Home / habitat-thinking / ai-literacy-superpowers · ai-literacy-superpowers/skills/convention-extraction/SKILL.md · GitHub

convention-extraction skillA

convention-extraction is agent-read markdown (skill) from habitat-thinking/ai-literacy-superpowers: Use when setting up a new project's conventions, onboarding AI to an existing codebase, after team composition changes, or when AI output quality varies depending on who prompts — guides structured discovery of tacit team knowledge into explicit, enforceable artefacts.

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

# Convention Extraction

Most team conventions live in people's heads — pattern recognition
built from years of reviews, production incidents, and architectural
discussions. They transfer slowly through pairing and code review, and
walk out the door when someone leaves. AI amplifies this: without
explicit conventions, AI output quality varies by who prompts. Same
codebase, same AI, completely different quality gates.

This skill guides systematic extraction of tacit knowledge into
versioned, enforceable artefacts. The approach is informed by Rahul
Garg's "Encoding Team Standards" (2026), which frames inconsistent AI
output as a systems problem requiring a systems solution.

This skill does not cover convention enforcement (see constraint-design
and verification-slots), convention maintenance (see context-engineering
and garbage-collection), or CI pipeline configuration.

For the full interview protocol with worked examples, consult
`references/extraction-interview-guide.md`.

## When to Extract

| Situation | Signal |
| ----------- | -------- |
| New project setup | CLAUDE.md and HARNESS.md are empty or boilerplate |
…

Read the whole file at its exact version.

How to install

Latest version
mdr add habitat-thinking/ai-literacy-superpowers/convention-extraction@git:20260415.bb944ba
Exact content
mdr add habitat-thinking/ai-literacy-superpowers/convention-extraction@sha256:ebaf88b6026f4317

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

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Versions

versioncommittedcommitsizeaudit
git:20260415.bb944ba latest2026-04-15 bb944ba 6,352 BA view · diff
git:20260406.60a61ca2026-04-06 60a61ca 6,328 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 (6352 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

habitat-thinking/ai-literacy-superpowers · 106 stars · license NOASSERTION · pushed 2026-09-20 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_f77iafzexisey3ha
GET https://markdownregistry.com/api/v1/resolve?ref=habitat-thinking/ai-literacy-superpowers/convention-extraction
GET https://markdownregistry.com/api/v1/blob/ebaf88b6026f4317baa4d21df30c0a91df2ee871926bd20292ea1734673e5248

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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