systematic-exploration

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Strategies for avoiding dead ends and premature conclusions. Read this when stuck or when an approach seems to not work.

A-EVO-Lab By A-EVO-Lab schedule Updated 4/6/2026

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:

  1. List all approaches you've tried AND rejected
  2. For each rejected approach, ask: "Did I test it thoroughly, or did I dismiss it after one attempt?"
  3. 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
Install via CLI
npx skills add https://github.com/A-EVO-Lab/a-evolve --skill systematic-exploration
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