EKWbench

task_116Retail trade

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

TaxonomyRetail tradeGeneral and operations managers

All trialsGPT-5.6 TerracodexTrial 03

63%

Trial reward

GPT-5.6 TerraFail

Trial 03 — 1st of 4 by reward score. This model averages 59.2% across 4 trials on this task.

  • 10/15Core verifiers passed
  • 12/18All verifiers passed
  • 5Core failed
  • 43Turns
  • 33Tool calls
  • $1.48Cost
  • 21.3mTime
  • 57kOutput tokens

Missed 5 of 15 core — capacity, traffic_profit and execution and 2 more, plus 1 secondary.

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

  • capacityLLMFail
    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

    Failure mode Required Numeric Summary Missing or Inconsistent

    Why it failed

    The memo states only a general or partial capacity picture and never lays out all four buyer-proposal cluster overages with their exact numbers.

    Justification

    The memo identifies buyer-proposal capacity issues in Commuter, Campus, Highway, and Rural and says no extra July tray/driver stop is assumed, but it does not provide the required numeric reconciliations for each cluster: Commuter Suburban 10.5 vs 10.0, Campus / Hospital 10.5 vs 10.0, Highway / Travel 8.5 vs 8.0, and Rural North 7.5 vs 7.0. It states over-capacity only in general terms ('by 0.5 tray slot each').

  • 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

    Protein Snack Box is clearly given launch space and support ('Add Protein Snack Box at two facings...' plus five-day code, low pilot waste, pilot GP, and a signed $0.35 scanned-unit allowance), but the memo does not identify Chicken Caesar Wrap as a protected/expanded priority item because it is a core lunch traffic driver with OOS pressure. Chicken Caesar is only listed in the final assortments, so the full rubric is not satisfied.

  • 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_controlLLMPass
    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

  • executionLLMFail
    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

    Failure mode Allocation or Selection Plan Incorrect

    Why it failed

    The memo's cluster-level final facings and slot totals consistently differ from the required exact values for Metro, Highway, and Rural North.

    Justification

    The memo gives cluster-level facings and slot totals, but it does not match the required final outcomes. Metro Core is split into 'M-11: 11.5/12' and 'Other Metro: 10.0/12' and keeps Hummus 1 instead of the required 12.0 slots with Hummus 0; Commuter is 9.0/10 instead of 10.0; Highway has Protein 2 instead of 1; and Rural North is 5.0/7 instead of 6.0. Because all rubric-specified cluster outcomes are not satisfied, it fails.

  • 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_facingsLLMFail
    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

    Failure mode Allocation or Selection Plan Incorrect

    Why it failed

    The workbook's final facing counts for Chicken Caesar Wrap, Southwest Chicken Bowl, and the other graded SKUs consistently differ from the required per-cluster values.

    Justification

    The final facing plan does not match the required values. In Final Decisions, Chicken Caesar Wrap (GGS-84QJ) is 2/1/2/1/1 across Metro/Commuter/Campus/Highway/Rural, but rubric requires 2/2/2/2/2, including no cluster below 2. There are also other mismatches: Southwest Chicken Bowl (GGS-9PQL) is Metro 1 instead of 2, and Protein Snack Box (GGS-6BGH) is Highway 2 instead of 1. Spicy Tuna Sushi Roll is correctly 1 only in Metro and 0 elsewhere, but multiple graded SKU facings differ materially, so the criterion fails.

  • 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 extract references a 'Capacity Check' sheet in the Read Me, but it does not show a cluster-level capacity reconciliation table with live capacity, buyer-proposal tray slots, final tray slots, variance to capacity, and pass/fail or over/under indicators. It only shows Cluster Capacity, item-level proposal/final tray slots, and a summary ('Final planograms that fit capacity 6 of 6'). Also, summing the visible Final Decisions gives final slot totals of MET 11.5, COM 9.0, CAM 10.0, HWY 7.5, and RUR 5.0, not the required 12.0, 10.0, 10.0, 7.5, and 6.0.

  • 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_disciplineLLMFail
    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

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

    Why it failed

    The memo correctly argues for leaving some capacity open rather than force-filling weak items, but the specific Highway and Rural North open-slot numbers do not match the required 7.5/8.0 and 6.0/7.0 values.

    Justification

    The memo does endorse leaving space open (e.g., “leave its capacity open rather than backfilling it” and “Two trays stay open by design”) and rejects weak/unsupported items like Egg Salad, Caprese, Turkey Cranberry, and Sushi in poor-fit clusters. However, it does not meet the required numeric framing: Highway / Travel is shown as 7.5 / 8 but not explicitly as 0.5 open, and Rural North is shown as 5.0 / 7 with two trays open, not 6.0 / 7 with 1.0 open.

  • 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.docx14 KB

RECOMMENDATION MEMO

Refrigerated Grab-and-Go July Reset — First Four Weeks

To

From

Subject

Senior Merchant, Prepared Foods

Category Planning

Revised reset release recommendation

Decision

Do not release the buyer proposal as written. Release the revised set in this memo: it fits every first-four-week planogram, protects credible vegetarian lunch coverage, keeps the strongest core items, and removes route, code-date, seasonal, and capacity failures. The recommendation uses the merchant handoff as the business-rule authority, internal eight-week records as the demand signal, and signed offer letters for route and credit terms.

What changes before release

Keep Hummus in every cluster. Add Caprese only in Metro and Campus; retain Hummus alongside it in those two clusters because internal results support both and Sushi removals/reductions create the space.

Add Protein Snack Box at two facings in Metro, Commuter, Campus, and Highway; use one facing in Rural. The five-day code and low pilot waste support the space, while Rural gets a deliberately lighter launch.

Limit Spicy Tuna Sushi to one full facing in Metro M-11 stores only. Reject the Commuter and Campus Sushi adds and do not place Sushi in other Metro stores.

Remove Turkey Cranberry everywhere, including the proposed Highway holdover. Remove Egg Salad everywhere, including Rural. Remove Southwest Bowl in Rural; leave its capacity open rather than backfilling it with another low-repeat item.

Highest-risk proposal conflicts

Risk

Why the proposal fails

Final control

Sushi expansion

Only Metro M-11 has signed daily service and waste credit. Commuter/Campus were line-review tests, not launch commitments.

One M-11 facing only; no holdover; no Sushi outside M-11.

