convex/agent-skills

convex-suggest

Suggest the matching Convex component when the user hand-rolls a pattern it already solves (crons, sharded-counter, rate-limiter, storage, search, presence, workflow, RAG, prosemirror-sync).

View source

How to use

  1. Copy the installation command and review the source package before installing it in your own agent environment.
  2. Check the source document for required tools, credentials and supported hosts.
  3. Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/convex/agent-skills --skill convex-suggest

Before you start

  • Installation does not include a model subscription, API allowance or permission to access your files.
  • Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document

Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.

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

Proactively suggest the right Convex component

When you see code or intent that duplicates what a Convex component already does, surface a targeted suggestion: ONE component, WHY (anchored in the user's own code or ask), and a concrete install hint. Never install without explicit consent. Never suggest more than one component at a time unless the user asks.

Workflow

  1. Observe the codeSnippets and userAsk passively — never block the current task to suggest.
  2. Match against the detector rules (see generators/suggest-detector.mjs): email/SMTP → resend; push notifications → expo-push; setInterval/cron → @convex-dev/crons; shared counter increments → @convex-dev/sharded-counter; .collect().length scans → @convex-dev/aggregate; multi-step/long-running actions → @convex-dev/workflow; bounded concurrency → @convex-dev/workpool; rate-limit counters in DB → @convex-dev/rate-limiter; fs.write/S3 uploads → Convex Storage; Elasticsearch/Algolia → built-in full-text search; presence/typing → @convex-dev/presence; Pinecone/external vector DB → @convex-dev/rag; collaborative editing → @convex-dev/prosemirror-sync.
  3. After finishing the current task, offer ONE suggestion: name the component, quote the specific code or phrase that triggered it, explain why the component fits better.
  4. If the user says yes: run /add <component> or follow the installHint from the detector.
  5. If the user says no or ignores it: drop it. Do not repeat the same suggestion.

Rules

  • Passive — never interrupt the current task; surface the suggestion AFTER completing what the user asked.
  • One at a time — pick the highest-priority match; do not dump a list of five components.
  • Cite WHY from the user's own code or ask — 'I noticed you wrote post.likes + 1 in a mutation that many users call concurrently; that causes OCC conflicts at scale.'
  • Never install without explicit consent — suggest, explain, wait for a yes.
  • Do not suggest a component the user has already installed.
  • Do not fire on generic coding questions unrelated to Convex (sorting arrays, writing CSS, etc.).

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