verify
Skill1 starsChanged 15 days agoApache-2.0View on GitHub
Establish that a change, or the whole codebase when nothing has changed, actually works, by formal proof where the properties allow and by reproducible executable verification otherwise. This is the release gate before merging or deploying. Use it whenever you are about to say something works, is fixed, is done, or is ready, before committing, pushing, merging or deploying, whenever the user asks to verify, prove, check or test a change or the repository, or asks "did you run it" or "is it done", and after any fix that has not been verified, even if the user did not ask.
188 other projects use a version of this.
Adopted by
Most recently taken up by
- Doist/todoist-aitheir own version, first seen Nov 9, 2026
- udecode/better-convextheir own version, first seen Nov 9, 2026
- pytorch/heliontheir own version, first seen Nov 8, 2026
- amir20/dozzletheir own version, first seen Nov 8, 2026
- Doist/todoist-clitheir own version, first seen Nov 8, 2026
- codewithmukesh/dotnet-claude-kittheir own version, first seen Nov 8, 2026
Used with
Projects with it also use instinct-export, instinct-import and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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AaravChadhaSkillsecure
Security review with a confidence gate - a finding exists only with a concrete exploit scenario and a high/medium/low confidence rating; everything else goes to a worth-hardening list, never inflated. Sweeps five surfaces: auth gates, secrets hygiene, injection and unsafe sinks, unsafe deserialization/crypto/transport, and LLM tool-use trust boundaries. Reports only, never fixes. Use when the user asks for a security review or to check vulnerabilities, secrets, or auth.
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ArvorCoSkillspecify
Create feature specification from natural language description. Use when starting a new feature or creating a spec. Triggers on: create spec, specify feature, new feature spec.
Also in 10 projects that use this
- +1 more from TheKREATORS
Other versions188 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 188
- react/react★ 252ksame name
- facebook/react★ 252ksame name
- garrytan/gstack★ 141ksame name
- oven-sh/bun★ 97ksame name
- anthropics/financial-services★ 41ksame name
- anthropics/financial-services-plugins★ 41ksame name
- Yeachan-Heo/oh-my-claude-sisyphus★ 41ksame name
- Yeachan-Heo/oh-my-claudecode★ 41ksame name
- anthropics/claude-quickstarts★ 19ksame name
- NVIDIA-NeMo/Speech★ 19ksame name
178 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository19 other files it gives its agents.
- AGENTS.mdAGENTS.md
- ai-chatSkill
- argocdSkill
- code-reviewSkill
- commitSkill
- dependency-trackSkill
- financeSkill
- handoffSkill
- java-21-to-25-migrationSkill
- jenkinsSkill
- jiraSkill
- perplexitySkill
- pr-readySkill
- researchSkill
- shipSkill
- skanetrafikenSkill
- sonarqubeSkill
- tddSkill
- to-tasksSkill
The file
We split this skill into the rules it gives an agent
5 rules. 0 are common, 5 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 167 edited versions we read keep these.
5
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 31
Prefer the repository's own tooling, then select methods by actual risk:
- Distinctive: line 51
Test what will actually ship: the candidate release artifact, pinned dependencies, and production-relevant configuration.
- Distinctive: line 55
Look for counterexamples and minimize the ones you find.
- Distinctive: line 59
Keep destructive tests in disposable environments, and document the production differences Docker cannot reproduce.
- Distinctive: line 65
Write for engineers who know state machines but not necessarily formal languages.
“Common” is measured: kept by at least 6 in 10 of the 167 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Verify
Saying that something works is a claim other people will act on, so it needs evidence they can check. Establish that it works by formally proving it where the properties allow, and by verification that anyone can rerun with the same result. A claim without a proof or a reproducible run is not verified.
The aim is executable evidence. Create and run verification artifacts; a review or a proposed test plan does not count.
Scope: the change, or the whole codebase
With a change (uncommitted work, a branch, a diff, a revision), verify that change against the intended target branch, including the existing behavior it can affect. With no change, or when asked to verify the repository, the candidate is the whole codebase at its current revision: every component and the system's end-to-end behavior. Do not shrink a whole-codebase request to the last commit or to the checks that are easiest to run. State the scope and the revision at the top of the result.
Choose the properties and methods
Identify the release-critical properties and the required checks. Derive them from the requirements, not from what the current implementation happens to do, and write down every inferred requirement and assumption so a reader can disagree with it.
Prefer the repository's own tooling, then select methods by actual risk:
- Property-based and stateful testing for inputs, sequences, and invariants.
- Deterministic simulation testing for controlled scheduling and fault injection.
- TLA+/TLC for state-machine model checking; TLAPS or Lean 4 for machine-checked proofs where a proof is appropriate.
- Docker Compose or Testcontainers for real-service integration and recovery.
Using every method by default adds cost without evidence. Pick the ones that match a real risk and say which were skipped and why.
Build and run it
Make the verification reproducible: a clear entry point, exact commands, pinned versions, recorded seeds, and acceptance criteria, so a fresh checkout reruns it and reaches the same result. Run the existing relevant checks and add what is missing. Keep the artifacts that stay useful (tests, models, specs, the entry-point command) in the change, and keep the report out of the repository unless it already keeps such reports. Start any test database the repository provides before the run and tear it down after, including after a failure.
Test what will actually ship: the candidate release artifact, pinned dependencies, and production-relevant configuration. Exercise failure paths, not only successful requests, and include compatibility, migrations, and rollback where they apply.
Look for counterexamples and minimize the ones you find. Where practical, introduce a controlled violation and confirm that the matching check fails, because a check that cannot fail proves nothing. Never weaken a requirement or an assertion to get a passing result.
Keep destructive tests in disposable environments, and document the production differences Docker cannot reproduce. Change verification artifacts as needed; change production code only when authorized. Rerun the affected checks after every change.
Make it readable
Write for engineers who know state machines but not necessarily formal languages. Identify the state, the transitions, the properties, and the assumptions. Explain each important claim and any non-obvious notation in plain English, and use a small example or trace where it helps. Show how each model corresponds to the implementation, what it abstracts away, and what remains unchecked.
Evidence and verdict
Bind every result to the exact revision and release artifact tested, so it cannot be mistaken for evidence about something else. Keep the commands, observed results, relevant logs, seeds, counterexamples, model bounds, and proof assumptions, and keep expected outcomes separate from what actually ran.
Say which kind of evidence each result is: empirical testing, model checking, or machine-checked proof. A formal proof must be complete, with its assumptions and axioms disclosed. Passing tests do not establish unrestricted correctness, and a proved model is not a proved implementation.
Return one verdict:
- PASS: the release-critical properties have adequate evidence and every required check passed for the candidate.
- FAIL: a required check failed or a correctness violation was demonstrated.
- BLOCKED: required verification is incomplete, unavailable, or inconclusive.
Deliver the runnable artifacts, the reproduction instructions, and the remaining risks. Never mark an unexecuted check as passed, report a result while a suite is still running, or retry a red check without saying so, since each of those hides a real failure. The verdict covers one revision, so any later commit or rebase needs the affected checks rerun. Verifying does not authorize merging, pushing, or deploying.
Does it work?
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- It worked
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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