PaperclipOrg
Claude Agent Skill · by Lllllllama

Minimal Run And Audit

When you've already identified what command to run in an AI research repo and just need clean execution evidence, this handles the boring parts. It runs your sm

Install
Terminal · npx
$npx skills add https://github.com/obra/superpowers --skill test-driven-development
Works with Paperclip

How Minimal Run And Audit fits into a Paperclip company.

Minimal Run And Audit drops into any Paperclip agent that handles this kind of work. Assign it to a specialist inside a pre-configured PaperclipOrg company and the skill becomes available on every heartbeat — no prompt engineering, no tool wiring.

S
SaaS FactoryPaired

Pre-configured AI company — 18 agents, 18 skills, one-time purchase.

$27$59
Explore pack
Source file
SKILL.md47 lines
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---name: minimal-run-and-auditdescription: Trusted-lane execution and reporting skill for README-first AI 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, or end-to-end orchestration by itself.--- # minimal-run-and-audit ## 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. ## 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- clear distinction between verified, partial, and blocked states- `PATCHES.md` when repo files changed ## Notes Use `references/reporting-policy.md`, `scripts/run_command.py`, and `scripts/write_outputs.py`.