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propose-hypotheses

Execute complete FPF cycle from hypothesis generation to decision

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설치 방법 보기

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  • SKILL.md5.8 KB

SKILL.md(원문)

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Propose Hypotheses Workflow

Execute the First Principles Framework (FPF) cycle: generate competing hypotheses, verify logic, validate evidence, audit trust, and produce a decision.

User Input

Problem Statement: $ARGUMENTS

Workflow Execution

Step 1a: Create Directory Structure (Main Agent)

Create .fpf/ directory structure if it does not exist:

mkdir -p .fpf/{evidence,decisions,sessions,knowledge/{L0,L1,L2,invalid}}
touch .fpf/{evidence,decisions,sessions,knowledge/{L0,L1,L2,invalid}}/.gitkeep

Postcondition: .fpf/ directory scaffold exists.


Step 1b: Initialize Context (FPF Agent)

Launch fpf-agent with sonnet[1m] model:

  • Description: "Initialize FPF context"
  • Prompt:
    Read ${CLAUDE_PLUGIN_ROOT}/tasks/init-context.md and execute.
    
    Problem Statement: $ARGUMENTS
    
    **Write**: Context summary to `.fpf/context.md`**
    

Step 2: Generate Hypotheses (FPF Agent)

Launch fpf-agent with sonnet[1m] model:

  • Description: "Generate L0 hypotheses"
  • Prompt:
    Read ${CLAUDE_PLUGIN_ROOT}/tasks/generate-hypotheses.md and execute.
    
    Problem Statement: $ARGUMENTS
    Context: <summary from Step 1b>
    
    **Write**: List of hypothesis IDs and titles to `.fpf/knowledge/L0/`
    
    Reply with summary table in markdown format:
    
      | ID | Title | Kind | Scope |
      |----|-------|------|-------|
      | ... | ... | ... | ... |
    

Step 3: Present Summary (Main Agent)

  1. Read all L0 hypothesis files from .fpf/knowledge/L0/
  2. Present summary table from agent response.
  3. Ask user: "Would you like to add any hypotheses of your own? (yes/no)"

Step 4: Add User Hypothesis (FPF Agent, Conditional Loop)

Condition: User says yes to adding hypotheses.

Launch fpf-agent with sonnet[1m] model:

  • Description: "Add user hypothesis"
  • Prompt:
    Read ${CLAUDE_PLUGIN_ROOT}/tasks/add-user-hypothesis.md and execute.
    
    User Hypothesis Description: <get from user>
    
    **Write**: User hypothesis to `.fpf/knowledge/L0/`
    

Loop: Return to Step 3 after hypothesis is added.

Exit: When user says no or declines to add more.


Step 5: Verify Logic (Parallel Sub-Agents)

Condition: User finished adding hypotheses.

For EACH L0 hypothesis file in .fpf/knowledge/L0/, launch parallel fpf-agent with sonnet[1m] model:

  • Description: "Verify hypothesis: <hypothesis-id>"
  • Prompt:
    Read ${CLAUDE_PLUGIN_ROOT}/tasks/verify-logic.md and execute.
    
    Hypothesis ID: <hypothesis-id>
    Hypothesis File: .fpf/knowledge/L0/<hypothesis-id>.md
    
    **Move**: After you complete verification, move the file to `.fpf/knowledge/L1/` or `.fpf/knowledge/invalid/`.
    

Wait for all agents, then check that files are moved to .fpf/knowledge/L1/ or .fpf/knowledge/invalid/.


Step 6: Validate Evidence (Parallel Sub-Agents)

For EACH L1 hypothesis file in .fpf/knowledge/L1/, launch parallel fpf-agent with sonnet[1m] model:

  • Description: "Validate hypothesis: <hypothesis-id>"
  • Prompt:
    Read ${CLAUDE_PLUGIN_ROOT}/tasks/validate-evidence.md and execute.
    
    Hypothesis ID: <hypothesis-id>
    Hypothesis File: .fpf/knowledge/L1/<hypothesis-id>.md
    
    **Move**: After you complete validation, move the file to `.fpf/knowledge/L2/` or `.fpf/knowledge/invalid/`.
    

Wait for all agents, then check that files are moved to .fpf/knowledge/L2/ or .fpf/knowledge/invalid/.


Step 7: Audit Trust (Parallel Sub-Agents)

For EACH L2 hypothesis file in .fpf/knowledge/L2/, launch parallel fpf-agent with sonnet[1m] model:

  • Description: "Audit trust: <hypothesis-id>"
  • Prompt:
    Read ${CLAUDE_PLUGIN_ROOT}/tasks/audit-trust.md and execute.
    
    Hypothesis ID: <hypothesis-id>
    Hypothesis File: .fpf/knowledge/L2/<hypothesis-id>.md
    
    **Write**: Audit report to `.fpf/evidence/audit-{hypothesis-id}-{YYYY-MM-DD}.md`
    
    **Reply**: with R_eff score and weakest link
    

Wait for all agents, then check that audit reports are created in .fpf/evidence/.


Step 8: Make Decision (FPF Agent)

Launch fpf-agent with sonnet[1m] model:

  • Description: "Create decision record"
  • Prompt:
    Read ${CLAUDE_PLUGIN_ROOT}/tasks/decide.md and execute.
    
    Problem Statement: $ARGUMENTS
    L2 Hypotheses Directory: .fpf/knowledge/L2/
    Audit Reports: .fpf/evidence/
    
    **Write**: Decision record to `.fpf/decisions/`
    
    **Reply**: with decision record summary in markdown format:
    
    | Hypothesis | R_eff | Weakest Link | Status |
    |------------|-------|--------------|--------|
    | ... | ... | ... | ... |
    
    **Recommended Decision**: <hypothesis title>
    
    **Rationale**: <brief explanation>
    

Wait for agent, then check that decision record is created in .fpf/decisions/.

Step 9: Present Final Summary (Main Agent)

  1. Read the DRR from .fpf/decisions/
  2. Present results from agent response.
  3. Present next steps:
    • Implement the selected hypothesis
    • Use /fpf:status to check FPF state
    • Use /fpf:actualize if codebase changes
  4. Ask user if he agree with the decision, if not launch fpf-agent at step 8 with instruction to modify the decision as user wants.

Completion

Workflow complete when:

  • .fpf/ directory structure exists
  • Context recorded in .fpf/context.md
  • Hypotheses generated, verified, validated, and audited
  • DRR created in .fpf/decisions/
  • Final summary presented to user

Artifacts Created:

  • .fpf/context.md - Problem context
  • .fpf/knowledge/L0/*.md - Initial hypotheses
  • .fpf/knowledge/L1/*.md - Verified hypotheses
  • .fpf/knowledge/L2/*.md - Validated hypotheses
  • .fpf/knowledge/invalid/*.md - Rejected hypotheses
  • .fpf/evidence/*.md - Evidence files
  • .fpf/decisions/*.md - Design Rationale Record

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