execution
Run a local mathematical experiment through the MathModel runtime and package traceable observations, metrics, checks, and figures.
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.
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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/execution
What's inside
- Skill name
execution- Description
- Run a local mathematical experiment through the MathModel runtime and package traceable observations, metrics, checks, and figures. Use for numerical experiment requests, not for scheduling or publication-only restyling.
- License
- MIT
- Instructions
- 22 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
Use the runtime-backed execution API in `mathmodel_agent.execution`; do not start a private subprocess, task queue, or per-seed worker system. - Make every command argv explicit and case-relative inputs explicit. Use only the documented command placeholders from `docs/modules/execution.md`. - Use `formal` only after supplying a stable comparison-contract JSON. Preserve every planned instance, including failed or timed-out ones. Deterministic algorithms have `seed: null`. - Treat a fresh algorithm launch as a new `experiment_run_id`. Do not call a receipt replay a scientific rerun. - Write complete JSONL observations and figure provenance files before finalization. Do not infer `not_run` from missing output: only a task with no runtime attempt is `not_run`; otherwise preserve `unknown` or `partial` facts. - Use metric recomputation and independent checks only where their method matches the recorded check type. A process rerun and an independent implementation are different claims. - Keep raw input data read-only. A visual redraw does not modify a metric; a change to samples, aggregation, units, or numerical values needs a new experiment package. Read [the execution contract](../../docs/modules/execution.md) before preparing a formal run.
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 - 0.587score
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 - 0.546score
exploration
SoFarSoGoodya
Develop independently reasoned mathematical-modeling candidates and fixed comparison material for an approved case.
SkillBFreshness: B★ 2Claude Code +9
Signals
- Stars
- 2
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Oct 2, 2026 (29 days 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 - 0.587score
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 - 0.546score
exploration
SoFarSoGoodya
Develop independently reasoned mathematical-modeling candidates and fixed comparison material for an approved case.
SkillBFreshness: B★ 2Claude Code +9
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Cite this page
execution skill. Agent Mart. https://agentmart.dev/skills/sofarsogoodya-execution (last updated 2026-10-24)