=('stores_ranged','sum'),sales=('net_sales_units','sum'),waste=('waste_units','sum'))\ng=g.merge(master,on='sku').merge(cap[['cluster_code','store_count','deliveries_per_week']],on='cluster_code')\ng['uspw']=g.sales/g.sw;g['w

    … 1,548 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.7 seconds
Output:

Proposal rows with no local internal demand:
cluster_code      sku           item_x  proposed_facings  supplier_projection_units_per_store_week
         HWY GGS-3RZA Caprese Ciabatta                 1                                       2.5

Supported proposal subtotal by cluster (not executable where route/capacity conflict):
               units4  waste4    sales4  basegp4   scan4  wcred4   netgp4
cluster_code                                                             
CAM           1245.60   96.20   8923.71  4803.15  144.32    9.21  4956.67
COM           2301.62  204.33  16387.76  8756.00  217.10   34.76  9007.86
HWY            927.50   72.50   6129.02  3368.77   57.22    0.00  3426.00
MET           1914.00  126.00  14144.26  7703.29  195.50   77.58  7976.37
RUR            653.75   63.25   4246.31  2318.01   36.14    0.00  2354.15

Total supported pr

    … 168 more characters of output in the raw trajectory.

  28. 28Shell1

    Tool execution only — no assistant text

    Shellvia exec2k chars

    Arguments

    const r = await tools.exec_command({cmd:"python - <<'PY'\nimport pandas as pd\np=pd.read_csv('data/buyer_reset_proposal.csv')\nf={\n('MET','GGS-84QJ'):2,('MET','GGS-2VWK'):1,('MET','GGS-9PQL'):2,('MET','GGS-5MTC'):0,('MET','GGS-7DNL'):1,('MET','GGS-1KFV'):0,('MET','GGS-4HBP'):0,('MET','GGS-3RZA'):1,('MET','GGS-6BGH'):2,('MET','GGS-8XUY'):1,\n('COM','GGS-84QJ'):2,('COM','GGS-2VWK'):2,('COM','GGS-9PQL'):1,('COM','GGS-5MTC'):1,('COM','GGS-7DNL'):1,('COM','GGS-1KFV'):0,('COM','GGS-4HBP'):0,('COM','GGS-3RZA'):0,('COM','GGS-6BGH'):2,('COM','GGS-8XUY'):0,\n('CAM','GGS-84QJ'):2,('CAM'

    … 1,200 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.8 seconds
Output:

disposition
Accept    32
Change     7
Reject    11

Changed/rejected:
cluster_code      sku                      item proposed_action  proposed_facings  final_facings disposition
         MET GGS-9PQL    Southwest Chicken Bowl            Keep                 1              2      Change
         MET GGS-8XUY     Spicy Tuna Sushi Roll             Add                 2              1      Change
         COM GGS-84QJ       Chicken Caesar Wrap            Keep                 1              2      Change
         COM GGS-5MTC        Hummus Veggie Wrap          Remove                 0              1      Reject
         COM GGS-3RZA          Caprese Ciabatta             Add                 1              0      Reject
         COM GGS-8XUY     Spicy Tuna Sushi Roll             Add                 1              0      Reject
         CAM GGS-5MTC        Hummus

    … 1,288 more characters of output in the raw trajectory.

  29. 29The source reconciliation is complete. The proposal cannot be released as written: four clusters are each 0.5 tray slot…

    The source reconciliation is complete. The proposal cannot be released as written: four clusters are each 0.5 tray slot over capacity, and the sushi and Caprese expansions conflict with signed routing or internal pilot results. I’m now translating the revised decisions into an auditable workbook, including a route-limited Metro sushi exception rather than a clusterwide authorization.

  30. 30exec1

    Tool execution only — no assistant text

    execconst p = await tools.update_plan({explanation:"All source files have been extracted and reconciled. The final recommendation is set; I’m building the formula-driven workbook before drafting the memo from those validated outputs.",plan:[ {step:"Read the document and spreadsheet skill instructions",status:"completed"}, {step:"Inventory and analyze all attached source materials",status:"completed"}, {step:"Resolve item and cluster decisions, economics, and capacity",status:"completed"}, {step:"Build and validate the decision workbook",status:"in_progress"}1k chars

