# Convex Launch Readiness

> Ejecuta todas las auditorías de Convex (authz, reviewer, advisor, insights) en un único reporte puntuado y deduplicado, con un plan de arreglo ordenado — como Lighthouse para tu backend.

Fuente: https://skillsagentes.com/skills/get-convex/agent-skills/convex-launch-readiness
Markdown: https://skillsagentes.com/skills/get-convex/agent-skills/convex-launch-readiness.md

Repositorio: https://github.com/get-convex/agent-skills
Autor: get-convex
Licencia: Apache-2.0
Actualizado: el mes pasado
Coste de contexto: 40 tok instalada, 1.2k tok al activarse, 1.2k tok con todos los archivos del bundle
Bundle: 1 archivo, 5 KB
Permisos que pide: ninguno declarado

## Instalación

Un skill son archivos markdown: los mismos archivos valen para cualquier agente y lo único que cambia es el directorio de destino, es decir la bandera `--agent`. Añade `-g` para instalarlo en todos los proyectos de la máquina.

```bash
# Claude Code
npx -y skills add get-convex/agent-skills --skill convex-launch-readiness --agent claude-code
# Cursor
npx -y skills add get-convex/agent-skills --skill convex-launch-readiness --agent cursor
# Codex
npx -y skills add get-convex/agent-skills --skill convex-launch-readiness --agent codex
# Gemini CLI
npx -y skills add get-convex/agent-skills --skill convex-launch-readiness --agent gemini
# Windsurf
npx -y skills add get-convex/agent-skills --skill convex-launch-readiness --agent windsurf
# Cline
npx -y skills add get-convex/agent-skills --skill convex-launch-readiness --agent cline
```

## Qué hace

- Ejecuta convex-authz, convex-reviewer, convex-advisor y convex-insights y fusiona sus findings en un único reporte normalizado
- Deduplica findings que representan el mismo defecto visto desde locus de código o de deployment, usando una identidad function/table normalizada
- Calcula un score auditable partiendo de 100, restando por severidad de findings CONFIRMED, con la fórmula impresa
- Ordena los findings en blockers/should-fix/nice-to-have y entrega un plan de arreglo ordenado con la fixCapability de cada uno
- Al pedirlo, despacha las fixCapabilities correspondientes y luego re-ejecuta los passes afectados para mostrar el delta de score

## Cuándo usarla

- Se quiere un reporte único de disponibilidad para lanzamiento en vez de cuatro reportes de auditoría separados
- Se necesita saber qué arreglar primero en un backend Convex antes de producción
- Se quiere verificar si un fix realmente movió el número de readiness

## Qué la activa

- "Dame un reporte de launch-readiness de mi proyecto Convex"
- "¿Qué debería arreglar primero antes de salir a producción?"
- "Corre todas las auditorías de Convex y dame un score único"

## Antes de instalar

- Requiere un directorio convex/ para las pasadas de código; convex-advisor y convex-insights solo corren si existe un deployment con tráfico o logs.

## Archivos

- SKILL.md — 5 KB

## SKILL.md

Reproducido tal cual desde get-convex/agent-skills bajo Apache-2.0. Esta sección es el documento original y está en inglés.

<!-- GENERATED from convex-agents content/capabilities/launch-readiness.json — do not edit by hand. -->

# Launch-readiness report

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.

