skill-release-gate
GitHub在发布前对Agent Skill包进行结构完整性、触发器质量、脚本正确性、安全性及可移植性等全面评估,确保符合发布标准。
Trigger Scenarios
Install
npx skills add rohitg00/ai-engineering-from-scratch --skill skill-release-gate -g -y
SKILL.md
Frontmatter
{
"name": "skill-release-gate",
"license": "MIT",
"metadata": {
"lesson": "27"
},
"description": "Evaluate an Agent Skill bundle for structural integrity, trigger quality, artifact improvement, script correctness, safety, installed-tree integrity, and target-host portability before release."
}
Skill release gate
Use this skill before publishing or distributing an Agent Skill directory bundle.
Workflow
- Resolve
SKILL_ROOTto the absolute directory containing this installedSKILL.md. Do not assume the process cwd is the installed bundle. - Resolve
TARGET_ROOTfrom the original workspace working directory and resolve the user-supplied candidate as an absoluteTARGET_BUNDLE. - Read
references/eval-contract.mdfromSKILL_ROOT. - Inspect the positive and near-miss trigger cases in
evals/cases.jsonunderTARGET_BUNDLE. - Inspect the shared baseline and with-skill assertions in
evals/artifacts.jsonunderTARGET_BUNDLE. - Inspect the explicit script and safety results in
evals/evidence.jsonunderTARGET_BUNDLE. - Inspect the declared runtime capabilities in
assets/hosts.jsonunderTARGET_BUNDLEand verify the target file hashes against itsassets/manifest.json. - For production, replace deterministic predictions, artifacts, evidence,
and host capabilities with captured results; set all four captured modes;
and bind every raw trigger observation, both artifacts, the complete
evidence set, and the non-empty host matrix to non-empty sources and
matching SHA-256 provenance digests. These local checks can set
localEvidenceReady, but locally recomputable hashes do not prove capture. - Obtain an external JSON attestation whose
evidenceRootmatches the report, plus the SHA-256 of its exact bytes from a separate trusted policy or release channel. The attestation must be a regular file outside the target bundle. - Before execution, show the exact resolved argv. The installed evaluator is
scripts/evaluate_skill.pyunderSKILL_ROOT. For the shipped lesson fixture, build argv frompython3, that absolute evaluator path,--fixture-demo, and the absoluteTARGET_BUNDLE. For production, use the same installed script with--attestation,--trusted-attestation-sha256, and the absoluteTARGET_BUNDLE, without--fixture-demo. - Return
checksPassed,fixturePassed,localEvidenceReady,trustAnchorValid,productionReady, andpassedwith the evidence root, evaluation modes, failed checks, precision, recall, every raw trigger observation, per-case repeated-run rates, artifact comparison, script and safety evidence, installed-tree verification, and portability matrix. Include the resolved script path, resolved target path, cwd, exact argv, and exit code. Mark unavailable observations unverified.
Output contract
Return the complete JSON evaluation report. Preserve every layer-specific check and its evidence so a passing aggregate cannot hide a routing, artifact, script, safety, installed-tree, or portability failure. fixturePassed reports a successful teaching fixture. localEvidenceReady reports only local digest integrity. passed is true only when productionReady also has a valid out-of-bundle trust anchor.
Failure behavior
If configuration is invalid, provenance is absent or mismatched, the trusted attestation is missing or invalid, a file hash differs, a required capability is absent, or any production gate fails, stop with a nonzero result and report the failed layer. The explicit --fixture-demo path may exit successfully only when fixturePassed is true, and it never makes a release claim. Never publish, install elsewhere, repair evidence, create the trust decision, or weaken a threshold automatically.
Do not publish a bundle merely because SKILL.md parses or one positive prompt activates. Do not label a package portable when a target drops required companion files or ignores required runtime extensions.
Version History
- 39ea8a1 Current 2026-08-28 11:20


