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/propose-hypotheses

Execute complete FPF cycle from hypothesis generation to decision

From plugin
context-engineering-kit
1.8k68 skills21 agents1 command

Claude Code

$ npx -y skills add NeoLabHQ/context-engineering-kit --skill propose-hypotheses --agent claude-code

SKILL.md

propose-hypotheses.SKILL.md
name: propose-hypotheses
description: Execute complete FPF cycle from hypothesis generation to decision

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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A hand-crafted collection of advanced context engineering techniques and patterns with minimal token footprint, focused on improving agent result quality and predictability.

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propose-hypotheses installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.