Agent Skills
› A-EVO-Lab/a-evolve
› systematic-exploration
systematic-exploration
GitHub提供系统化探索策略,避免死胡同和过早结论。指导在方法失败时调整参数、陷入僵局时回溯重试、验证数据解读及独立处理多条件需求,适用于解决开发中的复杂问题与调试困境。
Trigger Scenarios
遇到死胡同或当前方法无效
对结果存疑需验证解读
处理多个独立约束条件
Install
npx skills add A-EVO-Lab/a-evolve --skill systematic-exploration -g -y
SKILL.md
Frontmatter
{
"name": "systematic-exploration",
"description": "Strategies for avoiding dead ends and premature conclusions. Read this when stuck or when an approach seems to not work."
}
Systematic Exploration
Don't reject approaches based on a single test
When a promising approach (solver, algorithm, transformation) gives bad results:
- Vary the key parameter across a wide range before rejecting (e.g., iterations: 1, 5, 20, 50, 100)
- Combine with other settings (disable warmstart, change precision, different flags)
- A method that fails with default parameters may succeed with tuned parameters
Stuck for 5+ turns? Backtrack.
If you've been optimizing the same approach without crossing the threshold:
- List all approaches you've tried AND rejected
- For each rejected approach, ask: "Did I test it thoroughly, or did I dismiss it after one attempt?"
- Re-test the most promising rejected approach with different configurations
Verify your interpretation before committing
When data looks unusual or results seem off:
- Try multiple interpretations of the data (different units, coordinate transforms, encodings)
- Don't lock in on the first plausible explanation — test at least 2 alternatives
- Check if numerical coincidences are real or spurious (e.g., ratio match vs exact value match)
Independent requirements
When a task lists multiple criteria (A, B, C):
- Each criterion may be satisfied by DIFFERENT entities unless explicitly stated otherwise
- Don't combine independent filters into a single query/check
Version History
- c9d4789 Current 2026-07-25 07:28