Capacity overage

Commuter, Campus, Highway, and Rural exceed live capacity by 0.5 tray slot. Partial facings are not allowed.

Use the final facings below; no extra July tray, lease-line, or driver stop is assumed.

Vegetarian swap

Highway/Rural Caprese routing is not approved; Egg Salad cannot be the only vegetarian option.

Retain one Hummus face in every cluster; Caprese only Metro/Campus.

Winter carryover

Turkey Cranberry is a winter feature with no Q3 return/billback authorization and weak internal economics.

Remove from every July planogram and ordering file.

Revised cluster-level assortment

Facings below are full facings. Tray usage uses the item-master slot requirement; a Southwest Bowl or Sushi facing uses 1.5 tray slots.

Cluster

Final assortment and facings

Final tray slots

Release instruction

Metro Core

Chicken Caesar 2; Turkey Club 1; Southwest Bowl 1; Hummus 1; Cobb 1; Caprese 1; Protein 2; Sushi 1 in M-11 only.

M-11: 11.5 / 12; Other Metro: 10.0 / 12

Use a separate M-11 sushi overlay. Do not range Sushi in other Metro stores.

Commuter Suburban

Chicken Caesar 1; Turkey Club 2; Southwest Bowl 1; Hummus 1; Cobb 1; Protein 2.

9.0 / 10

Do not swap Hummus for Caprese; do not add Sushi.

Campus / Hospital

Chicken Caesar 2; Turkey Club 1; Southwest Bowl 1; Hummus 1; Cobb 1; Caprese 1; Protein 2.

10.0 / 10

No Sushi. Hummus plus Caprese protects the meatless lunch mission.

Highway / Travel

Chicken Caesar 1; Turkey Club 2; Southwest Bowl 1; Hummus 1; Protein 2.

7.5 / 8

No Caprese or Turkey Cranberry. Keep Hummus to one face.

Rural North

Chicken Caesar 1; Turkey Club 2; Hummus 1; Protein 1.

5.0 / 7

No Bowl, Egg Salad, Caprese, or Sushi. Two trays stay open by design.

All six final planograms pass capacity and credible-vegetarian checks. The original proposal exceeded capacity in Commuter, Campus, Highway, and Rural by 0.5 tray slot each; the revised plan fits without a partial facing.

Economics supporting the changes

Internal results below are average weekly sales per ranged store and gross profit after waste. Gross profit after waste is calculated before any uncertain vendor waste-credit booking; signed support is shown as an operating benefit, not as proof of demand.

Decision point

Internal result

Recommendation rationale

Caprese: Metro / Campus vs. Commuter

Metro: 3.17 units, 8.4% waste, $11.41 GP/store/week. Campus: 3.30, 6.4%, $12.14. Commuter: 1.83, 16.4%, $6.00.

Accept Metro and Campus only. Commuter Hummus is stronger: 2.18 units, 8.7% waste, $7.16 GP/store/week.

Protein Snack Box

Pilot GP/store/week: Metro $15.61; Commuter $14.51; Campus $20.97; Highway $9.90; Rural $6.64. Waste stayed 2.6%–7.8%.

Use two facings except Rural, where one face preserves the five-day-code snack option without overbuilding low-volume space.

Sushi

Metro pilot: 3.15 units, 10.6% waste, $16.33 GP/store/week. Commuter and Campus waste was 32.5% and 26.1%.

One M-11 face only. Signed route/credit is the controlling restriction; pilot demand does not authorize expansion.

Rural Southwest Bowl

1.38 units, 19.3% waste, and $3.43 GP/tray/store/week versus Protein at 1.84 units, 7.8% waste, and $6.64.

Remove Bowl and keep Protein at one face. Empty capacity is preferable to a short-code, low-return facing.

Execution instructions for Space Planning and Field Operations

Build two Metro planograms: the base Metro planogram without Sushi, and an M-11-only overlay with one Sushi facing. Do not estimate M-11 volume beyond the signed route list.

Treat Campus as a full 10-slot planogram. Do not solve the final 0.0-slot balance with a partial facing or an added line item.

For Highway and Rural, keep one Hummus face as the required vegetarian solution, but do not add Caprese. These clusters have fewer than four delivery days and do not qualify for GreenFork shrink credit.

Remove Turkey Cranberry and Egg Salad from item files, planograms, and store-order instructions at launch. Do not rely on winter returns/billbacks.

Signed support to communicate, but not use as demand proof: Caprese has a $0.40 scanned-unit allowance July 13–August 9 (cap 5,500) and a 30% documented-waste credit only in 4+ delivery-day GreenFork stores; Protein has a $0.35 scanned-unit allowance for the first six reset weeks (cap 8,000) with no shrink credit; Sushi has 50% documented-waste credit through August 16 only in Metro M-11.

Release decision

Release the revised assortment and the Metro M-11 route overlay to Space Planning and Field Operations. Hold all rejected proposal actions for a later review only if new signed routing or internal post-launch performance changes the facts.

Source basis: merchant handoff dated June 10, 2026; signed vendor offer letters dated June 5–7, 2026; item master, capacity file, buyer proposal, and internal POS/inventory/waste records for April 6–May 25, 2026.

User prompt → 43 turns · 33 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’ll review the source files against the merchant handoff, then build a decision workbook and a concise merchant memo. I…

    I’ll review the source files against the merchant handoff, then build a decision workbook and a concise merchant memo. I’m using the Word and spreadsheet document skills because the requested outputs are .docx and .xlsx; if the attachments include PDFs, I’ll use the PDF workflow for those as well.

  7. 7Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({"cmd":"pwd && rg --files -g '!*output*' /workspace | sed -n '1,240p'","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":20000});
    text(r.output);
    

    Output

    Script completed
    Wall time 0.1 seconds
    Output:
    
    /workspace
    /workspace/data/weekly_pos_inventory_waste.csv
    /workspace/data/store_cluster_capacity.csv
    /workspace/data/signed_vendor_offer_letters.pdf
    /workspace/data/merchant_handoff_prepared_foods.docx
    /workspace/data/item_master_unit_economics.csv
    /workspace/data/buyer_reset_proposal.csv
    
  8. 8Shell1

    Tool execution only — no assistant text

    Shellvia exec41k chars

    Arguments

    const r = await tools.exec_command({"cmd":"for f in /root/.agents/skills/docx/SKILL.md /root/.agents/skills/xlsx/SKILL.md /root/.agents/skills/pdf/SKILL.md; do echo \"===== $f =====\"; cat \"$f\"; done","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":50000});
    text(r.output);
    

    Output

    Script completed
    Wall time 0.1 seconds
    Output:
    
    ===== /root/.agents/skills/docx/SKILL.md =====
    ---
    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."
    

