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Skills/neolabhq/context-engineering-kit/propose-hypotheses
propose-hypotheses logo

propose-hypotheses

neolabhq/context-engineering-kit
568 installs1K stars
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Installation

npx skills add https://github.com/neolabhq/context-engineering-kit --skill propose-hypotheses

Summary

Execute complete FPF cycle from hypothesis generation to decision

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)

  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
  1. 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

Score

0–100
65/ 100

Grade

C

Popularity17/30

568 installs — growing adoption. Source repo has 1,103 GitHub stars.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Propose Hypotheses skill score badge previewScore badge

Markdown

[![Propose Hypotheses skill](https://www.remoteopenclaw.com/skills/neolabhq/context-engineering-kit/propose-hypotheses/badges/score.svg)](https://www.remoteopenclaw.com/skills/neolabhq/context-engineering-kit/propose-hypotheses)

HTML

<a href="https://www.remoteopenclaw.com/skills/neolabhq/context-engineering-kit/propose-hypotheses"><img src="https://www.remoteopenclaw.com/skills/neolabhq/context-engineering-kit/propose-hypotheses/badges/score.svg" alt="Propose Hypotheses skill"/></a>

Propose Hypotheses FAQ

How do I install the Propose Hypotheses skill?

Run “npx skills add https://github.com/neolabhq/context-engineering-kit --skill propose-hypotheses” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Propose Hypotheses skill do?

Execute complete FPF cycle from hypothesis generation to decision The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Propose Hypotheses skill free?

Yes. Propose Hypotheses is a free, open-source skill published from neolabhq/context-engineering-kit. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Propose Hypotheses work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Propose Hypotheses works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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