    Arguments

    const p = await tools.update_plan({explanation:"All source files have been extracted and reconciled. The final recommendation is set; I’m building the formula-driven workbook before drafting the memo from those validated outputs.",plan:[
  {step:"Read the document and spreadsheet skill instructions",status:"completed"},
  {step:"Inventory and analyze all attached source materials",status:"completed"},
  {step:"Resolve item and cluster decisions, economics, and capacity",status:"completed"},
  {step:"Build and validate the decision workbook",status:"in_progress"}

    … 876 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.7 seconds
Output:

RESULT 1
/root/.nvm/versions/node/v22.23.2/bin/node

RESULT 2
node:internal/modules/cjs/loader:1433
  throw err;
  ^

Error: Cannot find module 'docx'
Require stack:
- /workspace/[eval]
    at Function._resolveFilename (node:internal/modules/cjs/loader:1430:15)
    at defaultResolveImpl (node:internal/modules/cjs/loader:1040:19)
    at resolveForCJSWithHooks (node:internal/modules/cjs/loader:1045:22)
    at Function._load (node:internal/modules/cjs/loader:1216:25)
    at wrapModuleLoad (node:internal/modules/cjs/loader:254:19)
    at Module.require (node:internal/modules/cjs/loader:1527:12)
    at require (node:internal/modules/helpers:147:16)
    at [eval]:1:1
    at runScriptInThisContext (node:internal/vm:209:10)
    at node:internal/process/execution:446:12 {
  code: 'MODULE_NOT_FOUND',
  requireStack: [ '/wor

    … 188 more characters of output in the raw trajectory.

  31. 31Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"mkdir -p /workspace/output","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":1000});
text(r.output);

    Output

    Script completed
Wall time 0.1 seconds
Output:
  32. 32exec1

    Tool execution only — no assistant text

    execconst patch = "*** Begin Patch\n*** Add File: build_reset_workbook.py\n+import csv\n+from datetime import datetime\n+from pathlib import Path\n+\n+from openpyxl import Workbook\n+from openpyxl.comments import Comment\n+from openpyxl.formatting.rule import CellIsRule, FormulaRule\n+from openpyxl.styles import Alignment, Border, Font, PatternFill, Side\n+from openpyxl.utils import get_column_letter\n+from openpyxl.worksheet.table import Table, TableStyleInfo\n+\n+\n+ROOT = Path(\"/workspace\")\n+DATA = ROOT / \"data\"\n+OUT = ROOT / \"output\" / \"reset_d

    Arguments

    const patch = "*** Begin Patch\n*** Add File: build_reset_workbook.py\n+import csv\n+from datetime import datetime\n+from pathlib import Path\n+\n+from openpyxl import Workbook\n+from openpyxl.comments import Comment\n+from openpyxl.formatting.rule import CellIsRule, FormulaRule\n+from openpyxl.styles import Alignment, Border, Font, PatternFill, Side\n+from openpyxl.utils import get_column_letter\n+from openpyxl.worksheet.table import Table, TableStyleInfo\n+\n+\n+ROOT = Path(\"/workspace\")\n+DATA = ROOT / \"data\"\n+OUT = ROOT / \"output\" / \"reset_d

    … 52,464 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.0 seconds
Output:

{}
  33. 33Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"python -m py_compile build_reset_workbook.py","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":5000});
text(r.output);

    Output

    Script completed
Wall time 0.2 seconds
Output:
  34. 34Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"python build_reset_workbook.py","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":10000});
text(r.output);

    Output

    Script completed
Wall time 1.7 seconds
Output:

/workspace/output/reset_decision_workbook.xlsx
  35. 35Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"python /root/.agents/skills/xlsx/scripts/recalc.py output/reset_decision_workbook.xlsx 60","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":10000});
text(r.output);
if(r.session_id) text(`SESSION_ID=${r.session_id}`);

    Output

    Script completed
Wall time 3.2 seconds
Output:

status: success
total_errors: 0
error_summary: {}
total_formulas: 3927
  36. 36Shell1

    Tool execution only — no assistant text

    Shellvia exec1k chars

    Arguments

    const r = await tools.exec_command({cmd:"python - <<'PY'\nfrom openpyxl import load_workbook\np='output/reset_decision_workbook.xlsx'\nwbv=load_workbook(p,data_only=True,read_only=True)\nprint('Sheets:',wbv.sheetnames)\nws=wbv['Decision Summary']\nfor cell in ['B14','B15','B16','G14','G15','G16','G17','G18','G19']:\n    print(cell,ws[cell].value)\nprint('\\nCapacity')\nws=wbv['Capacity Check']\nfor r in range(6,11):\n    print([ws.cell(r,c).value for c in range(1,14)])\nprint('\\nFinal economics')\nws=wbv['Final Assortment']\nfor r in range(14,22): print(ws.cell(r,

