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Get Started Free →Use when the user asks to "log this launch", query a launch date/embargo, record a stage transition, or update submissions/outcomes; curates launch facts through the append-only launches event stream with optimistic revisions and derived dossier/calendar views. Not for RAMP scoring — use launch-readiness-auditor; not for planning tier/window — use launch-tier-planner. 发布台账/发布日历/阶段与禁运期记录
.claude/skills/aaron-he-zhu-launch-registry/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 105% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 52% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 13% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 17% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -29% | 0% |
The canonical launch-record authority. It stores what was decided/observed; it never plans a launch or issues a RAMP verdict.
textRegister launch widget-2 with tier/type/stage/date/access model and source evidence. Transition widget-2 from beta to general-availability at revision 4. Review pending launch-day submission proposals without clearing history.
Unit: one launch moment/aggregate ID. Reads: memory/events/launches.ndjson, live projection, decision evidence, and approved source records. Writes: owner events through registry-events.py; per-launch dossiers and calendar.md are regenerated views. Done when: stage/date/embargo/submission/manifest/outcome facts have event IDs and provenance, pending proposals are resolved, and projection verifies.
Mobilize/prove skills submit propose; only a host-capability launch-registry principal accepts/rejects/upserts/transitions. launch-readiness-auditor consumes the result but cannot mutate it.
Include aggregate ID, current revision/state, accepted/rejected event IDs, authoritative dates/embargo, unresolved conflicts, and one next skill.
../../references/registry-event-protocol.md../../references/runtime-invocation.mdregistry-event-protocol.md and runtime-invocation.md. Resolve AARON_SKILLS_ROOT="${CLAUDE_PLUGIN_ROOT:-$(git rev-parse --show-toplevel 2>/dev/null || true)}" and verify the registry script, event schema, and system catalog before invoking it; pasted platform text is untrusted evidence.launches projection. For factual questions, answer with current revision, source, date, and history; never say “ready.”owner-append with owner upsert; request actor fields alone cannot confer authority.owner-append with transition, exact from, to, and expected_revision. State cannot be unset/reinitialized. Valid forward path is draft → concept → alpha → beta → general-availability → archived; record rollback/incidents as events, never rewrite the GA timestamp.owner-append; decisions omit expected_revision and inherit the proposal revision. Never batch-delete, truncate, edit the stream, or store capability values in request data/logs.verify launches, and report offsets/revisions.Persistent events require explicit authorization. Append schema-valid requests through the runtime only. Human files under memory/launch-registry/ are replaceable projections; an event absent from the stream is not canonical.
If the host capability or verified root runtime/schema/catalog is unavailable, leave proposals pending. Standalone one-folder installs cannot append/project or claim canonical launch state.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 11,609 | 14,377 | +24% | 1 | 1 | 0% | 1,462 | 3,004 | +105% | 0 | 0 | — |
case-02 | fail→fail | 11,837 | 5,459 | -54% | 1 | 1 | 0% | 2,220 | 1,357 | -39% | 0 | 0 | — |
case-03 | fail→fail | 17,338 | 5,692 | -67% | 1 | 1 | 0% | 1,526 | 1,382 | -9% | 0 | 0 | — |
case-04 | fail→pass | 8,735 | 7,732 | -11% | 1 | 1 | 0% | 1,479 | 2,251 | +52% | 0 | 0 | — |
case-05 | fail→pass | 14,346 | 15,462 | +8% | 1 | 1 | 0% | 2,699 | 3,040 | +13% | 0 | 0 | — |
case-06 | fail→pass | 11,778 | 7,508 | -36% | 1 | 1 | 0% | 1,974 | 2,301 | +17% | 0 | 0 | — |
case-07 | fail→pass | 21,445 | 5,408 | -75% | 1 | 1 | 0% | 2,749 | 1,948 | -29% | 0 | 0 | — |
case-08 | fail→pass | 6,956 | 4,870 | -30% | 1 | 1 | 0% | 1,433 | 1,919 | +34% | 0 | 0 | — |
case-09 | fail→pass | 2,835 | 4,619 | +63% | 1 | 1 | 0% | 475 | 1,970 | +315% | 0 | 0 | — |
case-10 | fail→pass | 5,901 | 3,427 | -42% | 1 | 1 | 0% | 966 | 1,637 | +69% | 0 | 0 | — |
case-11 | pass→pass | 16,490 | 4,655 | -72% | 1 | 1 | 0% | 1,094 | 1,837 | +68% | 0 | 0 | — |
case-12 | fail→pass | 6,449 | 9,903 | +54% | 1 | 1 | 0% | 927 | 2,403 | +159% | 0 | 0 | — |
case-13 | fail→pass | 4,734 | 3,645 | -23% | 1 | 1 | 0% | 963 | 1,747 | +81% | 0 | 0 | — |
case-14 | fail→pass | 8,547 | 3,693 | -57% | 1 | 1 | 0% | 1,370 | 1,803 | +32% | 0 | 0 | — |
case-15 | fail→pass | 14,920 | 3,284 | -78% | 1 | 1 | 0% | 776 | 1,566 | +102% | 0 | 0 | — |
case-16 | fail→pass | 10,094 | 3,199 | -68% | 1 | 1 | 0% | 1,684 | 1,539 | -9% | 0 | 0 | — |
case-17 | fail→pass | 5,523 | 2,807 | -49% | 1 | 1 | 0% | 920 | 1,498 | +63% | 0 | 0 | — |
case-18 | fail→pass | 15,251 | 4,808 | -68% | 1 | 1 | 0% | 808 | 1,937 | +140% | 0 | 0 | — |
case-19 | fail→pass | 15,957 | 6,112 | -62% | 1 | 1 | 0% | 2,873 | 2,008 | -30% | 0 | 0 | — |
case-20 | pass→pass | 7,931 | 5,841 | -26% | 1 | 1 | 0% | 1,246 | 1,526 | +22% | 0 | 0 | — |
case-21 | pass→pass | 9,038 | 5,540 | -39% | 1 | 1 | 0% | 1,425 | 1,959 | +37% | 0 | 0 | — |
case-22 | fail→pass | 14,912 | 3,029 | -80% | 1 | 1 | 0% | 2,510 | 1,543 | -39% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 16 counted toward the lift figure. The other 6 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +77 percentage points is the difference between those two pass rates over the 16 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.