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Get Started Free →Explain an existing Convex app — data model + relationships, public vs internal functions, auth/ownership model, components, a request→data flow — read from the schema and function surface. Read-only.
.claude/skills/get-convex-convex-explain-app/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-09 | ✗→✓ | ▲ Improved | 5% | 0% |
| case-15 | ✗→✓ | ▲ Improved | 14% | 0% |
| case-10 | ✓→✗ | ▼ Worse | -39% | 0% |
| case-13 | ✓→✗ | ▼ Worse | -53% | 0% |
| case-17 | ✓→✗ | ▼ Worse | -62% | 0% |
<!-- GENERATED from convex-agents content/capabilities/explain-app.json — do not edit by hand. -->
Before you can safely change an app you have to know what it is — and reading 15 function files top-to-bottom is slow and error-prone. This capability produces the map fast and accurately by reading the two sources that can't lie: the schema (the data model) and the function surface (functionSpec / the exported queries/mutations/actions). It is deliberately DESCRIPTIVE — it explains what IS, hands judgment to the audit capabilities and changes to the fixers. It is also the natural first step of an optimize or self-heal session, and the reusable 're-explain the current architecture' that 'change what you built' depends on.
convex/ directory, schema.ts, and whether a deployment exists (if one does, functionSpec/tables via the official MCP give the authoritative live surface; if not, read the source directly). deploy-guard classifies any deployment read as read-only.schema.ts, list every table with its fields and, crucially, its RELATIONSHIPS — which v.id("other") fields point where, and which indexes exist (indexes reveal the intended access paths). Draw the foreign-key graph in words: 'tasks belong to projects (projectId) and users (ownerId); messages belong to conversations'.@convex-dev/* components installed (convex.config.ts) and what they provide, the HTTP routes (http.ts) and crons, and any external calls in actions (which APIs, which env vars).| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 22,092 | 10,790 | -51% | 1 | 1 | 0% | 3,379 | 1,306 | -61% | 0 | 0 | — |
case-02 | fail→fail | 3,251 | 6,717 | +107% | 1 | 1 | 0% | 358 | 1,203 | +236% | 0 | 0 | — |
case-03 | fail→fail | 30,416 | 4,638 | -85% | 1 | 1 | 0% | 4,611 | 1,364 | -70% | 0 | 0 | — |
case-04 | fail→fail | 8,054 | 18,419 | +129% | 1 | 1 | 0% | 1,070 | 2,914 | +172% | 0 | 0 | — |
case-05 | fail→fail | 18,404 | 4,334 | -76% | 1 | 1 | 0% | 3,606 | 1,449 | -60% | 0 | 0 | — |
case-06 | pass→pass | 9,587 | 4,395 | -54% | 1 | 1 | 0% | 1,604 | 1,412 | -12% | 0 | 0 | — |
case-07 | fail→fail | 10,464 | 3,543 | -66% | 1 | 1 | 0% | 1,624 | 1,376 | -15% | 0 | 0 | — |
case-08 | fail→fail | 11,346 | 4,260 | -62% | 1 | 1 | 0% | 1,927 | 1,373 | -29% | 0 | 0 | — |
case-14 | fail→fail | 9,841 | 5,303 | -46% | 1 | 1 | 0% | 1,341 | 1,513 | +13% | 0 | 0 | — |
case-09 | fail→pass | 12,655 | 8,298 | -34% | 1 | 1 | 0% | 1,883 | 1,968 | +5% | 0 | 0 | — |
case-10 | pass→fail | 12,600 | 4,627 | -63% | 1 | 1 | 0% | 2,235 | 1,366 | -39% | 0 | 0 | — |
case-11 | pass→pass | 12,655 | 8,713 | -31% | 1 | 1 | 0% | 2,488 | 2,157 | -13% | 0 | 0 | — |
case-12 | pass→pass | 17,792 | 11,291 | -37% | 1 | 1 | 0% | 2,841 | 2,512 | -12% | 0 | 0 | — |
case-13 | pass→fail | 19,110 | 9,314 | -51% | 1 | 1 | 0% | 3,590 | 1,695 | -53% | 0 | 0 | — |
case-15 | fail→pass | 16,452 | 7,714 | -53% | 1 | 1 | 0% | 1,690 | 1,930 | +14% | 0 | 0 | — |
case-16 | fail→fail | 26,095 | 3,362 | -87% | 1 | 1 | 0% | 3,741 | 1,262 | -66% | 0 | 0 | — |
case-17 | pass→fail | 23,948 | 4,143 | -83% | 1 | 1 | 0% | 3,608 | 1,383 | -62% | 0 | 0 | — |
case-18 | pass→pass | 20,951 | 17,099 | -18% | 1 | 1 | 0% | 3,445 | 3,627 | +5% | 0 | 0 | — |
case-19 | pass→pass | 14,861 | 7,797 | -48% | 1 | 1 | 0% | 2,027 | 1,977 | -2% | 0 | 0 | — |
case-20 | fail→fail | 8,577 | 10,951 | +28% | 1 | 1 | 0% | 844 | 2,101 | +149% | 0 | 0 | — |
case-21 | pass→fail | 16,764 | 2,847 | -83% | 1 | 1 | 0% | 3,002 | 1,212 | -60% | 0 | 0 | — |
case-22 | pass→fail | 15,184 | 4,396 | -71% | 1 | 1 | 0% | 2,411 | 1,121 | -54% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 21 counted toward the lift figure. The other 1 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of -50 percentage points is the difference between those two pass rates over the 21 comparable cases. 7 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.