    … 473 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 1.1 seconds
Output:

Sheets: ['Decision Summary', 'Source POS', 'Source Item Master', 'Source Capacity', 'Source Proposal', 'Signed Terms', 'Proposal Reconciliation', 'Item Economics', 'Capacity Check', 'Final Assortment']
B14 32 accept / 7 change / 11 reject
B15 4 of 5 clusters over
B16 5 of 5 clusters fit
G14 47422.7165
G15 440.075
G16 0.0600340362257304
G17 26095.956
G18 658.3945
G19 26754.3505

Capacity
['MET', 'Metro Core', 18, 5, 12, 12, 0, 'Fits', 10.5, 12, 1.5, 0, 'Fits - full facings']
['COM', 'Commuter Suburban', 26, 4, 10, 10.5, -0.5, 'OVER CAPACITY', 10, None, 0, None, 'Fits - full facings']
['CAM', 'Campus / Hospital', 11, 5, 10, 10.5, -0.5, 'OVER CAPACITY', 10, None, 0, None, 'Fits - full facings']
['HWY', 'Highway / Travel', 15, 3, 8, 8.5, -0.5, 'OVER CAPACITY', 7.5, None, 0.5, None, 'Fits - full facings']
['RUR', 'Rural North', 14, 2, 7, 7.5, -0.5, 'OVER CAP

    … 432 more characters of output in the raw trajectory.

  37. 37The workbook is built and recalculated successfully: 3,927 formulas, zero Excel errors, and the key checks reconcile to…

    The workbook is built and recalculated successfully: 3,927 formulas, zero Excel errors, and the key checks reconcile to 32 accepts, 7 changes, 11 rejects; four proposal clusters over capacity; all final variants fit. I’m doing the visual QA now, then I’ll draft the memo directly from these locked outputs.

  38. 38Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"libreoffice --headless --convert-to pdf --outdir /tmp output/reset_decision_workbook.xlsx","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":5000});
text(r.output);

    Output

    Script completed
Wall time 1.6 seconds
Output:

Warning: failed to launch javaldx - java may not function correctly
convert /workspace/output/reset_decision_workbook.xlsx as a Calc document -> /tmp/reset_decision_workbook.pdf using filter : calc_pdf_Export
  39. 39Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"pdfinfo /tmp/reset_decision_workbook.pdf","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":3000});
text(r.output);

    Output

    Script completed
Wall time 0.1 seconds
Output:

Author:          openpyxl
Creator:         Calc
Producer:        LibreOffice 25.2.3.2 (X86_64) / LibreOffice Community
CreationDate:    Thu Aug 20 02:50:32 2026 UTC
Custom Metadata: no
Metadata Stream: yes
Tagged:          yes
UserProperties:  no
Suspects:        no
Form:            none
JavaScript:      no
Pages:           14
Encrypted:       no
Page size:       612 x 792 pts (letter)
Page rot:        0
File size:       2567549 bytes
Optimized:       no
PDF version:     1.7
  40. 40Shell1

    Tool execution only — no assistant text

    Shellvia exec3k chars

    Arguments

    const r = await tools.exec_command({cmd:"python - <<'PY'\nfrom pypdf import PdfReader\nr=PdfReader('/tmp/reset_decision_workbook.pdf')\nfor i,p in enumerate(r.pages,1):\n    t=(p.extract_text() or '').replace('\\n',' | ')\n    print(i, t[:180])\nPY","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":5000});
text(r.output);

    Output

    Script completed
Wall time 1.4 seconds
Output:

1 Blue Mesa Market | Internal planning use Page 1 of 14 | Blue Mesa Market | Refrigerated Grab-and-Go Reset | Merchant recommendation for the first four weeks of the July 2026 reset.
2 Blue Mesa Market | Internal planning use Page 2 of 14 | Source POS | Source: weekly_pos_inventory_waste.csv. Imported without demand or term adjustments. | week_start cluster_code 
3 Blue Mesa Market | Internal planning use Page 3 of 14 | 2026-04-06HWY Highway / Travel GGS-9PQL Southwest Chicken Bowl Current set 15 35 4 0.1 43 28 | 2026-04-13HWY Highway / Trave
4 Blue Mesa Market | Internal planning use Page 4 of 14 | 2026-05-25COM Commuter Suburban GGS-1KFV Egg Salad Croissant Current set 26 33 7 0.6 37 53 | 2026-04-06CAM Campus / Hospital
5 Blue Mesa Market | Internal planning use Page 5 of 14 | 2026-05-18CAM Campus / Hospital GGS-6BGH Protein Snack Box Controlled pilot 5 29 1 0.8

    … 1,523 more characters of output in the raw trajectory.

