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SoFarSoGoodyaSoFarSoGoodya/mathmodel-weave/skills/exploration/SKILL.md

exploration

Skill2 starsChanged 41 days agoMITView on GitHub

Develop independently reasoned mathematical-modeling candidates and fixed comparison material for an approved case.

3 other projects use a version of this.

Adopted by

Most recently taken up by

  • Other versions3 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository6 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use a Variant only for implementation/configuration changes within a Candidate.

    line 12
  2. Distinctive:

    Before formal scoring, fix data/split, metric formulas and units, constraints, meaningful baseline, fair budget, failure denominator, and …

    line 14

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Exploration

Produce a Candidate as a readable mathematical route: subproblem, origin, variables/objective/constraints, derivation, pseudocode, sources, assumptions, limitations, and a structural difference from known routes. An algorithm name, prompt persona, or parameter setting is not a distinct Candidate.

First-round authors receive only the problem contract, selected data/material, and reliable shared sources. Do not inject another first-round draft or recommendation. A human suggestion remains one candidate or a challenge target unless the human explicitly fixed a base route and its conditions independently hold.

Use a Variant only for implementation/configuration changes within a Candidate. A changed mathematical structure, stage composition, objective, or error propagation is a new Candidate; a fusion records parents but begins unreviewed.

Before formal scoring, fix data/split, metric formulas and units, constraints, meaningful baseline, fair budget, failure denominator, and stopping condition in a ComparisonContract. Preserve evidence, uncertainty, and tradeoffs in comparison packs. Do not manufacture aggregate scores, benchmarks, totals, or experimental conclusions.

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