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Kitchen commander

Skill cloudaipro/openclaw-agent-skills/skills/kitchen-commander

Inventory-first solo cooking operator for selecting dishes, generating SOP recipes, and enforcing kitchen safety constraints from available ingredients and equipment. Use when users ask for meal recommendations, recipe steps, pantry optimization, or device-safe cooking workflows.From its SKILL.md

Install
npx -y skills add cloudaipro/openclaw-agent-skills --skill kitchen-commander

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
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SKILL.md

1.9 KB, 332 tokens by cl100k_base, as published. Nobody here has run it

Kitchen Commander

Objective

Produce practical and safe one-person cooking plans that maximize taste while reducing food waste.

Trigger Rules

Use when the request includes inventory-aware meal planning or recipe execution.

Positive cues:

  • "Use what I have in the fridge."
  • "Recommend dinner with these ingredients."
  • "Give me exact SOP with timing."

Do not use when:

  • User requests medical nutrition diagnosis.
  • User asks for unsafe chemical or equipment misuse.
  • User needs restaurant recommendations instead of cooking execution.

Inputs

Required:

  • Available ingredients or pantry list.
  • Available equipment.

Optional:

  • Servings.
  • Time limit.
  • Dietary constraints.

Output Schema

Return universal envelope from ../shared/references/output-schemas.md.

Artifacts order:

  1. Dish decision brief.
  2. Ingredient usage table.
  3. SOP execution plan.
  4. Safety and cleanup checklist.

Workflow

  1. Parse inventory and equipment.
  2. Choose dish strategy using high-depletion ingredients first.
  3. Build clear prep/cook/finish SOP with time markers.
  4. Add substitutions and failure recovery notes.
  5. Add equipment safety notes before serving steps.

Quality Bar

  • Recipe must be executable with listed equipment.
  • Ingredient usage must be explicit.
  • Safety constraints must be visible and actionable.

Safety Rules

  • Refuse unsafe instructions.
  • Flag allergy/conflict risks when uncertain.
  • Avoid overclaiming nutrition or medical impact.

Resources

  • Domain framework: references/domain.md
  • Envelope validator: scripts/validate_output.py
  • Operations artifact validator: scripts/validate_operations_artifacts.py

What ships with it: 7 files

9.4 KB alongside SKILL.md, 3 of them executable

agents/

references/

scripts/

src/

Gives 0 of the 12 instructions most operations skills give in 332 tokens

Counted across 483 of the 484 authors here whose files we hold, read 2026-08-07

  • Collect monitoring data throughout the simulationin 14 of 483, across 6 files
  • Set the random seed for reproducibilityin 14 of 483, across 6 files
  • Validate simulations against analytical solutionsin 12 of 483, across 4 files
  • Clarify goals, constraints, and inputsin 11 of 483, across 2 files
  • Implement contract tests for integration pointsin 11 of 483, across 2 files
  • Implement strangler fig infrastructure with API gatewayin 11 of 483, across 2 files
  • Audit modernized components for security vulnerabilitiesin 11 of 483, across 2 files
  • Avoid Python blocking calls in processesin 10 of 483, across 3 files
  • Use resource context managers for automatic cleanupin 9 of 483, across 2 files
  • Maintain consistent time unitsin 9 of 483, across 2 files
  • Validate outcomes against success criteriain 8 of 483, across 1 file
  • Analyze the legacy codebase for technical debtin 8 of 483, across 1 file

Said here and by no other author read

  • Parse inventory and equipment
  • Prioritize high-depletion ingredients
  • Build timed prep cook finish SOP
  • Add substitution and recovery notes
  • Add equipment safety notes before serving
  • Make recipe executable with listed equipment

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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