  41. 41Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const pages=[1,9,10,11,13,14];
const rs=await Promise.all(pages.map(p=>tools.exec_command({cmd:`pdftoppm -f ${p} -l ${p} -png -r 120 /tmp/reset_decision_workbook.pdf /tmp/wb_${p}`,workdir:"/workspace",yield_time_ms:10000,max_output_tokens:1000})));
rs.forEach((r,i)=>text(`p${pages[i]} ${r.output}`));

    Output

    Script completed
Wall time 0.5 seconds
Output:

p1 
p9 
p10 
p11 
p13 
p14
  42. 42Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"ls -1 /tmp/wb_*.png","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":3000});
text(r.output);

    Output

    Script completed
Wall time 0.1 seconds
Output:

/tmp/wb_1-01.png
/tmp/wb_10-10.png
/tmp/wb_11-11.png
/tmp/wb_13-13.png
/tmp/wb_14-14.png
/tmp/wb_9-09.png
  43. 43exec1

    Tool execution only — no assistant text

    execconst files=["/tmp/wb_1-01.png","/tmp/wb_9-09.png","/tmp/wb_10-10.png","/tmp/wb_11-11.png","/tmp/wb_13-13.png","/tmp/wb_14-14.png"]; for (const f of files){const r=await tools.view_image({path:f,detail:"original"}); image(r.image_url,"original");}551k chars

    Arguments

    const files=["/tmp/wb_1-01.png","/tmp/wb_9-09.png","/tmp/wb_10-10.png","/tmp/wb_11-11.png","/tmp/wb_13-13.png","/tmp/wb_14-14.png"];
for (const f of files){const r=await tools.view_image({path:f,detail:"original"}); image(r.image_url,"original");}

    Output

    Script completed
Wall time 0.1 seconds
Output:

    … 550,370 more characters of output in the raw trajectory.

  44. 44exec1

    Tool execution only — no assistant text

    execconst patch = "*** Begin Patch\n*** Update File: build_reset_workbook.py\n@@\n-for c, width in enumerate([15, 16, 16, 18, 3, 20, 18, 15, 23, 58], 1):\n+for c, width in enumerate([15, 16, 16, 18, 16, 20, 18, 15, 23, 58], 1):\n@@\n for ws in wb.worksheets:\n ws.sheet_properties.pageSetUpPr.fitToPage = True\n+ ws.page_setup.orientation = \"landscape\"\n+ ws.page_setup.paperSize = ws.PAPERSIZE_LETTER\n*** End Patch"; text(await tools.apply_patch(patch));

    Arguments

    const patch = "*** Begin Patch\n*** Update File: build_reset_workbook.py\n@@\n-for c, width in enumerate([15, 16, 16, 18, 3, 20, 18, 15, 23, 58], 1):\n+for c, width in enumerate([15, 16, 16, 18, 16, 20, 18, 15, 23, 58], 1):\n@@\n for ws in wb.worksheets:\n     ws.sheet_properties.pageSetUpPr.fitToPage = True\n+    ws.page_setup.orientation = \"landscape\"\n+    ws.page_setup.paperSize = ws.PAPERSIZE_LETTER\n*** End Patch";
text(await tools.apply_patch(patch));

    Output

    Script completed
Wall time 0.0 seconds
Output:

{}
  45. 45Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"python build_reset_workbook.py","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":3000});
text(r.output);

    Output

    Script completed
Wall time 1.5 seconds
Output:

/workspace/output/reset_decision_workbook.xlsx
  46. 46Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"python /root/.agents/skills/xlsx/scripts/recalc.py output/reset_decision_workbook.xlsx 60","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":5000});
text(r.output);

    Output

    Script completed
Wall time 2.1 seconds
Output:

status: success
total_errors: 0
error_summary: {}
total_formulas: 3927
  47. 47Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"npm install --prefix /tmp/docx_build docx","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":5000});
text(r.output);
if(r.session_id) text(`SESSION_ID=${r.session_id}`);

