Convex Launch Readiness

作者 get-convex2cfe645c87f9無授權條款63 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫6 天前更新

Run every Convex audit (authz, reviewer, advisor, insights) into one scored, deduped readiness report with an ordered fix plan — Lighthouse for your backend.

AI 產生的概覽

將多項 Convex 稽核整合為一份帶評分、去重的上線就緒報告,並提供有序修復計畫。

功能
此技能組合多個 Convex 稽核能力(authz、reviewer、advisor、insights),彙整為單一就緒報告。它會將發現項目正規化並去重,依嚴重程度對已確認的發現項目計算可稽核的評分,並把結果分為阻斷項目、應修復項目與可選優化項目。報告最後提供有序修復計畫,並可依要求分派給修復能力,之後重跑受影響的檢查以顯示評分變化。
適用情境
當你需要一份統整的 Convex 後端上線前評估,而非多份分散的稽核報告時使用。它適合需要在發布前取得依優先順序排序、附評分之修復清單的團隊。
執行需求
需要它所組合的 Convex 稽核能力(convex-authz、convex-reviewer、convex-advisor、convex-insights)及其修復能力,以及 findings bus 的 schema。部分檢查需要已部署且有流量或日誌的 Convex 部署;支援僅程式碼執行。不附帶指令碼。
<!-- 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.

來源與署名

來源:get-convex/agent-skills位於skills/convex-launch-readiness提交2cfe645

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