    … 40,154 more characters of output in the raw trajectory.

  9. 9exec1

    Tool execution only — no assistant text

    execconst r = await tools.update_plan({explanation:"Review authoritative business rules and source data, reconcile the proposal, then produce and validate the requested memo and workbook.",plan:[{step:"Extract handoff, signed-offer, and internal-data inputs","status":"in_progress"},{step:"Determine revised item and cluster decisions with economics/capacity","status":"pending"},{step:"Create and validate the workbook and merchant memo","status":"pending"}]}); text(typeof r === "string" ? r : JSON.stringify(r));

    Arguments

    const r = await tools.update_plan({explanation:"Review authoritative business rules and source data, reconcile the proposal, then produce and validate the requested memo and workbook.",plan:[{step:"Extract handoff, signed-offer, and internal-data inputs","status":"in_progress"},{step:"Determine revised item and cluster decisions with economics/capacity","status":"pending"},{step:"Create and validate the workbook and merchant memo","status":"pending"}]});
    text(typeof r === "string" ? r : JSON.stringify(r));
    

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    
    {}
  10. 10Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({"cmd":"mkdir -p /tmp/grab_go_review && pandoc --track-changes=all /workspace/data/merchant_handoff_prepared_foods.docx -t plain -o /tmp/grab_go_review/merchant_handoff.txt && pdftotext -layout /workspace/data/signed_vendor_offer_letters.pdf /tmp/grab_go_review/signed_vendor_offer_letters.txt && for f in /tmp/grab_go_review/merchant_handoff.txt /tmp/grab_go_review/signed_vendor_offer_letters.txt /workspace/data/buyer_reset_proposal.csv /workspace/data/item_master_unit_economics.csv /workspace/data/store_cluster_capacity.csv /workspace/data/weekly

    … 195 more characters of arguments in the raw trajectory.

    Output

    Script completed
    Wall time 0.1 seconds
    Output:
    
    /bin/bash: line 1: pandoc: command not found
    
  11. 11The handoff is a Word file and the offer letters are a PDF, so I’m extracting their text directly and cross-checking it…

    The handoff is a Word file and the offer letters are a PDF, so I’m extracting their text directly and cross-checking it with the internal CSVs before making any assortment calls.

  12. 12Shell1

    Tool execution only — no assistant text

    Shellvia exec39k chars

    Arguments

    const r = await tools.exec_command({"cmd":"command -v pdftotext || true; command -v libreoffice || true; command -v python || true; python - <<'PY'\ntry:\n    import docx\n    print('python-docx available')\nexcept Exception as e:\n    print('python-docx unavailable:', e)\ntry:\n    import pypdf\n    print('pypdf available')\nexcept Exception as e:\n    print('pypdf unavailable:', e)\ntry:\n    import pdfplumber\n    print('pdfplumber available')\nexcept Exception as e:\n    print('pdfplumber unavailable:', e)\nPY\npython - <<'PY'\nfrom docx import Document\np='

    … 964 more characters of arguments in the raw trajectory.

    Output

    Script completed
    Wall time 1.2 seconds
    Output:
    
    /usr/bin/pdftotext
    /usr/bin/libreoffice
    /usr/local/bin/python
    python-docx available
    pypdf available
    pdfplumber available
    P1: Prepared Foods Reset Handoff
    P2: Blue Mesa Market - Q3 2026 refrigerated grab-and-go case
    P3: From: L. Moreno, Senior Merchant - Prepared Foods
    P4: To: Category Planning / Space Planning
    P5: Date: June 10, 2026
    P6: Context: The July reset has to protect lunch traffic while taking shrink dollars out of the case. The buyer proposal was assembled after vendor line reviews, but it has not been reconciled to current tray capacity, delivery cadence, or the signed trade terms. Stores are already flagging that the case is hard to recover after the noon rush, so the final call needs to be operationally boring even if the vendor story is exciting.
    P7: Decision rules for this reset
    P8: Fit the first four weeks of the July reset into the live re

    … 37,922 more characters of output in the raw trajectory.

  13. 13Shell1

    Tool execution only — no assistant text

    Shellvia exec6k chars

    Arguments

    const r = await tools.exec_command({"cmd":"python - <<'PY'\nimport pandas as pd\np='/workspace/data/weekly_pos_inventory_waste.csv'\ndf=pd.read_csv(p, parse_dates=['week_start'])\nprint('rows',len(df),'date range',df.week_start.min().date(),df.week_start.max().date())\nprint('\\nrange type counts')\nprint(df.groupby('range_type').agg(rows=('sku','size'),weeks=('week_start','nunique'),skus=('sku','nunique'),clusters=('cluster_code','nunique')).to_string())\nprint('\\nitems / cluster / range type')\nprint(df.groupby(['range_type','cluster_code','sku','item']).agg(weeks=(

    … 514 more characters of arguments in the raw trajectory.

    Output

    Script completed
    Wall time 1.6 seconds
    Output:
    
    rows 368 date range 2026-04-06 2026-05-25
    
    range type counts
                      rows  weeks  skus  clusters
    range_type                                   
    Controlled pilot    88      8     3         5
    Current set        280      8     7         5
    
    items / cluster / range type
                                                                      weeks  sales  waste  receipts  oos_days
    range_type       cluster_code sku      item                                                              
    Controlled pilot CAM          GGS-3RZA Caprese Ciabatta               8    132      9       153       1.7
                                  GGS-6BGH Protein Snack Box              8    224      8       248       9.4
                                  GGS-8XUY Spicy Tuna Sushi Roll          8     68     24       100       1.5
                     COM          GGS-3RZA Caprese Ciabatta       

    … 5,484 more characters of output in the raw trajectory.