    Output

    Script completed
Wall time 1.8 seconds
Output:


added 22 packages in 2s

1 package is looking for funding
  run `npm fund` for details
  48. 48exec1

    Tool execution only — no assistant text

    execconst patch = "*** Begin Patch\n*** Add File: build_grab_go_memo.js\n+const fs = require(\"fs\");\n+const {\n+ AlignmentType,\n+ BorderStyle,\n+ Document,\n+ Footer,\n+ Header,\n+ HeadingLevel,\n+ LevelFormat,\n+ PageBreak,\n+ PageNumber,\n+ Paragraph,\n+ Packer,\n+ ShadingType,\n+ Table,\n+ TableCell,\n+ TableRow,\n+ TextRun,\n+ WidthType,\n+} = require(\"/tmp/docx_build/node_modules/docx\");\n+\n+const OUT = \"/workspace/output/grab_go_reset_memo.docx\";\n+const W = 10368;\n+const NAVY = \"1F4E78\";\n+const TEAL = \"0F6B

    Arguments

    const patch = "*** Begin Patch\n*** Add File: build_grab_go_memo.js\n+const fs = require(\"fs\");\n+const {\n+  AlignmentType,\n+  BorderStyle,\n+  Document,\n+  Footer,\n+  Header,\n+  HeadingLevel,\n+  LevelFormat,\n+  PageBreak,\n+  PageNumber,\n+  Paragraph,\n+  Packer,\n+  ShadingType,\n+  Table,\n+  TableCell,\n+  TableRow,\n+  TextRun,\n+  WidthType,\n+} = require(\"/tmp/docx_build/node_modules/docx\");\n+\n+const OUT = \"/workspace/output/grab_go_reset_memo.docx\";\n+const W = 10368;\n+const NAVY = \"1F4E78\";\n+const TEAL = \"0F6B

    … 24,718 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.0 seconds
Output:

{}
  49. 49Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"node build_grab_go_memo.js","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":5000});
text(r.output);

    Output

    Script completed
Wall time 0.3 seconds
Output:

/workspace/output/grab_go_reset_memo.docx
  50. 50Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"python /root/.agents/skills/docx/scripts/office/validate.py output/grab_go_reset_memo.docx","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":5000});
text(r.output);

    Output

    Script completed
Wall time 1.2 seconds
Output:


Paragraphs: 0 → 234 (+234)
All validations PASSED!
  51. 51Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"python /root/.agents/skills/docx/scripts/office/soffice.py --headless --convert-to pdf --outdir /tmp output/grab_go_reset_memo.docx","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":5000});
text(r.output);

    Output

    Script completed
Wall time 1.0 seconds
Output:

Warning: failed to launch javaldx - java may not function correctly
convert /workspace/output/grab_go_reset_memo.docx as a Writer document -> /tmp/grab_go_reset_memo.pdf using filter : writer_pdf_Export
  52. 52Shell1

    Tool execution only — no assistant text

    Shellvia exec19k chars

    Arguments

    const rs = await Promise.all([
  tools.exec_command({cmd:"pdfinfo /tmp/grab_go_reset_memo.pdf","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":3000}),
  tools.exec_command({cmd:"pdftotext -layout /tmp/grab_go_reset_memo.pdf -","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":30000})
]);
rs.forEach((r,i)=>{text(`RESULT ${i+1}\n${r.output}`)});

    Output

    Script completed
Wall time 0.1 seconds
Output:

RESULT 1
Title:           Blue Mesa Market Grab-and-Go Reset Recommendation
Author:          OpenAI
Creator:         Writer
Producer:        LibreOffice 25.2.3.2 (X86_64) / LibreOffice Community
CreationDate:    Thu Aug 20 02:53:24 2026 UTC
Custom Metadata: no
Metadata Stream: yes
Tagged:          yes
UserProperties:  no
Suspects:        no
Form:            none
JavaScript:      no
Pages:           5
Encrypted:       no
Page size:       612 x 792 pts (letter)
Page rot:        0
File size:       143245 bytes
Optimized:       no
PDF version:     1.7

RESULT 2
BLUE MESA MARKET                                                                     Prepared Foods | Internal
REFRIGERATED GRAB-AND-GO RESET

First-four-week merchant recommendation
To: L. Moreno, Senior Merchant - Prepared Foods        From: Category Plan

    … 17,613 more characters of output in the raw trajectory.

