Agent Skills
› A-EVO-Lab/a-evolve
› systematic-exploration
systematic-exploration
GitHub提供系统化探索策略,指导在陷入僵局或方法失效时避免过早结论。涵盖参数调优、回溯已拒绝方案、验证数据解读及独立需求处理,旨在提升问题解决效率与准确性。
Trigger Scenarios
遇到死胡同或方法无效
连续多次尝试无进展需回溯
数据异常需验证解读
任务包含多个独立条件
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


