C

convex-advisor

by @convexv
4.6(120)

Convex デプロイの直近 72 時間の insights イベント(読み取り上限到達、閾値接近、OCC 書き込み競合、恒久的失敗)を読み取り、指摘された関数の実コードまで遡って根本原因を特定し、生のエビデンス付きで性能・コストの所見と修正案を出力する。リリース前の健全性チェックや、本番での読み取り増幅・書き込みホットスポット・コスト超過の切り分けに適し、推測ではなく実行時の事実に基づいた判断を可能にする。

convexobservabilityperformance-optimizationtroubleshootingsreGitHub
インストール方法
npx skills add https://github.com/convex/agent-skills --skill convex-advisor
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Before / After 効果比較

2 组
使用前

読み取り増幅や書き込み競合のアラートが出ても、開発者はログを漁り、どのテーブルが原因か推測して経験でインデックスを直すしかなく、1 回の調査に数時間かかり、コスト異常も定量化されない。

使用後

この Skill はデプロイの直近 72 時間の実 insights イベントを読み、指摘された関数のコードまで遡って根本原因を特定し、生のエビデンスと具体的な修正案を提示するため、調査が数時間から十数分に短縮され、コストリスクもリリース前に可視化される。

SKILL.md

Live-deployment advisor

Static review guesses; the deployment KNOWS. The official Convex MCP ships an insights tool with typed 72h health events per function — documentsReadLimit / bytesReadLimit (hard limit hits), documentsReadThreshold / bytesReadThreshold (approaching), occFailedPermanently / occRetried (write contention) — each carrying evidence (table_name, bytes_read, documents_read, occ document id + retry count). The advisor turns each event into a root-caused finding by reading the flagged function's actual code, and emits findings on the findings bus (specs/finding.schema.json) so fixers can be dispatched and launch-readiness can score.

Workflow

  1. GUARD: run deploy-guard step 0-1 — identify + announce the deployment being read. Reading insights/logs on prod is allowed read-only; never enable mutating prod access for an advisory pass.
  2. GATHER (deterministic, via the official Convex MCP): status → deployment selector; insights → the typed 72h events; tables → schema + row counts; functionSpec → the public/internal surface. The insights tool is only available on cloud dev/prod deployments when logged in as a user (not on previews or deploy-key-scoped contexts) and needs ~72h of traffic; if it returns nothing or is unavailable, say so and fall back to offering convex-reviewer — do NOT invent findings.
  3. ROOT-CAUSE each insight event by reading the flagged function's code:
    • bytesReadThreshold/Limit or documentsReadThreshold/Limit → look for .collect() / unindexed .filter() / missing pagination on the named table; the fix is an index + .withIndex, .take(n), or .paginate (convex-expert patterns), or an aggregate component for counting shapes.
    • occRetried / occFailedPermanently → look for read-modify-write hotspots on the named document (shared counters, status toggles); the fix is @convex-dev/sharded-counter, narrowing the read set, or moving contention to a workpool.
    • repeated failures in logs (status: failure) → classify: crash loop in a cron, validator rejections, unhandled error shapes.
  4. EMIT findings per specs/finding.schema.json: class perf/correctness/cost, severity from the insight kind (limit hits = high, thresholds = med, retried = med, permanent OCC failure = high), locus {kind: deployment, functionId, tableName}, evidence {kind: insight-event, detail: the raw event}, confidence: confirmed (the event happened — it is not a hypothesis), fixCapability + autofixable where the repair is mechanical.
  5. REPORT: findings ranked by severity, each with (a) the runtime evidence in one line ('messages:list read 4.2MB from messages 31× yesterday'), (b) the code-level root cause with file:line, (c) the concrete fix and which capability applies it. Offer to apply fixes; apply only on confirmation, then re-run insights after traffic to verify the trend, or re-run the static check immediately.
  6. Scope discipline: this is a health/perf/cost pass. Route authz findings to convex-authz, code-idiom findings to convex-reviewer, error triage to sentinel — emit a pointer finding rather than duplicating their work.

Rules

  • Evidence-not-vibes: every finding cites a real insight event, log line, or table stat — if the deployment has no evidence, the advisor has no findings (offer convex-reviewer instead).
  • Read-only by construction: an advisory pass never mutates any deployment and never enables prod mutation flags (deploy-guard discipline applies).
  • Root-cause in the code before reporting: an insight event names the symptom; the finding must name the line and the mechanism.
  • Emit on the findings bus (specs/finding.schema.json), confidence: confirmed — runtime events are facts, not hypotheses.
  • Severity from the event kind: limit-hit / permanent-OCC-failure = high; threshold / retried = med.
  • Stay in lane: perf/cost/health only — hand authz to convex-authz, style to convex-reviewer, error triage to sentinel.
  • Prefer component fixes over hand-rolls when they match (sharded-counter for OCC on counters, aggregate for count scans) — same bias as suggest.

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統計データ

インストール数34.9K
評価4.6 / 5.0
バージョン
更新日2026年10月23日
比較事例2 件

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4.6(120)
5
37%
4
43%
3
13%
2
5%
1
2%

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作成2026年10月17日
最終更新2026年10月23日
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