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.

Security Scan

The skill's instructions mostly match its stated purpose (iterative, one-change-at-a-time improvements), but it can read and overwrite other skill/plugin files and contains contradictory guidance about editing code — this broad filesystem access and inconsistency merit caution before installing or giving it permission to run autonomously.

Purpose & Capability

The name/description (autoresearch to optimize prompts/skills/articles) aligns with instructions to mutate, test, and score small edits. However the docs contradict themselves: README/README_zh advertise 'Plugin mode: optimize plugin configuration and code', while the Precautions explicitly say 'Not for code with actual runtime behavior (use tests instead)'. That inconsistency between claiming code/plugin editing and warning against editing run-time code is a design incoherence.

Instruction Scope

SKILL.md instructs the agent to locate, read, mutate, test, score, and save SKILL.md files under user paths (e.g., ~/.claude/skills/<name>/SKILL.md and plugin directories). Those read/write operations (search current dir, inspect ~/.claude/skills, save final file back to ~/.claude/skills/<target>/SKILL.md) allow the skill to access and modify other local skill/plugin files beyond what the skill metadata declares. The skill does require confirming with the user before proceeding, but the instructions enable automated, repeated edits (up to 100 rounds) which could introduce or propagate undesired changes if misused.

Install Mechanism

No install spec or code files; instruction-only skill — lowest install risk. The README suggests cloning a GitHub repo as an optional manual install, but the skill package itself has no installer or external downloads.

Credentials

The skill declares no required env vars or config paths, yet its runtime instructions assume access to user filesystem locations (home ~/.claude/skills, plugins directories, current directory) and to write back to those locations. Because these paths are not declared in metadata, there is a mismatch between what the skill claims to need and what its instructions instruct it to access/write.

Persistence & Privilege

always:false (normal). The skill can modify files under user skill/plugin directories (it explicitly saves optimized SKILL.md back to target locations). That behavior is within the stated purpose (editing skills) but grants write capability to other skills' files — users should ensure changes are reviewed and backups are kept. The skill's requirement for a user confirmation step mitigates but does not eliminate risk if the agent is allowed to act autonomously after consent.

What to consider before installing

This skill is coherent with its stated goal of iteratively improving text content, but exercise caution: it instructs the agent to search, read, mutate, and overwrite files in ~/.claude/skills and plugin directories even though no config paths are declared. Before installing or running: 1) restrict its target — don't point it at system or sensitive directories; 2) keep backups (or use version control) of any SKILL.md or plugin files that might be edited; 3) require explicit human approval before allowing write/save operations or many autonomous rounds; 4) avoid using it to modify runtime code unless you fully understand and review generated changes (the docs are inconsistent about editing code); and 5) consider running it first on a copy of the target content to verify behavior and outputs.

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:

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

After full completion:

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)

"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.