## Workflow

1. GUARD + SCOPE: deploy-guard classifies the target (local-anonymous / dev / preview / prod); announce it. Detect what's assessable — is there a convex/ dir, a deployed deployment with traffic, an auth foundation? Skip passes whose preconditions aren't met and SAY which were skipped (a skipped pass is not a pass).
2. RUN THE PASSES, each emitting findings on the bus:
   - convex-authz — the authz scan (identity-from-arg, missing ownership, PII leak, parent-ref-on-write). Always runnable on code.
   - convex-reviewer — validators, indexes-not-filter, idiom, error handling. Always runnable on code.
   - convex-advisor — live read-limit / OCC evidence (only if a deployment with traffic exists; else record 'skipped: no traffic').
   - convex-insights — recent failures from logs (only if a deployment exists).
   Run independent passes concurrently; each returns findings, not fixes.
3. NORMALIZE + DEDUPE: collect all findings into one report. Set each finding's `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.
4. SCORE, auditable: start at 100; subtract per CONFIRMED finding by severity (high −15, med −5, low −1), floor at 0; print the exact formula and the per-class breakdown so the number is reproducible, not a vibe. plausible-only findings are listed as candidates but do NOT move the score (evidence-not-vibes). A deployment/traffic-less run reports a code-only score and says so.
5. REPORT: the score, then findings ranked by severity, each with its evidence, its locus, and the fixCapability + a one-line fix note. Group by 'blockers' (high) / 'should-fix' (med) / 'nice-to-have' (low). End with the ordered fix plan: which capability to run next, in what order (authz/data-loss first, then perf/scale, then idiom/observability).
6. DISPATCH on request: for each finding the user accepts, invoke its fixCapability (convex-authz, convex-reviewer's fixers, migrate-rehearse for schema changes, suggest for component swaps). After fixes, RE-RUN the affected passes and show the score delta — the readiness number is only meaningful if it moves when you fix things.
7. Never claim more coverage than was run: the report header lists which passes ran, which were skipped and why. A green score on a code-only run is 'code looks ready', not 'production-verified'.

## Rules

- Compose, don't re-implement: run the existing audit capabilities and aggregate their bus findings — never re-derive an authz or perf check inline.
- The score counts CONFIRMED findings only, by severity, with the formula printed; plausible findings are candidates that don't move the number.
- Normalize each finding's locus to a function/table identity before dedup (map deployment functionId ↔ code file:line) so one defect seen from two loci collapses to one and isn't double-scored; keep the higher-confidence source; drop nothing silently.
- Every finding carries its fixCapability; the report ends with an ORDERED fix plan (data-loss/authz first, then scale, then idiom/observability).
- Re-run affected passes after fixes and show the score delta — a readiness number that doesn't move when you fix things is theater.
- Never claim more than was run: header lists ran/skipped passes; a code-only run yields a code-only score, explicitly labeled.
- This is a read + aggregate + dispatch pass; fixes happen in the fixer capabilities, gated by their own consent/deploy-target rules.

## Dónde encaja

- Categoría: [Testing y QA](https://skillsagentes.com/categorias/testing-qa.md) — Flujos de testing unitario, de integración y end-to-end.
- Creador: [get-convex](https://skillsagentes.com/creators/get-convex.md) — 33 skills en el directorio
- [Todas las skills](https://skillsagentes.com/skills.md)
- [Ranking de instalaciones](https://skillsagentes.com/ranking.md)

## Otras skills del mismo repositorio

- [Convex Quickstart](https://skillsagentes.com/skills/get-convex/agent-skills/convex-quickstart.md): Levanta un template Next.js + Convex barebones a partir de una idea en una frase.
- [Convex Design](https://skillsagentes.com/skills/get-convex/agent-skills/convex-design.md): Diseña y construye backends reactivos y type-safe de nivel producción en Convex: schema, queries/mutations/actions, índices, auth, storage, scheduling, multiplayer en tiempo real y workflows LLM/agentes.
- [Convex Authz](https://skillsagentes.com/skills/get-convex/agent-skills/convex-authz.md): Audita y refuerza la autorización de una app Convex: impersonación por identity-from-arg, checks de ownership por documento faltantes, queries públicas que filtran datos por un id del cliente y escrituras en un contenedor ajeno.
- [Convex Expert](https://skillsagentes.com/skills/get-convex/agent-skills/convex-expert.md): Especialista en el backend de Convex: código dentro de convex/ (funciones, schemas, índices, queries, mutations, actions, endpoints HTTP, cron jobs, storage, auth y componentes).
- [Convex Agent](https://skillsagentes.com/skills/get-convex/agent-skills/convex-agent.md): Añade un backend de agente de IA / RAG (@convex-dev/agent) a la app Convex.

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