Skills

Work Operating Model

Conversation-first workflow for turning tacit work patterns into a structured operating...

Install

npx skills add NateBJones-Projects/OB1 --skill work-operating-model -g -a claude-code -y
Category
AI and agents
Updated
3d ago
License
See repository
Context cost
Mediumabout 2,050 tokens
Runs scripts
No, instructions only

What it does

Conversation-first workflow for turning tacit work patterns into a structured operating model. Use when the user wants to map how their work actually runs, generate USER.md / SOUL.md / HEARTBEAT.md artifacts, or build an agent-ready model of rhythms, recurring decisions, dependencies, institutional knowledge, and friction. Requires base Open Brain search/capture tools plus the paired Work Operating Model recipe MCP tools.

Work Operating Model

Purpose

The first job is not to automate the user. It is to help them see and describe how their work actually runs.

Your job is to:

  1. interview the user through five fixed layers
  2. convert the approved results into canonical structured entries
  3. save each layer only after explicit confirmation
  4. capture one concise summary thought per approved layer in the core Open Brain
  5. run a contradiction pass
  6. generate the final exports

Required Tools

Before doing anything else, identify the actual tool names available in the current environment for:

  • the base Open Brain search tool, usually search_thoughts
  • the base Open Brain capture tool, usually capture_thought
  • start_operating_model_session
  • save_operating_model_layer
  • query_operating_model
  • generate_operating_model_exports

If any of the recipe tools are missing, stop and say so clearly. If the base search/capture tools are missing, stop and say so clearly.

Do not assume the exact tool prefix. Use the names exposed in the current client.

Non-Negotiable Rules

  1. Use this fixed layer order:

    • operating rhythms
    • recurring decisions
    • dependencies
    • institutional knowledge
    • friction
  2. Start concrete, not abstract.

    • Ask about last week, last month, recent examples, recent misses, recent waits.
    • Do not open with “what do you do all day?”
  3. Search results are hints, not facts.

    • You may use the base search tool before a layer starts.
    • Treat everything retrieved as tentative context.
    • Never persist a retrieved hint unless the user confirms it or you reframe it as a synthesized pattern they approve.
  4. Save only after explicit confirmation.

    • Show a checkpoint summary first.
    • Ask for confirmation or corrections.
    • Only then call save_operating_model_layer.
Read the whole SKILL.md on GitHub

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