One of 30 skills in the get-convex/agent-skills package — works on its own, and pairs well with its siblings.
WHEN YOUR AGENT SHOULD USE IT
USE FOR
- Find the function that reads too much data, and the index that fixes it.
- Track down writes that keep colliding on a shared counter or status field.
- Get a ranked list of findings, each with its evidence, line of code and fix.
- Check again after a fix to see whether the warnings stopped.
DO NOT USE FOR
- A new app with little traffic: the health data needs about 72 hours of use, so it offers a code review instead.
- Security or code-style review: those go to the authorization and code-review skills.
Documents
This is the playbook your agent receives when the skill activates — you don't need to read it to use the skill, but it's here to audit before installing.
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
- 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.
- GATHER (deterministic, via the official Convex MCP):
status→ deployment selector;insights→ the typed 72h events;tables→ schema + row counts;functionSpec→ the public/internal surface. Theinsightstool 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. - 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.
- bytesReadThreshold/Limit or documentsReadThreshold/Limit → look for
- 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.
- 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
insightsafter traffic to verify the trend, or re-run the static check immediately. - 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.
Installation
npx skills add get-convex/agent-skills --skill "convex-advisor" --full-depthRun this in your project — your agent picks the skill up automatically.
BEFORE IT WILL WORK
1 FOR YOU- 01Convex's own MCP server, signed in as you
Connect the official Convex MCP server, signed in as yourself. Its health data covers cloud development and production deployments, not preview deployments or deploy-key sessions.
License
Licensed under Apache-2.0— you can use, modify, and redistribute it under that license's terms.
View the full license file on GitHub →