  53. 53Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"python - <<'PY'\nfrom openpyxl import load_workbook\nw=load_workbook('output/reset_decision_workbook.xlsx',data_only=True,read_only=True)['Item Economics']\nprint(sum((w.cell(r,39).value or 0) for r in range(6,56)))\nprint(sum((w.cell(r,40).value or 0) for r in range(6,56)))\nprint(sum((w.cell(r,43).value or 0) for r in range(6,56)))\nPY","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":1000});
text(r.output);

    Output

    Script completed
Wall time 2.3 seconds
Output:

27423.170499999997
1327.2144999999996
26754.350499999997
  54. 54exec1

    Tool execution only — no assistant text

    execconst patch = "*** Begin Patch\n*** Update File: build_grab_go_memo.js\n@@\n- const content = Array.isArray(value) ? value : [p(value, { after: 0 })];\n+ const content = Array.isArray(value) ? value : [p(value, { after: 0, size: opts.bodySize || 20 })];\n@@\n- [\"Rural low-repeat items\", \"Remove Egg Salad and Bowl\", \"Egg 0.72 U/SPW, 24.3% waste; Bowl 1.38, 19.3%, 1.52 weeks of ending inventory\", \"Two delivery days and large case/slot requirements make forced range breadth operationally expensive.\"],\n ];\n@@\n- width: { size: W, type

    Arguments

    const patch = "*** Begin Patch\n*** Update File: build_grab_go_memo.js\n@@\n-      const content = Array.isArray(value) ? value : [p(value, { after: 0 })];\n+      const content = Array.isArray(value) ? value : [p(value, { after: 0, size: opts.bodySize || 20 })];\n@@\n-  [\"Rural low-repeat items\", \"Remove Egg Salad and Bowl\", \"Egg 0.72 U/SPW, 24.3% waste; Bowl 1.38, 19.3%, 1.52 weeks of ending inventory\", \"Two delivery days and large case/slot requirements make forced range breadth operationally expensive.\"],\n ];\n@@\n-        width: { size: W, type

    … 3,993 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.0 seconds
Output:

{}
  55. 55Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"node build_grab_go_memo.js","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":3000});
text(r.output);

    Output

    Script completed
Wall time 0.4 seconds
Output:

/workspace/output/grab_go_reset_memo.docx
  56. 56Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const rs = await Promise.all([
  tools.exec_command({cmd:"python /root/.agents/skills/docx/scripts/office/validate.py output/grab_go_reset_memo.docx","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":3000}),
  tools.exec_command({cmd:"unzip -t output/grab_go_reset_memo.docx","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":3000}),
  tools.exec_command({cmd:"unzip -t output/reset_decision_workbook.xlsx","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":3000})
]);
rs.forEach((r,i)=>{text(`RESULT ${i+1}\n$

    … 19 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 1.1 seconds
Output:

RESULT 1

Paragraphs: 0 → 230 (+230)
All validations PASSED!

RESULT 2
/bin/bash: line 1: unzip: command not found

RESULT 3
/bin/bash: line 1: unzip: command not found
  57. 57Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"python /root/.agents/skills/docx/scripts/office/soffice.py --headless --convert-to pdf --outdir /tmp output/grab_go_reset_memo.docx","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":3000});
text(r.output);

    Output

    Script completed
Wall time 0.9 seconds
Output:

Warning: failed to launch javaldx - java may not function correctly
convert /workspace/output/grab_go_reset_memo.docx as a Writer document -> /tmp/grab_go_reset_memo.pdf using filter : writer_pdf_Export
Overwriting: /tmp/grab_go_reset_memo.pdf
  58. 58Shell1

    Tool execution only — no assistant text

    Shellvia exec1k chars

    Arguments

    const rs=await Promise.all([
  tools.exec_command({cmd:"pdfinfo /tmp/grab_go_reset_memo.pdf | rg 'Pages|Page size|File size'","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":1000}),
  tools.exec_command({cmd:"pdftotext -layout /tmp/grab_go_reset_memo.pdf - | rg -n 'RECOMMENDATION|deliveries/w|Rural and shrink|Release instructions|Page [0-9] of'","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":5000})
]);
rs.forEach((r,i)=>{text(`RESULT ${i+1}\n${r.output}`)});

    Output

    Script completed
Wall time 0.1 seconds
Output:

RESULT 1
Pages:           4
Page size:       612 x 792 pts (letter)
File size:       140299 bytes

RESULT 2
10:  RECOMMENDATION                revised cluster sets below, with a separate Metro M-11 sushi
57:Confidential - merchant decision support                                                               Page 1 of 4
70: deliveries/wk                                                           default /
80: deliveries/wk
88: deliveries/wk
97: deliveries/wk
104: deliveries/wk
131:Confidential - merchant decision support                                                                    Page 2 of 4
190:Rural and shrink read-through: Remove Egg Salad (0.72 U/SPW; 24.3% waste) and Southwest
199:Confidential - merchant decision support                                                                      Page 3 of 4
202:Rele

    … 156 more characters of output in the raw trajectory.

