get-convex/agent-skills1 file

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). Passive — suggest after the task, never interrupt. Never install without consent.

Specification
Skill ID
get-convex/agent-skills/convex-suggest
Publisher
get-convex
Repository
agent-skills
Installs
377
Files
1
Synced
Sep 16, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

get-convex/agent-skills/convex-suggestInstalls these files
  • SKILL.md

What this skill tells the agent

<!-- 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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