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Skills/get-convex/agent-skills/convex-advisor
convex-advisor logo

convex-advisor

get-convex/agent-skills
963 installs42 stars
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Installation

npx skills add https://github.com/get-convex/agent-skills --skill convex-advisor

Summary

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.

SKILL.md

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

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.
  1. 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.
  2. 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.
  3. 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.

Score

0–100
63/ 100

Grade

C

Popularity15/30

963 installs — growing adoption.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Convex Advisor skill score badge previewScore badge

Markdown

[![Convex Advisor skill](https://www.claudemarket.ai/skills/get-convex/agent-skills/convex-advisor/badges/score.svg)](https://www.claudemarket.ai/skills/get-convex/agent-skills/convex-advisor)

HTML

<a href="https://www.claudemarket.ai/skills/get-convex/agent-skills/convex-advisor"><img src="https://www.claudemarket.ai/skills/get-convex/agent-skills/convex-advisor/badges/score.svg" alt="Convex Advisor skill"/></a>

Convex Advisor FAQ

How do I install the Convex Advisor skill?

Run “npx skills add https://github.com/get-convex/agent-skills --skill convex-advisor” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Convex Advisor skill do?

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. The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Convex Advisor skill free?

Yes. Convex Advisor is a free, open-source skill published from get-convex/agent-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Convex Advisor work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Convex Advisor works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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