  59. 59The memo is now a clean four-page merchant document and has passed DOCX validation. I corrected the economics cross-chec…

    The memo is now a clean four-page merchant document and has passed DOCX validation. I corrected the economics cross-check to the workbook ($1,327 projected shrink cost), tightened the pagination, and am completing the last image-level review of all four pages.

  60. 60Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"pdftoppm -png -r 130 /tmp/grab_go_reset_memo.pdf /tmp/memo_final","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":1000});
text(r.output);

    Output

    Script completed
Wall time 1.6 seconds
Output:
  61. 61exec1

    Tool execution only — no assistant text

    execconst files=["/tmp/memo_final-1.png","/tmp/memo_final-2.png","/tmp/memo_final-3.png","/tmp/memo_final-4.png"]; for (const f of files){const r=await tools.view_image({path:f,detail:"original"}); image(r.image_url,"original");}1.8M chars

    Arguments

    const files=["/tmp/memo_final-1.png","/tmp/memo_final-2.png","/tmp/memo_final-3.png","/tmp/memo_final-4.png"];
for (const f of files){const r=await tools.view_image({path:f,detail:"original"}); image(r.image_url,"original");}

    Output

    Script completed
Wall time 0.1 seconds
Output:

    … 1,776,658 more characters of output in the raw trajectory.

  62. 62Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"libreoffice --headless --convert-to pdf --outdir /tmp output/reset_decision_workbook.xlsx","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":3000});
text(r.output);

    Output

    Script completed
Wall time 1.6 seconds
Output:

Warning: failed to launch javaldx - java may not function correctly
convert /workspace/output/reset_decision_workbook.xlsx as a Calc document -> /tmp/reset_decision_workbook.pdf using filter : calc_pdf_Export
Overwriting: /tmp/reset_decision_workbook.pdf
  63. 63Shell1

    Tool execution only — no assistant text

    Shellvia exec2k chars

    Arguments

    const r = await tools.exec_command({cmd:"python - <<'PY'\nfrom pypdf import PdfReader\nr=PdfReader('/tmp/reset_decision_workbook.pdf')\nprint('pages',len(r.pages))\nfor i,p in enumerate(r.pages,1):\n t=(p.extract_text() or '').replace('\\n',' | ')\n print(i,t[:100])\nPY","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":5000});
text(r.output);

    Output

    Script completed
Wall time 1.4 seconds
Output:

pages 15
1 Blue Mesa Market | Internal planning use Page 1 of 15 | Blue Mesa Market | Refrigerated Grab-and-Go 
2 Blue Mesa Market | Internal planning use Page 2 of 15 | Source POS | Source: weekly_pos_inventory_wa
3 Blue Mesa Market | Internal planning use Page 3 of 15 | 2026-04-13CAM Campus / Hospital GGS-2VWK Tur
4 Blue Mesa Market | Internal planning use Page 4 of 15 | 2026-04-13MET Metro Core GGS-5MTC Hummus Veg
5 Blue Mesa Market | Internal planning use Page 5 of 15 | 2026-04-13HWY Highway / Travel GGS-7DNL Cobb
6 Blue Mesa Market | Internal planning use Page 6 of 15 | 2026-04-13COM Commuter Suburban GGS-4HBP Tur
7 Blue Mesa Market | Internal planning use Page 7 of 15 | 2026-04-13COM Commuter Suburban GGS-6BGH Pro
8 Blue Mesa Market | Internal planning use Page 8 of 15 | Source Item Master | Source: item_master_uni
9 Blue Mesa Market | Internal planning

    … 698 more characters of output in the raw trajectory.

