Home / uchicago-dsi / ai-sci-skills · skills/run-provenance/SKILL.md · GitHub

run-provenance skillA

run-provenance is agent-read markdown (skill) from uchicago-dsi/ai-sci-skills: Decide how much provenance a computational run owes, record it before the first expensive step, and write a README that says how to remake the output. Use when launching a run, publishing an artifact another run will consume, freezing a checkout for a queued job, or deciding whether a branch, worktree, or recovery copy can be deleted..

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# Run Provenance

Provenance exists so a later reader can tell what produced an artifact and remake
it. Everything below scales with what the artifact is for: a probe nobody will
reuse owes very little, and a parent that other runs consume owes all of it.

## Choose The Tier Before You Launch

Use three tiers so iteration stays fast without weakening durable evidence.

1. **Developer checks.** Compile/import checks, config validation, dry runs, and
   disposable local mechanics probes may use uncommitted code and need no
   provenance artifact. A read-only diagnostic that consumes immutable inputs and
   writes nothing anything else will consume is this tier by default; it needs no
   deliberation about which tier applies.
2. **Exploratory scheduled smokes.** Uncommitted code is allowed when the run root
   automatically records the full base commit SHA, exact command, config hash,
   environment identity, immutable data/parent hashes, working-tree status, and an
   exact binary patch or source snapshot covering every dirty or untracked
   execution path. Report these results only as preliminary, with that provenance.
…

Read the whole file at its exact version.

How to install

Latest version
mdr add uchicago-dsi/ai-sci-skills/run-provenance@git:20260921.9b3de7c
Exact content
mdr add uchicago-dsi/ai-sci-skills/run-provenance@sha256:6125bdce639a9dac

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_q53cxsckxfzxcm5r.svg)](https://markdownregistry.com/a/art_q53cxsckxfzxcm5r)

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Versions

versioncommittedcommitsizeaudit
git:20260921.9b3de7c latest2026-09-21 9b3de7c 7,554 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (7554 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

uchicago-dsi/ai-sci-skills · 20 stars · license MIT · pushed 2026-09-23 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_q53cxsckxfzxcm5r
GET https://markdownregistry.com/api/v1/resolve?ref=uchicago-dsi/ai-sci-skills/run-provenance
GET https://markdownregistry.com/api/v1/blob/6125bdce639a9dacf3172efdad1810d6fe28a5ee034d4aadf1a9e9212c044082

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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