  14. 14Shell1

    Tool execution only — no assistant text

    Shellvia exec11k chars

    Arguments

    const r = await tools.exec_command({"cmd":"python - <<'PY'\nimport pandas as pd\npd.set_option('display.max_rows', 200)\ndf=pd.read_csv('/workspace/data/weekly_pos_inventory_waste.csv')\nfor sku in ['GGS-3RZA','GGS-6BGH','GGS-8XUY']:\n    print('\\n', sku)\n    x=df[df.sku.eq(sku)].copy()\n    print(x[['week_start','cluster_code','stores_ranged','net_sales_units','waste_units','oos_store_days','receipts_units','ending_on_hand_units']].to_string(index=False))\nPY","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":30000});
    text(r.output);
    

    Output

    Script completed
    Wall time 0.7 seconds
    Output:
    
    
     GGS-3RZA
    week_start cluster_code  stores_ranged  net_sales_units  waste_units  oos_store_days  receipts_units  ending_on_hand_units
    2026-04-06          MET              9               25            2             0.6              25                    12
    2026-04-13          MET              9               30            3             0.1              37                    16
    2026-04-20          MET              9               29            2             0.3              28                    13
    2026-04-27          MET              9               29            2             0.6              33                    15
    2026-05-04          MET              9               27            3             0.8              31                    16
    2026-05-11          MET              9               30            3             0.5              30                    13
    

    … 10,445 more characters of output in the raw trajectory.

  15. 15Shell1

    Tool execution only — no assistant text

    Shellvia exec20k chars

    Arguments

    const r = await tools.exec_command({"cmd":"python - <<'PY'\nimport pandas as pd\npd.set_option('display.width',240)\np='/workspace/data/weekly_pos_inventory_waste.csv'; e='/workspace/data/item_master_unit_economics.csv'\nd=pd.read_csv(p); m=pd.read_csv(e)\nx=d.groupby(['cluster_code','cluster_name','sku','item','range_type','stores_ranged'], as_index=False).agg(weeks=('week_start','nunique'), sales=('net_sales_units','sum'), waste=('waste_units','sum'), receipts=('receipts_units','sum'), oos=('oos_store_days','sum'))\nx=x.merge(m[['sku','retail_price','unit_cost','tray_slots

    … 1,552 more characters of arguments in the raw trajectory.

    Output

    Script completed
    Wall time 0.8 seconds
    Output:
    
    cluster_code      sku                      item       range_type  stores_ranged sales_per_store_wk waste_pct_sold_plus_waste waste_pct_receipts gp_per_store_wk gp_per_tray_store_wk oos_days_per_store_wk  shelf_life_days  tray_slots_per_facing
             CAM GGS-6BGH         Protein Snack Box Controlled pilot              5              5.600                     0.034              0.032          20.972               20.972                 0.235                5                    1.0
             CAM GGS-3RZA          Caprese Ciabatta Controlled pilot              5              3.300                     0.064              0.059          12.140               12.140                 0.042                2                    1.0
             CAM GGS-8XUY     Spicy Tuna Sushi Roll Controlled pilot              4              2.125                     0.261              0.240      

    … 19,242 more characters of output in the raw trajectory.

  16. 16Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({"cmd":"node --version && npm --version && node -e \"try {require('docx'); console.log('docx module available')} catch(e) {console.log('docx module unavailable')}\" && find / -path '*scripts/recalc.py' -o -path '*scripts/office/validate.py' 2>/dev/null | sed -n '1,80p'","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":10000});
    text(r.output);
    

    Output

    Script completed
    Wall time 1.4 seconds
    Output:
    
    v22.23.2
    10.9.8
    docx module unavailable
    /root/.agents/skills/docx/scripts/office/validate.py
    /root/.agents/skills/xlsx/scripts/office/validate.py
    /root/.agents/skills/xlsx/scripts/recalc.py
    /harbor/skills/docx/scripts/office/validate.py
    /harbor/skills/xlsx/scripts/office/validate.py
    /harbor/skills/xlsx/scripts/recalc.py
    
  17. 17The key conflicts are now clear: the proposal is over physical capacity in Commuter, Campus, Highway, and Rural; it expa…

    The key conflicts are now clear: the proposal is over physical capacity in Commuter, Campus, Highway, and Rural; it expands sushi beyond its signed route; and it leaves Highway/Rural without a valid vegetarian choice once Caprese is ruled out. I’m reconciling those against the eight weeks of internal performance rather than supplier projections.

  18. 18Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({"cmd":"npm install --prefix /tmp/grab_go_review docx@9.5.1","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":20000});
    text(r.output);
    

    Output

    Script completed
    Wall time 2.1 seconds
    Output:
    
    
    added 22 packages in 2s
    
    1 package is looking for funding
      run `npm fund` for details
    
  19. 19exec1

    Tool execution only — no assistant text

    execconst patch = "*** Begin Patch\n*** Add File: create_reset_workbook.py\n+from pathlib import Path\n+\n+import pandas as pd\n+from openpyxl import Workbook\n+from openpyxl.comments import Comment\n+from openpyxl.formatting.rule import CellIsRule\n+from openpyxl.styles import Alignment, Border, Font, PatternFill, Side\n+from openpyxl.utils import get_column_letter\n+\n+\n+ROOT = Path('/workspace')\n+DATA = ROOT / 'data'\n+OUT = ROOT / 'output'\n+OUT.mkdir(exist_ok=True)\n+OUTFILE = OUT / 'reset_decision_workbook.xlsx'\n+\n+NAVY = '1F4E78'\n+BLUE = '2E75B6'\n+LIGHT_

    Arguments

    const patch = "*** Begin Patch\n*** Add File: create_reset_workbook.py\n+from pathlib import Path\n+\n+import pandas as pd\n+from openpyxl import Workbook\n+from openpyxl.comments import Comment\n+from openpyxl.formatting.rule import CellIsRule\n+from openpyxl.styles import Alignment, Border, Font, PatternFill, Side\n+from openpyxl.utils import get_column_letter\n+\n+\n+ROOT = Path('/workspace')\n+DATA = ROOT / 'data'\n+OUT = ROOT / 'output'\n+OUT.mkdir(exist_ok=True)\n+OUTFILE = OUT / 'reset_decision_workbook.xlsx'\n+\n+NAVY = '1F4E78'\n+BLUE = '2E75B6'\n+LIGHT_

    … 42,383 more characters of arguments in the raw trajectory.

