openclaw/autoresearch-pro

autoresearch-pro

Overview

Automatically improve any OpenClaw skill, prompt, or article through iterative mutation-testing: small edits → run test cases → score with checklist → keep improvements, discard regressions.

Inspired by Karpathy/autoresearch.

Supports three optimization modes:

| Mode | Input | Output | |------|-------|--------| | Skill | Path to a skill directory | Improved SKILL.md | | Prompt | A prompt text string | Improved prompt | | Article | An article/document text | Improved article |

---

Workflow

Step 1 — Identify Mode and Input

Ask the user to confirm:

• Mode 1 — Skill: User says "optimize [skill-name]" or provides a skill path
• Mode 2 — Prompt: User says "optimize this prompt" or pastes a prompt
• Mode 3 — Article: User says "improve this article" or pastes article text

For Skill mode, resolve the skill path to ~/.openclaw/skills/<skill-name>/SKILL.md. For Prompt/Article mode, keep the text in context (do not write to disk unless needed).

Step 2 — Generate Checklist (10 Questions)

Read the target content first. Then generate 10 diverse, specific yes/no checklist questions relevant to the content type:

For Skill mode (same as before):

| # | Dimension | What to Check | |---|----------|---------------| | 1 | Description clarity | Is the frontmatter description precise and actionable? | | 2 | Trigger coverage | Does it cover the main real-world use cases? | | 3 | Workflow structure | Are steps clearly sequenced and unambiguous? | | 4 | Error guidance | Does it handle error states and edge cases? | | 5 | Tool usage accuracy | Are tool names and parameters correct for OpenClaw? | | 6 | Example quality | Do examples reflect real usage patterns? | | 7 | Conciseness | Is content free of redundant repetition? | | 8 | Freedom calibration | Is instruction specificity appropriate? | | 9 | Reference quality | Are references and links accurate? | | 10 | Completeness | Are all sections filled with real content? |

For Prompt mode (10 tailored questions):

| # | Dimension | What to Check | |---|----------|---------------| | 1 | Goal clarity | Does the prompt state a clear, specific goal? | | 2 | Role/tone | Is the desired role or tone specified? | | 3 | Input format | Is the input format clearly described? | | 4 | Output format | Is the expected output format specified? | | 5 | Constraints | Are key constraints and boundaries stated? | | 6 | Context sufficiency | Is enough context provided to avoid hallucination? | | 7 | Edge cases | Does it handle ambiguous or edge case inputs? | | 8 | Conciseness | Is it free of redundant or contradictory instructions? | | 9 | Actionability | Are instructions concrete and actionable vs. vague? | | 10 | Completeness | Are all necessary elements for the task present? |

For Article mode (10 tailored questions):

| # | Dimension | What to Check | |---|----------|---------------| | 1 | Title quality | Does the title clearly convey the main value? | | 2 | Opening hook | Does the opening grab attention and set expectations? | | 3 | Logical structure | Are ideas logically organized (not random)? | | 4 | Argument clarity | Are claims supported with evidence or reasoning? | | 5 | Conciseness | Is unnecessary padding or repetition removed? | | 6 | Transition flow | Do paragraphs/sections flow smoothly? | | 7 | Closing strength | Does the conclusion summarize and inspire action? | | 8 | Tone consistency | Is the tone consistent throughout? | | 9 | Readability | Is sentence/paragraph length varied appropriately? | | 10 | Audience match | Does language match the target audience level? |

Present the 10 questions, numbered 1-10. Ask the user to select which ones to activate (e.g., "use questions 1, 3, 5, 7"). Default: use all 10 if user doesn't specify.

Step 3 — Prepare Test Cases

• Skill mode: Generate 3-5 realistic prompts a user would send when using the skill
• Prompt mode: Generate 3-5 test inputs that the prompt would process
• Article mode: Generate 3-5 ways the article might be read or consumed

Store test cases in context — do not write to disk.

Step 4 — Run Autoresearch Loop

Loop configuration:

• Rounds per batch: 30
• Max total rounds: 100
• Pause: After every 30 rounds, show summary and ask user to continue or stop
• Stop conditions: User says stop, OR 100 rounds completed

Per-round procedure:

1. Mutate: Make ONE small edit to the target content:

   • Skill mode: edit SKILL.md
   • Prompt mode: edit the prompt string
   • Article mode: edit the article text

2. Test: For each test case, simulate what output the content would produce.

3. Score: Apply each active checklist question (0 or 1 per question). Score = (passed / total) × 100.

4. Decide: If new score ≥ best score → keep the mutation. If lower → revert.

5. Log: Round number, mutation type, score, keep/revert decision.

Mutation types (pick one per round):

| Type | Description | |------|-------------| | A | Add a constraint rule | | B | Strengthen trigger/coverage | | C | Add a concrete example | | D | Tighten vague language | | E | Improve error/edge case handling | | F | Remove redundant content | | G | Improve transitions | | H | Expand a thin section | | I | Add cross-reference | | J | Adjust degree-of-freedom |

Step 5 — Report Results

After each batch (30 rounds):

Batch N (rounds X-Y):
  Best score: XX%
  Mutations kept: N  |  Reverted: N
  Most effective types: [list top 2-3]
Accumulated improvements: [summary]
Continue? (yes/stop)

After full completion:

• Original score vs. final score
• Top 3 most impactful mutations
• Final improved content (inline or diff)
• File path (skill mode only)

---

Mutation Strategy Reference

High-impact, low-risk changes:

• Adding explicit constraints where the content is vague
• Expanding coverage to cover edge cases
• Adding concrete examples to abstract instructions
• Tightening soft language ("try to" → "must")

Avoid in one round:

• Large rewrites of entire sections
• Multiple unrelated changes at once
• Changing fundamental scope or purpose

See references/mutation_strategies.md for the full strategy guide.

---

Mode Selection Quick Reference

| User says | Mode | |-----------|------| | "optimize [skill]" / "autoresearch [skill]" | Skill | | "optimize this prompt" / "improve my prompt" | Prompt | | "polish this article" / "improve this article" | Article | | "optimize this document" | Article |

Default to Prompt mode if the input is a text string without a skill path.