This file is byte-identical to the first copy the registry indexed, one of 6 indexed copies. Same content hash, so the same checks give both the same grade.
principle-foundational-thinking from nightly-labs/openbot is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Foundational Thinking
**Structural decisions** protect option value. **Code-level decisions** protect simplicity.
**Data structures first.** Get the data shape right before writing logic. Define core types early, trace every access pattern, and choose structures that match the dominant paths.
At code level, DRY the structure, not every line. Types and data models should converge. Three similar statements still beat a premature abstraction. Prefer explicit over clever. Test behavior and edge cases, not line counts.
**Concurrency corollary.** Before sharing state between actors, ask "what happens if another actor modifies this concurrently?" If not "nothing", isolate.
**Scaffold first.** If something helps every later phase, do it first. Ask "does every subsequent phase benefit from this existing?" CI, linting, test infrastructure, and shared types are scaffold. Sequence for option value: setup before features, tests before fixes. Keep commits small and single-purpose.
Each increment should land a coherent abstraction or deepen one that exists. Do not spread a new capability across callers as special-case coordination.
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The line at the top of this page pins the label git:20261013.9e6954c, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
A 17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the 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 (1530 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
nightly-labs/openbot · 5,267 stars · license a license file GitHub does not identify · pushed 2026-11-04 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_umfer27e23amak53
GET https://markdownregistry.com/api/v1/resolve?ref=nightly-labs/openbot/principle-foundational-thinking
GET https://markdownregistry.com/api/v1/blob/864b827e8199d946ce58beca0f89c4ed4099ed6e426fb698a3aaa45de2a9eea2
Your AI assistant 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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