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    
    {}
  20. 20Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    let{output,...rest}=await tools.exec_command({"cmd":"python /workspace/create_reset_workbook.py","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":20000});text(rest);text(output);
    

    Output

    Script completed
    Wall time 2.9 seconds
    Output:
    
    chunk_id: 0ede18
    wall_time_seconds: 2.729185408
    exit_code: 0
    original_token_count: 58
    /workspace/create_reset_workbook.py:539: DeprecationWarning: Call to deprecated function copy (Use copy(obj) or cell.obj = cell.obj + other).
      cell.font = cell.font.copy(name='Arial')
    /workspace/output/reset_decision_workbook.xlsx
    
  21. 21exec1

    Tool execution only — no assistant text

    execconst patch = "*** Begin Patch\n*** Update File: create_reset_workbook.py\n@@\n- ('Final planograms that fit capacity', '=COUNTIF(\\'Capacity Check\\'!$J$5:$J$10,\"FIT\")&\" of 6\"'),\n- ('Credible vegetarian coverage', '=COUNTIF(\\'Capacity Check\\'!$K$5:$K$10,\"PASS\")&\" of 6 planograms\"'),\n+ ('Final planograms that fit capacity', '=COUNTIF(\\'Capacity Check\\'!$J$4:$J$9,\"FIT\")&\" of 6\"'),\n+ ('Credible vegetarian coverage', '=COUNTIF(\\'Capacity Check\\'!$K$4:$K$9,\"PASS\")&\" of 6 planograms\

    Arguments

    const patch = "*** Begin Patch\n*** Update File: create_reset_workbook.py\n@@\n-        ('Final planograms that fit capacity', '=COUNTIF(\\'Capacity Check\\'!$J$5:$J$10,\"FIT\")&\" of 6\"'),\n-        ('Credible vegetarian coverage', '=COUNTIF(\\'Capacity Check\\'!$K$5:$K$10,\"PASS\")&\" of 6 planograms\"'),\n+        ('Final planograms that fit capacity', '=COUNTIF(\\'Capacity Check\\'!$J$4:$J$9,\"FIT\")&\" of 6\"'),\n+        ('Credible vegetarian coverage', '=COUNTIF(\\'Capacity Check\\'!$K$4:$K$9,\"PASS\")&\" of 6 planograms\

    … 126 more characters of arguments in the raw trajectory.

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    
    {}
  22. 22Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({"cmd":"python /workspace/create_reset_workbook.py && python /root/.agents/skills/xlsx/scripts/recalc.py /workspace/output/reset_decision_workbook.xlsx 90","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":30000});
    text(r.output);
    

    Output

    Script completed
    Wall time 6.4 seconds
    Output:
    
    /workspace/create_reset_workbook.py:539: DeprecationWarning: Call to deprecated function copy (Use copy(obj) or cell.obj = cell.obj + other).
      cell.font = cell.font.copy(name='Arial')
    /workspace/output/reset_decision_workbook.xlsx
    {
      "status": "success",
      "total_errors": 0,
      "error_summary": {},
      "total_formulas": 2015
    }
    
  23. 23Shell1

    Tool execution only — no assistant text

    Shellvia exec10k chars

    Arguments

    const r = await tools.exec_command({"cmd":"python - <<'PY'\nfrom openpyxl import load_workbook\np='/workspace/output/reset_decision_workbook.xlsx'\nwbv=load_workbook(p,data_only=True)\nfor wsname in ['Read Me','Capacity Check','Proposal Reconciliation']:\n    ws=wbv[wsname]\n    print('\\n===',wsname,'===')\n    for row in ws.iter_rows(min_row=1,max_row=min(ws.max_row,15),values_only=True):\n        print(row)\nprint('\\nFinal Hummus / Caprese / Protein / Sushi metric rows:')\nws=wbv['Final Decisions']\nfor row in ws.iter_rows(min_row=4,max_row=53,values_only=True):

    … 364 more characters of arguments in the raw trajectory.

    Output

    Script completed
    Wall time 0.7 seconds
    Output:
    
    
    === Read Me ===
    ('Blue Mesa Market | Refrigerated Grab-and-Go July Reset', None, None, None, None, None, None, None)
    ('First-four-week recommendation. Demand signal: internal POS, waste, and inventory records from Apr 6-May 25, 2026. Supplier projections are retained only as proposal context and are not used in the recommendation.', None, None, None, None, None, None, None)
    (None, None, None, None, None, None, None, None)
    ('Decision summary', None, None, None, None, None, None, None)
    ('Final decisions accepted', 36, None, None, None, None, None, None)
    ('Final decisions changed', 7, None, None, None, None, None, None)
    ('Proposed adds/keeps rejected', 7, None, None, None, None, None, None)
    ('Final planograms that fit capacity', '6 of 6', None, None, None, None, None, None)
    ('Credible vegetarian coverage', '6 of 6 planograms', None, None, None, None, None, None

    … 8,671 more characters of output in the raw trajectory.

  24. 24exec1

    Tool execution only — no assistant text

    execconst patch = "*** Begin Patch\n*** Add File: create_reset_memo.js\n+const fs = require('fs');\n+const {\n+ AlignmentType, BorderStyle, Document, Footer, Header, LevelFormat, PageNumber, Packer, Paragraph,\n+ ShadingType, Table, TableCell, TableRow, TextRun, VerticalAlign, WidthType\n+} = require('/tmp/grab_go_review/node_modules/docx');\n+\n+const out = '/workspace/output/grab_go_reset_memo.docx';\n+const NAVY = '1F4E78';\n+const BLUE = '2E75B6';\n+const LIGHT_BLUE = 'D9EAF7';\n+const LIGHT_GREEN = 'E2F0D9';\n+const LIGHT_YELLOW = 'FFF2CC';\n+const LIGHT_RED = 'FCE4

    Arguments

    const patch = "*** Begin Patch\n*** Add File: create_reset_memo.js\n+const fs = require('fs');\n+const {\n+  AlignmentType, BorderStyle, Document, Footer, Header, LevelFormat, PageNumber, Packer, Paragraph,\n+  ShadingType, Table, TableCell, TableRow, TextRun, VerticalAlign, WidthType\n+} = require('/tmp/grab_go_review/node_modules/docx');\n+\n+const out = '/workspace/output/grab_go_reset_memo.docx';\n+const NAVY = '1F4E78';\n+const BLUE = '2E75B6';\n+const LIGHT_BLUE = 'D9EAF7';\n+const LIGHT_GREEN = 'E2F0D9';\n+const LIGHT_YELLOW = 'FFF2CC';\n+const LIGHT_RED = 'FCE4

    … 14,171 more characters of arguments in the raw trajectory.