  64. 64Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const pages=[1,14,15];
const rs=await Promise.all(pages.map(p=>tools.exec_command({cmd:`pdftoppm -f ${p} -l ${p} -png -r 120 /tmp/reset_decision_workbook.pdf /tmp/wb_final_${p}`,workdir:"/workspace",yield_time_ms:10000,max_output_tokens:1000})));
rs.forEach((r,i)=>text(`p${pages[i]} ${r.output}`));

    Output

    Script completed
Wall time 0.3 seconds
Output:

p1 
p14 
p15
  65. 65exec1

    Tool execution only — no assistant text

    execconst files=["/tmp/wb_final_1-01.png","/tmp/wb_final_14-14.png","/tmp/wb_final_15-15.png"]; for (const f of files){const r=await tools.view_image({path:f,detail:"original"}); image(r.image_url,"original");}497k chars

    Arguments

    const files=["/tmp/wb_final_1-01.png","/tmp/wb_final_14-14.png","/tmp/wb_final_15-15.png"];
for (const f of files){const r=await tools.view_image({path:f,detail:"original"}); image(r.image_url,"original");}

    Output

    Script completed
Wall time 0.1 seconds
Output:

    … 496,212 more characters of output in the raw trajectory.

  66. 66Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({cmd:"ls -lh output && python /root/.agents/skills/xlsx/scripts/recalc.py output/reset_decision_workbook.xlsx 60","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":5000});
text(r.output);
if(r.session_id) text(`SESSION_ID=${r.session_id}`);

    Output

    Script completed
Wall time 2.1 seconds
Output:

total 132K
-rw-r--r-- 1 root root  19K Aug 20 02:54 grab_go_reset_memo.docx
-rw-r--r-- 1 root root 110K Aug 20 02:51 reset_decision_workbook.xlsx
{
  "status": "success",
  "total_errors": 0,
  "error_summary": {},
  "total_formulas": 3927
}
  67. 67exec1

    Tool execution only — no assistant text

    execconst r = await tools.update_plan({explanation:"Both deliverables are complete. The workbook recalculates with zero formula errors, and the memo passed DOCX validation plus four-page visual review.",plan:[ {step:"Read the document and spreadsheet skill instructions",status:"completed"}, {step:"Inventory and analyze all attached source materials",status:"completed"}, {step:"Resolve item and cluster decisions, economics, and capacity",status:"completed"}, {step:"Build and validate the decision workbook",status:"completed"}, {step:"Draft, render, and va

    Arguments

    const r = await tools.update_plan({explanation:"Both deliverables are complete. The workbook recalculates with zero formula errors, and the memo passed DOCX validation plus four-page visual review.",plan:[
  {step:"Read the document and spreadsheet skill instructions",status:"completed"},
  {step:"Inventory and analyze all attached source materials",status:"completed"},
  {step:"Resolve item and cluster decisions, economics, and capacity",status:"completed"},
  {step:"Build and validate the decision workbook",status:"completed"},
  {step:"Draft, render, and va

    … 68 more characters of arguments in the raw trajectory.

    Output

    Script completed
Wall time 0.0 seconds
Output:

{}
  68. 68Completed both deliverables. Recommendation: approve only after revisions; four proposed clusters exceed capacity, and s…

    Completed both deliverables. Recommendation: approve only after revisions; four proposed clusters exceed capacity, and sushi must remain limited to verified Metro M-11 stores.

    • Merchant memo
    • Decision workbook

    Workbook validation: 3,927 formulas, zero errors.

3 failure modes across 3 verifier failures

  1. 1Unsupported Permission or Source Fact IntroducedView on Failure Modes ↗Input and Instruction Comprehension1 failure

    Description

    Does the recommendation depend on a waiver, approval, route, credit, corrective action, operating permission, or factual premise that is not documented in the packet?

    Failure evidence · per affected verifier

    • The memo counts a $149 Caprese scan allowance that is not among the signed vendor credits the packet documents.

  2. 2Quantity, Cost, Capacity, or Rate Calculation WrongView on Failure Modes ↗Reasoning and Computation1 failure

    Description

    With the correct source rows and eligibility decisions available, is a required order quantity, excess, cost, credit, capacity, production-mix value, threshold flag, or weighted rate calculated incorrectly?

    Failure evidence · per affected verifier

    • The workbook correctly shows live capacity and the buyer-proposal overages, but the final reconciled tray-slot totals per cluster do not match the required final values.

  3. 3Required Rationale or Authority Statement OmittedView on Failure Modes ↗Presentation and Communication1 failure

    Description

    Is the underlying decision correct or substantially present, but the memo fails to state a required rule hierarchy, source-governance principle, item-specific reason, signed-term basis, or operating condition?

    Failure evidence · per affected verifier

    • The memo protects Chicken Caesar Wrap and gives Protein Snack Box launch space but never states the full required rationale together: OOS pressure for Caesar, and pilot performance, low waste, code date, and scan credit for Protein Snack Box.