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Get Started Free →Run every Convex audit (authz, reviewer, advisor, insights) into one scored, deduped readiness report with an ordered fix plan — Lighthouse for your backend.
.claude/skills/get-convex-convex-launch-readiness/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-18 | ✗→✓ | ▲ Improved | 11% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 13% | 0% |
| case-06 | ✗→✓ | ▲ Improved | -1% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 38% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 8% | 0% |
<!-- GENERATED from convex-agents content/capabilities/launch-readiness.json — do not edit by hand. -->
Readiness is not one check — it's the union of the checks, deduped, ranked, and scored. This capability is pure composition over the findings bus (specs/finding.schema.json): it runs each audit capability, normalizes their outputs into one report (specs/finding-report.schema.json), computes an auditable score, and — because every finding names a fixCapability — hands the user a prioritized, actionable punch list instead of four separate reports. It fixes nothing itself; it decides WHAT to fix and in what order, then dispatches to the fixers.
Run independent passes concurrently; each returns findings, not fixes.
identity field to a normalized function/table key (e.g. messages:list) that is the SAME whether the pass reported a code-locus or a deployment-locus for that function — so the SAME defect seen from two loci (reviewer flags a missing index at code-locus, advisor flags its read-limit symptom at deployment-locus) collapses to ONE via the bus's (class, identity) dedup and isn't double-counted in the score. Keep the higher-confidence source. Drop nothing silently; a pass that errored/was skipped is a stated coverage gap, not a clean result.| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-13 | pass→pass | 14,763 | 5,841 | -60% | 1 | 1 | 0% | 1,894 | 1,855 | -2% | 0 | 0 | — |
case-18 | fail→pass | 14,581 | 8,702 | -40% | 1 | 1 | 0% | 2,129 | 2,355 | +11% | 0 | 0 | — |
case-01 | fail→fail | 40,965 | 9,910 | -76% | 1 | 1 | 0% | 6,209 | 1,638 | -74% | 0 | 0 | — |
case-02 | fail→fail | 3,644 | 9,246 | +154% | 1 | 1 | 0% | 421 | 1,865 | +343% | 0 | 0 | — |
case-03 | fail→fail | 4,273 | 6,558 | +53% | 1 | 1 | 0% | 319 | 1,773 | +456% | 0 | 0 | — |
case-04 | pass→fail | 10,642 | 8,224 | -23% | 1 | 1 | 0% | 1,687 | 2,392 | +42% | 0 | 0 | — |
case-05 | fail→pass | 15,394 | 7,515 | -51% | 1 | 1 | 0% | 2,205 | 2,483 | +13% | 0 | 0 | — |
case-06 | fail→pass | 16,676 | 9,193 | -45% | 1 | 1 | 0% | 2,376 | 2,361 | -1% | 0 | 0 | — |
case-12 | fail→fail | 9,790 | 5,661 | -42% | 1 | 1 | 0% | 1,223 | 1,851 | +51% | 0 | 0 | — |
case-07 | pass→pass | 7,402 | 4,317 | -42% | 1 | 1 | 0% | 1,236 | 1,883 | +52% | 0 | 0 | — |
case-08 | fail→pass | 10,762 | 5,737 | -47% | 1 | 1 | 0% | 1,394 | 1,930 | +38% | 0 | 0 | — |
case-09 | fail→fail | 12,431 | 6,562 | -47% | 1 | 1 | 0% | 1,765 | 1,988 | +13% | 0 | 0 | — |
case-10 | fail→fail | 14,142 | 5,112 | -64% | 1 | 1 | 0% | 1,864 | 1,821 | -2% | 0 | 0 | — |
case-11 | fail→pass | 8,888 | 3,180 | -64% | 1 | 1 | 0% | 1,382 | 1,490 | +8% | 0 | 0 | — |
case-14 | fail→pass | 19,604 | 7,953 | -59% | 1 | 1 | 0% | 2,600 | 2,111 | -19% | 0 | 0 | — |
case-15 | fail→pass | 21,007 | 2,861 | -86% | 1 | 1 | 0% | 2,789 | 1,557 | -44% | 0 | 0 | — |
case-16 | fail→pass | 14,243 | 12,477 | -12% | 1 | 1 | 0% | 2,250 | 2,704 | +20% | 0 | 0 | — |
case-17 | fail→fail | 11,610 | 5,491 | -53% | 1 | 1 | 0% | 1,896 | 1,906 | +1% | 0 | 0 | — |
case-19 | fail→pass | 16,207 | 3,052 | -81% | 1 | 1 | 0% | 2,655 | 1,566 | -41% | 0 | 0 | — |
case-20 | pass→pass | 13,157 | 9,115 | -31% | 1 | 1 | 0% | 2,205 | 2,385 | +8% | 0 | 0 | — |
case-21 | fail→fail | 12,426 | 7,299 | -41% | 1 | 1 | 0% | 1,920 | 2,057 | +7% | 0 | 0 | — |
case-22 | pass→pass | 9,547 | 11,145 | +17% | 1 | 1 | 0% | 1,687 | 2,765 | +64% | 0 | 0 | — |
case-23 | fail→fail | 22,548 | 12,174 | -46% | 1 | 1 | 0% | 3,318 | 2,742 | -17% | 0 | 0 | — |
case-24 | fail→fail | 29,697 | 39,649 | +34% | 1 | 1 | 0% | 5,086 | 7,367 | +45% | 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. 24 cases were attempted, and 22 counted toward the lift figure. The other 2 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 +33 percentage points is the difference between those two pass rates over the 22 comparable cases. 2 cases got worse with the skill loaded, and they are 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.