exploration
Develop independently reasoned mathematical-modeling candidates and fixed comparison material for an approved case.
Skill by SoFarSoGoodya
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/sofarsogoodya-exploration
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/exploration
What's inside
- Skill name
exploration- Description
- Develop independently reasoned mathematical-modeling candidates and fixed comparison material for an approved case.
- License
- MIT
- Instructions
- 11 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# 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.
From SoFarSoGoodya/mathmodel-weave, MIT.
More from SoFarSoGoodya/mathmodel-weave
- 0.598score
publication
SoFarSoGoodya
Build and review a Chinese XeLaTeX mathematical-modeling paper from a fixed selected result, evidence freeze, and formal execution manifest.
SkillAFreshness: A★ 2Claude Code +9 - 0.595score
execution
SoFarSoGoodya
Run a local mathematical experiment through the MathModel runtime and package traceable observations, metrics, checks, and figures.
SkillAFreshness: A★ 2Claude Code +9 - 0.587score
coordinator
SoFarSoGoodya
Coordinate a bounded mathematical-modeling case through runtime RESULT.json handoffs and human decisions.
SkillAFreshness: A★ 2Claude Code +9 - 0.554score
evidence
SoFarSoGoodya
Intake modeling problem files and curate research evidence with faithful source text, targeted verification, pins, and freezes.
SkillBFreshness: B★ 2Claude Code +9 - 0.549score
review
SoFarSoGoodya
Independently review mathematical-modeling candidates, experiments, comparisons, or fusions from fixed selected material.
SkillBFreshness: B★ 2Claude Code +9
Signals
- Stars
- 2
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Sep 13, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/SoFarSoGoodya/mathmodel-weave
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from SoFarSoGoodya
- 0.598score
publication
SoFarSoGoodya
Build and review a Chinese XeLaTeX mathematical-modeling paper from a fixed selected result, evidence freeze, and formal execution manifest.
SkillAFreshness: A★ 2Claude Code +9 - 0.595score
execution
SoFarSoGoodya
Run a local mathematical experiment through the MathModel runtime and package traceable observations, metrics, checks, and figures.
SkillAFreshness: A★ 2Claude Code +9 - 0.587score
coordinator
SoFarSoGoodya
Coordinate a bounded mathematical-modeling case through runtime RESULT.json handoffs and human decisions.
SkillAFreshness: A★ 2Claude Code +9 - 0.554score
evidence
SoFarSoGoodya
Intake modeling problem files and curate research evidence with faithful source text, targeted verification, pins, and freezes.
SkillBFreshness: B★ 2Claude Code +9 - 0.549score
review
SoFarSoGoodya
Independently review mathematical-modeling candidates, experiments, comparisons, or fusions from fixed selected material.
SkillBFreshness: B★ 2Claude Code +9
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Cite this page
exploration skill. Agent Mart. https://agentmart.dev/skills/sofarsogoodya-exploration (last updated 2026-10-24)