Cjl Autoresearch Cc

Optimize skills, prompts, articles, workflows, or systems via single-step iterative edits with testing and scoring to keep improvements and discard regressions.

Overview

Improve skills, prompts, articles, workflows, and systems via iterative mutation-testing.

Core principle: One small verifiable change per round. Large rewrites are unverifiable and will be reverted.

Workflow: small edits → test → score → keep improvements, discard regressions.

Inspired by Karpathy/autoresearch and 0xcjl/openclaw-autoresearch-pro.

Trigger Keywords

English: autoresearch

Chinese: 自动优化, 自动研究

Semantic Triggers (No Keywords Needed)

This skill activates when the user's intent matches, even without explicit keywords:

• User wants to improve any skill, prompt, article, workflow, or system
• User asks to polish, refine, enhance, or upgrade content
• User wants iterative testing and improvement
• User says '帮我改进一下这个prompt', 'optimize this'
• User says '迭代优化', '循环改进', '反复打磨'
• User asks '能不能更好', '如何提升质量'
• User uses "打磨", "精炼", "完善", "升级" in context of content improvement

Supported Optimization Targets

Mode	Input	Example
Skill	Skill name or path	coding-standards, ~/.claude/skills/tdd-workflow
Plugin	Path to a plugin directory	~/.claude/plugins/everything-claude-code
Prompt	A prompt text string	Inline or file path
Article	An article/document text	Inline or file path
Workflow	A process or workflow description	Inline or file path
System	A mechanism or system design	Inline or file path

Workflow

Step 1 — Identify Mode and Target

Before proceeding, confirm with user:

"Optimize [target] in [mode] mode? (yes/no)"

If no, ask for clarification. If yes, proceed to Step 2.

Parse the user's request to determine mode. Check for:

Keyword triggers:

• autoresearch [target] / 自动优化 [target] / 自动研究 [target]
• optimize [target] / improve [target] / 优化 [target] / 改进 [target]
• refine [target] / enhance [target] / 精炼 [target] / 增强 [target]

Semantic triggers (intent-based):

• User wants to improve any skill, prompt, article, workflow, or system
• User asks to polish, refine, enhance, or upgrade content
• User describes wanting iterative testing and improvement

Mode detection from intent:

User Intent	Mode
Optimize a skill/SKILL.md file	Skill
Optimize an agent configuration	Skill
Improve a custom command	Skill
Optimize a plugin	Plugin
Improve hooks configuration	Plugin
Improve a prompt text	Prompt
Polish an article/document	Article
Optimize a workflow/process	Workflow
Improve a system mechanism	System

For Skill/Plugin mode, resolve the path:

• Skill: ~/.claude/skills/<skill-name>/SKILL.md
• Plugin: ~/.claude/plugins/<plugin-name>/

If path doesn't exist, search in order: ~/.claude/skills/ → current dir → ask user.

Examples of semantic triggers (no keywords):

• "帮我优化一下这个skill" → Skill mode
• "这个prompt不够好，帮我改进" → Prompt mode
• "我想让这篇文章更通顺" → Article mode
• "优化一下部署流程" → Workflow mode

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/Plugin mode:

#	Dimension	What to Check
1	Description clarity	Is the description precise, actionable, and clear? Does it state what the skill does and when to use it?
2	Trigger coverage	Does it cover 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 Claude Code?
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:

#	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/Documentation mode:

#	Dimension	What to Check
1	Title quality	Does the title clearly convey the main value? Is it specific enough?
2	Opening hook	Does the opening grab attention? Does it set clear 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?

For Workflow/System mode:

#	Dimension	What to Check
1	Goal clarity	Is the objective clearly stated?
2	Step sequencing	Are steps in logical, efficient order?
3	Completeness	Are all necessary steps present?
4	Error handling	Are failure modes addressed (timeout, auth, network, resource exhaustion)?
5	Edge cases	Are corner cases considered (empty input, large files)?
6	Simplicity	Is the workflow/system as simple as possible? Can steps be combined or eliminated?
7	Observability	Can progress/status be tracked?
8	Reversibility	Can steps be undone if errors occur?
9	Automation potential	Which steps could be automated?
10	Maintainability	Is it easy to modify and extend?

Present the 10 questions, numbered 1-10. Ask the user to select which ones to activate.

Rule: Must use at least 5 questions. Using fewer makes scoring unreliable.

After presenting, ask: "Ready to start the optimization loop? (yes/start)"

Step 3 — Prepare Test Cases

Test cases validate that mutations improve, not harm, the content. Generate realistic user scenarios.

• Skill/Plugin mode: Generate 3-5 realistic prompts a user would send when using the skill/plugin
• 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
• Workflow mode: Generate 3-5 scenarios the workflow would handle
• System mode: Generate 3-5 conditions the system would encounter

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

Step 4 — Run Autoresearch Loop

Tip: For mutation strategies, see Mutation Strategy Reference below.

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
  • 100 rounds completed
  • Score reaches 100%
  • No improvement for 10 consecutive rounds

Per-round procedure:

Track progress: Round N/100 | Best: XX% | Last: +/-YY

Constraint: ONE mutation per round. Multiple changes = unverifiable = will be reverted.

1. Mutate: Make ONE small edit (see Mutation types)

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

   Constraint: Be honest. If the output would disappoint a user, the mutation failed.

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

   Scoring scale:

   • 10/10 = 100% (perfect)
   • 7/10 = 70% (good)
   • 5/10 = 50% (minimum viable)

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

   Example: Best=85%, New=87% → Keep. Best=85%, New=83% → Revert.

   Trust the score. Don't rationalize a bad mutation.

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

Mutation types (pick ONE per round):

Type	Name	When to Use
A	Add constraint	When content is too vague
B	Strengthen coverage	When trigger cases are missing
C	Add example	When steps are too abstract
D	Tighten language	When words are soft ("try to")
E	Error handling	When failure modes missing
F	Remove redundancy	When content is verbose
G	Improve transitions	When flow is choppy
H	Expand thin section	When content is sparse
I	Add cross-ref	When sections are isolated
J	Adjust freedom	When balance is off

Step 5 — Report Results (after each batch)

See Quick Reference below for output format examples.

After each batch (30 rounds):

Example:

text

Batch 1 (rounds 1-30):
  Best score: 85%
  Mutations kept: 23  |  Reverted: 7
  Most effective types: A, C, D

After full completion:

text

Optimized: [filename/path]
Score: XX% → YY% (+ZZ%)
Rounds: N (kept: K, reverted: R)
Top mutations: [type, type, type]
---
Final content:
[diff or inline]

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
• Formatting-only changes (no testable value)
• Adding content the user didn't request
• Removing more than 10% of content

Quick Reference

Keywords Reference

Auto-detect: autoresearch, 自动优化, 自动研究 Skill: autoresearch ~/.claude/skills/tdd Prompt: optimize this prompt: [text] Workflow: optimize the deployment workflow System: improve the error handling system

Semantic Triggers (No Keywords)

text

"帮我优化一下这个skill"           # → Skill mode
"这个prompt不太行"               # → Prompt mode
"我想让文章更通顺"               # → Article mode
"优化一下部署流程"               # → Workflow mode
"改进一下这个系统"               # → System mode
"improve this code review"         # → Prompt/Skill mode
"polish this documentation"       # → Article mode

Mode Detection

Situation	Action
Path detected	Skill/Plugin mode
Keyword present	Keyword-specified mode
Short text	Prompt mode
Long document	Article mode
Uncertain	Prompt mode (default)

Edge cases: Empty → ask. Invalid path → fallback to ~/.claude/skills/. Ambiguous → ask.