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-sequence-verifiable-units from nightly-labs/openbot is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
Apply to multi-step work (sweeps, migrations, runs of similar edits) and to how you stack commits and PRs. Break work into small units that each end in a verifiable state, check each before the next, and order delivery so the sequence proves itself to a reviewer.
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
# Sequence work into verifiable units
Order work as a sequence of small units, each ending in a state you can check, and don't advance until the current one is green.
**Why:** A break caught at the unit that caused it is cheap to localize. A break caught after a batch is buried, and you have already built further on a broken base. Sequencing those same units into a delivery a reviewer can replay turns "trust me" into "watch it go red, then green."
**Execution.** In a sweep, migration, or any run of similar edits, verify each change before starting the next. Each unit is a before/after bracket: known-good state, one change, run the check, then proceed. Rebase onto clean trunk first so every check measures against the real baseline. When a lever does the edits, the per-unit check is nearly free. Run it anyway.
**Delivery.** Stack commits and PRs in the order that proves the work. The canonical shape is the failing test first, then the fix on top. Other story orders are a subtraction before the reshape, a baseline capture before the treatment, the scaffold before the feature. Each commit lands on its own and the sequence reads as an argument.
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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 (1705 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_adwmmc4b6pqf6mpl
GET https://markdownregistry.com/api/v1/resolve?ref=nightly-labs/openbot/principle-sequence-verifiable-units
GET https://markdownregistry.com/api/v1/blob/2ccbbacc56ace5afdfb8670cef19d7bd009fb2a0033b9a741cbdf2b6baf72187
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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