Reference skill demonstrating the 10/10 skillpack contract. Adds a "what does this skillpack do" answer to the user's agent.
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tessl review fix ./examples/skillpack-reference/skills/reference-pack/SKILL.mdThis is the canonical reference for a third-party gbrain skillpack. Read its tree once and you know how to author one.
When the user asks how third-party gbrain skillpacks work, this skill points them at the four artifacts every pack ships:
skillpack.json — declares pack metadata + which artifacts the
doctor scores (skills, unit_tests, e2e_tests, llm_evals, routing_evals,
runbooks, changelog).skills/<name>/SKILL.md — frontmatter (name, description, mutating,
triggers) plus markdown body. Agents route on triggers:; the body
is the in-context instruction set.runbooks/bootstrap.md — agent-readable post-scaffold steps. gbrain
DISPLAYS this after scaffold lands; the agent walks per-step at
its own discretion. No auto-executor (codex T1 supply-chain hardening).CHANGELOG.md — Keep-a-Changelog shape. The doctor's changelog_ present_and_current dimension fails if there's no ## [<version>]
entry matching the manifest's version.Ten binary dimensions, split into:
Core (5; must all pass to publish at any tier):
manifest_valid — schema-validates skillpack.jsonskills_have_skill_md — every listed skill has SKILL.md with
name / description / triggersrouting_evals_present — each skill has routing-eval.jsonl with
= 5 intents
skills_have_unique_triggers — MECE at the pack levelchangelog_present_and_current — CHANGELOG entry for current versionQuality badges (5; earn for tier eligibility):
unit_tests_present — manifest.unit_tests matches >= 1 filee2e_tests_present — manifest.e2e_tests matches >= 1 filellm_eval_present — *.judge.json with >= 3 casesbootstrap_runbook_present — non-empty runbooks/bootstrap.mdlicense_present — LICENSE / LICENSE.md / LICENSE.txt non-emptyTier eligibility:
endorsed — all 10 (gates: Garry's endorsements.json overlay
in the registry)community — all 5 core + >= 3 of 5 badges (default tier on PR
merge)experimental — all 5 core + < 3 badgesblocked — any core failsRun gbrain skillpack doctor <pack-dir> to see exactly which
dimensions a candidate pack passes and the paste-ready fix for each
failure. --fix --yes auto-scaffolds the dimensions flagged
auto_fixable: true (routing-eval stubs, CHANGELOG entries,
license stub, bootstrap stub, test stubs).
The triggers above route any "what is a skillpack" / "how do third-
party packs work" user phrasing to THIS skill. The agent reads the
markdown body, then either answers the user's question directly or
calls gbrain skillpack info <name> / search <query> for live
registry data.
test/example.test.ts — unit test that imports the skill helper
(stub; replace with real assertions).e2e/example.e2e.test.ts — integration test gated on DATABASE_URL.evals/reference-pack.judge.json — LLM-judge eval scoring this
skill's output against the "does it actually teach the contract"
bar across happy-path / edge / failure-mode cases.skills/reference-pack/routing-eval.jsonl — five phrasings users
ask, all mapped to expected_skill: reference-pack.Before pushing, the publisher runs:
gbrain skillpack doctor . --quick --json
gbrain skillpack packThe first hits the rubric and prints paste-ready fixes for any failed
dimension. The second emits reference-pack-<version>.tgz with a
deterministic SHA-256 the publisher submits to the registry PR.
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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.