Agent Skillsopenclaw/clawhub › convex-advisor

convex-advisor

GitHub

基于Convex部署72小时运行洞察,自动根因分析性能瓶颈、成本浪费及并发冲突。通过读取代码与运行时证据,生成带修复建议的精准报告,辅助优化应用稳定性与效率。

.agents/skills/convex-advisor/SKILL.md openclaw/clawhub

Trigger Scenarios

需要分析生产环境性能瓶颈 排查数据库读写限制或OCC冲突 获取基于真实数据的性能优化建议

Install

npx skills add openclaw/clawhub --skill convex-advisor -g -y
More Options

Non-standard path

npx skills add https://github.com/openclaw/clawhub/tree/main/.agents/skills/convex-advisor -g -y

Use without installing

npx skills use openclaw/clawhub@convex-advisor

指定 Agent (Claude Code)

npx skills add openclaw/clawhub --skill convex-advisor -a claude-code -g -y

安装 repo 全部 skill

npx skills add openclaw/clawhub --all -g -y

预览 repo 内 skill

npx skills add openclaw/clawhub --list

SKILL.md

Frontmatter
{
    "name": "convex-advisor",
    "description": "Read the Convex deployment's 72h insights (read limits, OCC contention), root-cause each event in code, report evidence-backed perf\/cost findings with fixes."
}

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.

Version History

  • d6a8c68 Current 2026-08-20 02:43

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2026-08-20 02:43

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