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    
    {}
  25. 25Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({"cmd":"rg -n \"\\\\n|\\\\t\" /workspace/create_reset_memo.js","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":20000});
    text(r.output);
    

    Output

    Script completed
    Wall time 0.1 seconds
    Output:
    
    
  26. 26Shell1

    Tool execution only — no assistant text

    Shellvia exec15k chars

    Arguments

    const r = await tools.exec_command({"cmd":"rg -n \"M-11:|\\\\\\\\t|\\\\\\\\n\" /workspace/create_reset_memo.js && sed -n '1,260p' /workspace/create_reset_memo.js","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":40000});
    text(r.output);
    

    Output

    Script completed
    Wall time 0.1 seconds
    Output:
    
    128:          run('\tPREPARED FOODS | RESET RELEASE RECOMMENDATION', { size: 15, color: GRAY }),
    134:          run('\tPage ', { size: 14, color: GRAY }),
    170:            ['Metro Core', 'Chicken Caesar 2; Turkey Club 1; Southwest Bowl 1; Hummus 1; Cobb 1; Caprese 1; Protein 2; Sushi 1 in M-11 only.', 'M-11: 11.5 / 12\nOther Metro: 10.0 / 12', 'Use a separate M-11 sushi overlay. Do not range Sushi in other Metro stores.'],
    const fs = require('fs');
    const {
      AlignmentType, BorderStyle, Document, Footer, Header, LevelFormat, PageNumber, Packer, Paragraph,
      ShadingType, Table, TableCell, TableRow, TextRun, VerticalAlign, WidthType
    } = require('/tmp/grab_go_review/node_modules/docx');
    
    const out = '/workspace/output/grab_go_reset_memo.docx';
    const NAVY = '1F4E78';
    const BLUE = '2E75B6';
    const LIGHT_BLUE = 'D9EAF7';
    const LIGHT_GREEN = 'E2F0D9';
    const LIGHT

    … 13,698 more characters of output in the raw trajectory.

  27. 27exec1

    Tool execution only — no assistant text

    execconst patch = "*** Begin Patch\n*** Update File: create_reset_memo.js\n@@\n headers: {\n default: new Header({ children: [rich([\n run('BLUE MESA MARKET', { size: 16, bold: true, color: NAVY }),\n- run('\\tPREPARED FOODS | RESET RELEASE RECOMMENDATION', { size: 15, color: GRAY }),\n+ run(' | PREPARED FOODS | RESET RELEASE RECOMMENDATION', { size: 15, color: GRAY }),\n@@\n default: new Footer({ children: [rich([\n run('Internal planning use only', { size: 14, color: GRAY }),\n- run('\\tPage ', { siz

    Arguments

    const patch = "*** Begin Patch\n*** Update File: create_reset_memo.js\n@@\n       headers: {\n         default: new Header({ children: [rich([\n           run('BLUE MESA MARKET', { size: 16, bold: true, color: NAVY }),\n-          run('\\tPREPARED FOODS | RESET RELEASE RECOMMENDATION', { size: 15, color: GRAY }),\n+          run('  |  PREPARED FOODS | RESET RELEASE RECOMMENDATION', { size: 15, color: GRAY }),\n@@\n         default: new Footer({ children: [rich([\n           run('Internal planning use only', { size: 14, color: GRAY }),\n-          run('\\tPage ', { siz

    … 751 more characters of arguments in the raw trajectory.

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    
    {}
  28. 28exec1

    Tool execution only — no assistant text

    execconst patch = "*** Begin Patch\n*** Update File: create_reset_memo.js\n@@\n return new Paragraph({\n spacing: { before: opts.before ?? 220, after: opts.after ?? 100, line: 276 },\n keepNext: true,\n+ pageBreakBefore: opts.pageBreakBefore || false,\n border: level === 1 ? { bottom: { style: BorderStyle.SINGLE, size: 6, color: BLUE, space: 1 } } : undefined,\n*** End Patch"; const r = await tools.apply_patch(patch); text(typeof r === "string" ? r : JSON.stringify(r));

    Arguments

    const patch = "*** Begin Patch\n*** Update File: create_reset_memo.js\n@@\n   return new Paragraph({\n     spacing: { before: opts.before ?? 220, after: opts.after ?? 100, line: 276 },\n     keepNext: true,\n+    pageBreakBefore: opts.pageBreakBefore || false,\n     border: level === 1 ? { bottom: { style: BorderStyle.SINGLE, size: 6, color: BLUE, space: 1 } } : undefined,\n*** End Patch";
    const r = await tools.apply_patch(patch);
    text(typeof r === "string" ? r : JSON.stringify(r));
    

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    
    {}
  29. 29The revised model now fits all six release planograms. I’m producing the merchant memo with the same capacity math and s…

    The revised model now fits all six release planograms. I’m producing the merchant memo with the same capacity math and signed-route controls, then validating both deliverables for formula and document integrity.

  30. 30Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({"cmd":"node /workspace/create_reset_memo.js && python /root/.agents/skills/docx/scripts/office/validate.py /workspace/output/grab_go_reset_memo.docx","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":30000});
    text(r.output);
    

    Output

    Script completed
    Wall time 1.6 seconds
    Output:
    
    /workspace/output/grab_go_reset_memo.docx
    
    Paragraphs: 0 → 84 (+84)
    All validations PASSED!
    
  31. 31Shell1

    Tool execution only — no assistant text

    Shellvia exec13k chars

    Arguments

    const r = await tools.exec_command({"cmd":"ls -l /root/.agents/skills/docx/scripts/office /root/.agents/skills/xlsx/scripts/office && mkdir -p /tmp/grab_go_review/rendered && python /root/.agents/skills/docx/scripts/office/soffice.py --headless --convert-to pdf --outdir /tmp/grab_go_review/rendered /workspace/output/grab_go_reset_memo.docx && pdfinfo /tmp/grab_go_review/rendered/grab_go_reset_memo.pdf | sed -n '1,24p' && pdftotext -layout /tmp/grab_go_review/rendered/grab_go_reset_memo.pdf - | sed -n '1,260p'","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens

    … 32 more characters of arguments in the raw trajectory.

