Rigor Run skill for README-first deep learning repo reproduction.
Use when the task is specifically to capture or normalize evidence from the selected smoke test or documented inference or evaluation command and write standardized `repro_outputs/` files, including patch notes when repository files changed.
Do not use for training execution, initial repo intake, generic environment setup, paper lookup, target selection, hidden scientific-meaning changes, or end-to-end orchestration by itself.
Stronger alternatives
Audit results are mixed — compare nearby options before installing.
Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.
Claude CodeNot declared
CursorNot declared
CodexNot declared
GitHub CopilotNot declared
WindsurfNot declared
Gemini CLINot declared
ClineNot declared
OpenCodeNot declared
Repository health
Stars484
LicenseLICENSE
Default branchmain
Open issues0
Status
Active
Package contents
Files included with this skill beyond the listing page.
skill mdSKILL.md2,761 B
docsSUMMARY.md525 B
History
First seen on skills.sh
First recorded snapshot · 450,000 installs
SKILL.md
minimal-run-and-audit
Use this as the Rigor Run skill. The installed slug remains minimal-run-and-audit for compatibility.
Use the shared operating principles in ../ai-research-reproduction/references/agent-operating-principles.md; this skill should make run evidence auditable without turning every command into a rigid protocol.
When to apply
After a reproduction target and setup plan exist.
When the main skill needs execution evidence and normalized outputs.
When a smoke test, documented inference run, documented evaluation run, or other short non-training verification is appropriate.
When the user already knows what command should be attempted and wants execution plus reporting only.
When not to apply
During initial repo scanning.
When environment or assets are still undefined enough to make execution meaningless.
When the task is a literature lookup rather than repository execution.
When the user is still deciding which reproduction target should count as the main run.
Clear boundaries
This skill owns normalized reporting for an attempted command.
It may receive execution evidence from the main skill or a thin helper.
It does not choose the overall target on its own.
It does not perform broad paper analysis.
It does not own training startup, resume, or long-running training state.
It should not normalize risky code edits into acceptable practice.
It must not hide changes that alter evaluation, preprocessing, checkpoints,
metrics, or other scientific meaning.
Input expectations
selected reproduction goal
runnable commands or smoke commands
environment and asset assumptions
optional patch metadata
Output expectations
execution result summary
standardized repro_outputs/ files
SCIENTIFIC_CHANGELOG.md for changed scientific meaning and evidence status
COMPARABILITY_REPORT.md for README/paper/baseline comparability
clear distinction between verified, partial, and blocked states
PATCHES.md when repo files changed
Notes
Use references/reporting-policy.md, ../ai-research-reproduction/references/research-rigor-principles.md, scripts/runcommand.py, and scripts/writeoutputs.py.
