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research-code-parsimony skillA

research-code-parsimony is agent-read markdown (skill) from uchicago-dsi/ai-sci-skills: Keep scoped implementation and review work from growing unnecessary code by identifying the real owner, real callers, and existing capability before adding surface. Use when writing, extending, or reviewing research code; for a dedicated cleanup pass over pre-existing debt, use a maintenance skill instead..

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

# Research Code Parsimony

## Establish The Contract And The Owner First

Before adding code, be able to state:

- the behavior or scientific contract being requested, including what must stay reproducible;
- the module, function, script, or config that already owns this behavior, and which callers actually exercise it;
- whether a maintained dependency or a native language/library capability already provides it.

Search before creating an owner. If none fits a genuinely new capability, create one clear owner rather than forcing unrelated behavior into an existing module.

## Reuse Before You Add

- Extend an understood existing owner instead of introducing a parallel one.
- Prefer a maintained dependency when it reduces ownership burden while meeting the scientific and operational contract. Check the standard library and present dependencies first.
- Parsimony means less code to own — not fewest files, shortest diff, or clever one-liners. Readable, explicit code beats a compressed version.
- Never satisfy the request by solving a smaller or easier scientific problem than the one asked for.

## Express Cohesive Families As Directories
…

Read the whole file at its exact version.

How to install

Latest version
mdr add uchicago-dsi/ai-sci-skills/research-code-parsimony@git:20260922.86f870d
Exact content
mdr add uchicago-dsi/ai-sci-skills/research-code-parsimony@sha256:c3c8e7d82e944548

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.

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Versions

versioncommittedcommitsizeaudit
git:20260922.86f870d latest2026-09-22 86f870d 14,660 BA view · diff
git:20260922.2a3a6c42026-09-22 2a3a6c4 13,909 BA view · diff
git:20260921.9b3de7c2026-09-21 9b3de7c 12,946 BA view · diff
git:20260905.878f7fc2026-09-05 878f7fc 5,282 BA view · diff
git:20260904.8c561a12026-09-04 8c561a1 3,819 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 (14660 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_fi6bp5ilfdyhzb4v
GET https://markdownregistry.com/api/v1/resolve?ref=uchicago-dsi/ai-sci-skills/research-code-parsimony
GET https://markdownregistry.com/api/v1/blob/c3c8e7d82e94454810d186f227b2e8300ac0221b553eeebdac9d25e72314ab5b

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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