    Output

    Script completed
    Wall time 1.0 seconds
    Output:
    
    /root/.agents/skills/docx/scripts/office:
    total 36
    drwxr-xr-x 2 root root 4096 Aug 20 01:14 helpers
    -rwxr-xr-x 1 root root 4991 Aug 20 01:14 pack.py
    drwxr-xr-x 6 root root 4096 Aug 20 01:14 schemas
    -rw-r--r-- 1 root root 5301 Aug 20 01:14 soffice.py
    -rwxr-xr-x 1 root root 4052 Aug 20 01:14 unpack.py
    -rwxr-xr-x 1 root root 3668 Aug 20 01:14 validate.py
    drwxr-xr-x 3 root root 4096 Aug 20 01:22 validators
    
    /root/.agents/skills/xlsx/scripts/office:
    total 40
    drwxr-xr-x 2 root root 4096 Aug 20 01:21 __pycache__
    drwxr-xr-x 2 root root 4096 Aug 20 01:14 helpers
    -rwxr-xr-x 1 root root 4991 Aug 20 01:14 pack.py
    drwxr-xr-x 6 root root 4096 Aug 20 01:14 schemas
    -rw-r--r-- 1 root root 5301 Aug 20 01:14 soffice.py
    -rwxr-xr-x 1 root root 4052 Aug 20 01:14 unpack.py
    -rwxr-xr-x 1 root root 3668 Aug 20 01:14 validate.py
    drwxr-xr-x 2 root root 4096 Aug 20 01:14 validat

    … 11,993 more characters of output in the raw trajectory.

  32. 32Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({"cmd":"pdftoppm -png -r 130 -f 1 -l 3 /tmp/grab_go_review/rendered/grab_go_reset_memo.pdf /tmp/grab_go_review/rendered/memo && ls -lh /tmp/grab_go_review/rendered/memo-*.png","workdir":"/workspace","yield_time_ms":30000,"max_output_tokens":10000});
    text(r.output);
    

    Output

    Script completed
    Wall time 1.1 seconds
    Output:
    
    -rw-r--r-- 1 root root 271K Aug 20 01:22 /tmp/grab_go_review/rendered/memo-1.png
    -rw-r--r-- 1 root root 339K Aug 20 01:22 /tmp/grab_go_review/rendered/memo-2.png
    -rw-r--r-- 1 root root 146K Aug 20 01:22 /tmp/grab_go_review/rendered/memo-3.png
    
  33. 33exec1

    Tool execution only — no assistant text

    execconst r = await tools.view_image({"path":"/tmp/grab_go_review/rendered/memo-2.png","detail":"high"}); image(r.image_url);463k chars

    Arguments

    const r = await tools.view_image({"path":"/tmp/grab_go_review/rendered/memo-2.png","detail":"high"});
    image(r.image_url);
    

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    

    … 461,620 more characters of output in the raw trajectory.

  34. 34exec1

    Tool execution only — no assistant text

    execconst r = await tools.view_image({"path":"/tmp/grab_go_review/rendered/memo-1.png","detail":"high"}); image(r.image_url);370k chars

    Arguments

    const r = await tools.view_image({"path":"/tmp/grab_go_review/rendered/memo-1.png","detail":"high"});
    image(r.image_url);
    

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    

    … 369,000 more characters of output in the raw trajectory.

  35. 35exec1

    Tool execution only — no assistant text

    execconst r = await tools.view_image({"path":"/tmp/grab_go_review/rendered/memo-3.png","detail":"high"}); image(r.image_url);199k chars

    Arguments

    const r = await tools.view_image({"path":"/tmp/grab_go_review/rendered/memo-3.png","detail":"high"});
    image(r.image_url);
    

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    

    … 197,528 more characters of output in the raw trajectory.

  36. 36exec1

    Tool execution only — no assistant text

    execconst patch = "*** Begin Patch\n*** Update File: create_reset_memo.js\n@@\n- heading('Execution instructions for Space Planning and Field Operations', 1),\n+ heading('Execution instructions for Space Planning and Field Operations', 1, { pageBreakBefore: true }),\n*** End Patch"; const r = await tools.apply_patch(patch); text(typeof r === "string" ? r : JSON.stringify(r));

    Arguments

    const patch = "*** Begin Patch\n*** Update File: create_reset_memo.js\n@@\n-        heading('Execution instructions for Space Planning and Field Operations', 1),\n+        heading('Execution instructions for Space Planning and Field Operations', 1, { pageBreakBefore: true }),\n*** End Patch";
    const r = await tools.apply_patch(patch);
    text(typeof r === "string" ? r : JSON.stringify(r));
    

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    
    {}
  37. 37Shell1

    Tool execution only — no assistant text

    Shellvia exec2k chars

    Arguments

    const r = await tools.exec_command({"cmd":"node /workspace/create_reset_memo.js && python /root/.agents/skills/docx/scripts/office/validate.py /workspace/output/grab_go_reset_memo.docx && rm -f /tmp/grab_go_review/rendered/grab_go_reset_memo.pdf /tmp/grab_go_review/rendered/memo-*.png && python /root/.agents/skills/docx/scripts/office/soffice.py --headless --convert-to pdf --outdir /tmp/grab_go_review/rendered /workspace/output/grab_go_reset_memo.docx && pdftoppm -png -r 130 -f 3 -l 3 /tmp/grab_go_review/rendered/grab_go_reset_memo.pdf /tmp/grab_go_review/rendered/memo && pdfinfo

    … 169 more characters of arguments in the raw trajectory.

    Output

    Script failed
    Wall time 0.0 seconds
    Output:
    
    Script error:
    exec_command failed for `/bin/bash -lc "node /workspace/create_reset_memo.js && python /root/.agents/skills/docx/scripts/office/validate.py /workspace/output/grab_go_reset_memo.docx && rm -f /tmp/grab_go_review/rendered/grab_go_reset_memo.pdf /tmp/grab_go_review/rendered/memo-*.png && python /root/.agents/skills/docx/scripts/office/soffice.py --headless --convert-to pdf --outdir /tmp/grab_go_review/rendered /workspace/output/grab_go_reset_memo.docx && pdftoppm -png -r 130 -f 3 -l 3 /tmp/grab_go_review/rendered/grab_go_reset_memo.pdf /tmp/grab_go_review/rendered/memo && pdfinfo /tmp/grab_go_review/rendered/grab_go_reset_memo.pdf | rg 'Pages'"`: CreateProcess { message: "Rejected(\"`/bin/bash -lc \\\"node /workspace/create_reset_memo.js && python /root/.agents/skills/docx/scripts/office/validate.py /workspace/output/grab_go_reset_memo.docx && rm -f /tmp

    … 544 more characters of output in the raw trajectory.

