Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sutchan/Agent-Skills-Hub --skill convex-suggestgit clone --depth 1 https://github.com/sutchan/Agent-Skills-HubWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sutchan/agent-skills-hub/convex-suggest)<a href="https://agentmods.dev/skills/sutchan/agent-skills-hub/convex-suggest"><img src="https://agentmods.dev/badge/skills/sutchan/agent-skills-hub/convex-suggest/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sutchan/agent-skills-hub/convex-suggest"><img src="https://agentmods.dev/badge/skills/sutchan/agent-skills-hub/convex-suggest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.00646 |
| Opus 5.5 | $0.00028 | $0.00258 |
| Sonnet 5.5 | $0.00014 | $0.00129 |
| Haiku 4.5 | $0.00007 | $0.00065 |
Grade A, and why
convex-suggest scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
89% identical to convex-suggest — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 32 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- Observe the codeSnippets and userAsk passively — never block the current task to suggest.
- 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.
- 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.
- If the user says yes: run
/add <component>or follow the installHint from the detector. - 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 + 1in 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.).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago Changed · -1 lines bfcdae6b7291
- 14d ago First seen · 33 lines · 70 tokens per session scan A 68ad8d8804b9
convex-suggest is a skill published in the GitHub repository sutchan/Agent-Skills-Hub (2 stars, last pushed 3d ago), licensed MIT. It adds 70 tokens to every session and 646 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to convex-suggest, differing in 8 lines, and is treated as a copy.
Other skills, from other repositories
search-engine-expert
Expert guide for full-text search engines (Typesense, Meilisearch, Elasticsearch), faceted search, and autocomplete / Panduan ahli mesin pencarian full-text (Typesense, Meilisearch, Elasticsearch), pencarian berfaset, dan autocomplete.
backend-patterns
Guides backend service architecture — layering, N+1 query prevention, caching, retries, rate limiting, and background job processing, in Go primarily and TypeScript/PHP where the pattern is language-agnostic. Use when structuring handler/service/repository layers, reviewing a service for N+1 queries, adding a cache in…
golang-database
This skill should be used when the user asks to "configure a Go database connection pool", "use database/sql in Go", "set up pgxpool", "why is my Go app running out of connections", "scan rows into a Go struct", "handle sql.ErrNoRows", or writes Go code that opens, pools, queries, or scans a PostgreSQL/MySQL…
supabase
Use when doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies…
k2
Build and troubleshoot Cloudflare K2 or K2 Streams durable logs. Use for stream setup, producing from Workers or HTTP, configuring retention and inputs, and consuming through subscriptions.
spring-data-neo4j
Provides Spring Data Neo4j integration patterns for Spring Boot applications. Use when you need to work with a graph database, Neo4j nodes and relationships, Cypher queries, or Spring Data Neo4j. Creates node entities with @Node annotation, defines relationships with @Relationship, writes Cypher queries using @Query…