fpf:propose-hypotheses

fpf:propose-hypotheses — an installable skill for AI agents, published by neolabhq/context-engineering-kit.

INSTALLATION
npx skills add https://github.com/neolabhq/context-engineering-kit --skill fpf:propose-hypotheses
Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

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)

  • Read all L0 hypothesis files from .fpf/knowledge/L0/
  • Present summary table from agent response.
  • 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: "
  • 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: "
  • 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: "
  • 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)

  • Read the DRR from .fpf/decisions/
  • Present results from agent response.
  • Present next steps:
  • Implement the selected hypothesis
  • Use /fpf:status to check FPF state
  • Use /fpf:actualize if codebase changes
  • 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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