  38. 38Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({"cmd":"node /workspace/create_reset_memo.js\npython /root/.agents/skills/docx/scripts/office/validate.py /workspace/output/grab_go_reset_memo.docx\nTASK_RENDER_DIR=$(mktemp -d /tmp/grab_go_render.XXXXXX)\npython /root/.agents/skills/docx/scripts/office/soffice.py --headless --convert-to pdf --outdir \"$TASK_RENDER_DIR\" /workspace/output/grab_go_reset_memo.docx\npdftoppm -png -r 130 -f 3 -l 3 \"$TASK_RENDER_DIR/grab_go_reset_memo.pdf\" \"$TASK_RENDER_DIR/memo\"\npdfinfo \"$TASK_RENDER_DIR/grab_go_reset_memo.pdf\" | rg 'Pages

    … 150 more characters of arguments in the raw trajectory.

    Output

    Script completed
    Wall time 2.7 seconds
    Output:
    
    /workspace/output/grab_go_reset_memo.docx
    
    Paragraphs: 0 → 84 (+84)
    All validations PASSED!
    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_render.bTnQU0/grab_go_reset_memo.pdf using filter : writer_pdf_Export
    Pages:           3
    /tmp/grab_go_render.bTnQU0
    
  39. 39exec1

    Tool execution only — no assistant text

    execconst r = await tools.view_image({"path":"/tmp/grab_go_render.bTnQU0/memo-3.png","detail":"high"}); image(r.image_url);256k chars

    Arguments

    const r = await tools.view_image({"path":"/tmp/grab_go_render.bTnQU0/memo-3.png","detail":"high"});
    image(r.image_url);
    

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    

    … 255,228 more characters of output in the raw trajectory.

  40. 40Shell1

    Tool execution only — no assistant text

    Shellvia exec

    Arguments

    const r = await tools.exec_command({"cmd":"find /workspace/output -maxdepth 1 -type f -printf '%f %s bytes\\n' | sort && python - <<'PY'\nfrom openpyxl import load_workbook\np='/workspace/output/reset_decision_workbook.xlsx'\nwb=load_workbook(p, data_only=False)\nprint('Workbook sheets:', ', '.join(wb.sheetnames))\nprint('Formula cells:', sum(1 for ws in wb.worksheets for row in ws.iter_rows() for c in row if isinstance(c.value,str) and c.value.startswith('=')))\nPY","workdir":"/workspace","yield_time_ms":10000,"max_output_tokens":20000});
    text(r.output);
    

    Output

    Script completed
    Wall time 0.7 seconds
    Output:
    
    grab_go_reset_memo.docx 14593 bytes
    reset_decision_workbook.xlsx 86898 bytes
    Workbook sheets: Read Me, POS Data, Item Master, Proposal, Cluster Capacity, Signed Terms, Final Decisions, Item Economics, Capacity Check, Proposal Reconciliation, Source Hierarchy
    Formula cells: 2015
    
  41. 41exec1

    Tool execution only — no assistant text

    execconst patch = "*** Begin Patch\n*** Delete File: create_reset_workbook.py\n*** Delete File: create_reset_memo.js\n*** End Patch"; const r = await tools.apply_patch(patch); text(typeof r === "string" ? r : JSON.stringify(r));

    Arguments

    const patch = "*** Begin Patch\n*** Delete File: create_reset_workbook.py\n*** Delete File: create_reset_memo.js\n*** End Patch";
    const r = await tools.apply_patch(patch);
    text(typeof r === "string" ? r : JSON.stringify(r));
    

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    
    {}
  42. 42exec1

    Tool execution only — no assistant text

    execconst r = await tools.update_plan({explanation:"Authoritative source conflicts were reconciled, and both requested deliverables were created and validated.",plan:[{step:"Extract handoff, signed-offer, and internal-data inputs","status":"completed"},{step:"Determine revised item and cluster decisions with economics/capacity","status":"completed"},{step:"Create and validate the workbook and merchant memo","status":"completed"}]}); text(typeof r === "string" ? r : JSON.stringify(r));

    Arguments

    const r = await tools.update_plan({explanation:"Authoritative source conflicts were reconciled, and both requested deliverables were created and validated.",plan:[{step:"Extract handoff, signed-offer, and internal-data inputs","status":"completed"},{step:"Determine revised item and cluster decisions with economics/capacity","status":"completed"},{step:"Create and validate the workbook and merchant memo","status":"completed"}]});
    text(typeof r === "string" ? r : JSON.stringify(r));
    

    Output

    Script completed
    Wall time 0.0 seconds
    Output:
    
    {}
  43. 43Completed the revised first-four-week reset recommendation. - [Merchant memo](/workspace/output/grab_go_reset_memo.docx)…

    Completed the revised first-four-week reset recommendation.

    • Merchant memo
    • Supporting decision workbook

    The final plan fits all six planograms, restricts Sushi to one Metro M-11 facing, retains valid vegetarian coverage, and removes the seasonal/route/capacity conflicts. Workbook formulas were recalculated with zero errors.

4 failure modes across 6 verifier failures

  1. 1Allocation or Selection Plan IncorrectView on Failure Modes ↗Reasoning and Computation2 failures

    Description

    After eligibility is established, does the artifact assign a scarce resource, facing, shelf position, assortment item, or appointment slot to the wrong recipient or produce the wrong required final set?

    Failure evidence · per affected verifier

    • The memo's cluster-level final facings and slot totals consistently differ from the required exact values for Metro, Highway, and Rural North.

    • The workbook's final facing counts for Chicken Caesar Wrap, Southwest Chicken Bowl, and the other graded SKUs consistently differ from the required per-cluster values.

  2. 2Quantity, Cost, Capacity, or Rate Calculation WrongView on Failure Modes ↗Reasoning and Computation2 failures

    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 memo correctly argues for leaving some capacity open rather than force-filling weak items, but the specific Highway and Rural North open-slot numbers do not match the required 7.5/8.0 and 6.0/7.0 values.

    • 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.

  4. 4Required Numeric Summary Missing or InconsistentView on Failure Modes ↗Presentation and Communication1 failure

    Description

    Are the detailed rows available and substantially correct while the memo or executive summary omits required counts, capacities, overages, unused amounts, totals, or states a value inconsistent with those rows?

    Failure evidence · per affected verifier

    • The memo states only a general or partial capacity picture and never lays out all four buyer-proposal cluster overages with their exact numbers.