Convex Agents
waynesutton/builder-skills
Builds AI agents on the Convex agent component: threads, messages, tools that call queries and mutations, streaming, RAG with vector search, and workflows for multi step jobs.
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).
Install Convex Suggest
$ npx skills add openclaw/clawhub --skill convex-suggest -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install openclaw/clawhub convex-suggest --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/openclaw/clawhub.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/convex-suggest .claude/skills/convex-suggest && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "convex-suggest" agent skill from https://github.com/openclaw/clawhub/tree/main/.agents/skills/convex-suggest into .claude/skills/convex-suggest/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "convex-suggest", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/openclaw/clawhub/tree/main/.agents/skills/convex-suggestType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add openclaw/clawhub --skill convex-suggest -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install openclaw/clawhub convex-suggest --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openclaw/clawhub.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/convex-suggest .agents/skills/convex-suggest && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "convex-suggest" agent skill from https://github.com/openclaw/clawhub/tree/main/.agents/skills/convex-suggest into .agents/skills/convex-suggest/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "convex-suggest", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add openclaw/clawhub --skill convex-suggest -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install openclaw/clawhub convex-suggest --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openclaw/clawhub.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/convex-suggest .cursor/skills/convex-suggest && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "convex-suggest" agent skill from https://github.com/openclaw/clawhub/tree/main/.agents/skills/convex-suggest into .cursor/skills/convex-suggest/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "convex-suggest", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/openclaw/clawhub.git --path .agents/skills/convex-suggest--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add openclaw/clawhub --skill convex-suggest -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install openclaw/clawhub convex-suggest --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openclaw/clawhub.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/convex-suggest .gemini/skills/convex-suggest && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "convex-suggest" agent skill from https://github.com/openclaw/clawhub/tree/main/.agents/skills/convex-suggest into .gemini/skills/convex-suggest/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "convex-suggest", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install openclaw/clawhub convex-suggestInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add openclaw/clawhub --skill convex-suggest -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/openclaw/clawhub.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/convex-suggest .github/skills/convex-suggest && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "convex-suggest" agent skill from https://github.com/openclaw/clawhub/tree/main/.agents/skills/convex-suggest into .github/skills/convex-suggest/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "convex-suggest", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add openclaw/clawhub --skill convex-suggest -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install openclaw/clawhub convex-suggest --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openclaw/clawhub.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/convex-suggest .opencode/skills/convex-suggest && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "convex-suggest" agent skill from https://github.com/openclaw/clawhub/tree/main/.agents/skills/convex-suggest into .opencode/skills/convex-suggest/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "convex-suggest", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
convex-suggest- GitHub stars
- 9.5k
- Used in
- 1 other repo
- Token cost
- ~625 tokens
- SKILL.md length
- 280 words
- Files
- 1
- Skills in repo
- 55
- Repo updated
- First seen
- Licence
- MIT
At a glance
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).
- Works in 5 steps: Observe the codeSnippets and userAsk… → Match against the detector rules (see… → After finishing the current task, offer… → …
- Hand-rolls a pattern it already solves (crons
- SKILL.md covers Workflow and Rules
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Convex Suggest is an agent skill from openclaw/clawhub. 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.
Its SKILL.md is about 630 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering Scheduled and recurring tasks and Retrieval-augmented generation. It works with Convex. The repository describes itself as: Skill + Plugin Registry for OpenClaw. The licence is MIT.
When your agent uses it
- Hand-rolls a pattern it already solves (crons
- Sharded-counter
- Prosemirror-sync)
Example prompts
- “/convex-suggest”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- 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…
- After finishing the current task, offer ONE suggestion: name the component, quote the specific code or phrase that triggered it, explain…
- If the user says yes: run /add or follow the installHint from the detector.
- If the user says no or ignores it: drop it. Do not repeat the same suggestion.
What it can do on your machine
Read from SKILL.md and the folder at commit d044664. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Convex Suggest loads about 625 tokens when it runs. Until then it costs about 72 tokens; SKILL.md has 280 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from openclaw/clawhub at commit d044664, republished under its MIT licence (© openclaw). 280 words, ~625 tokens.
Download SKILL.mdSave it as
.claude/skills/convex-suggest/SKILL.md (or your agent's skills folder).- name
- convex-suggest
- description
- 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.
<!-- 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
- 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.).
© openclaw, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .agents/skills/convex-suggest of openclaw/clawhub.
Open the folder on GitHubat commit d044664
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in openclaw/clawhub, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Convex Suggest next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Convex Suggest this skillopenclaw/clawhub | 9.5k | 1 repos | ~625 | Automated safety check: Pass | MIT | |
| Convex Agentswaynesutton/builder-skills | 406 | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Hybrid Search Implementationwshobson/agents | 40k | 9 repos | ~497 | Automated safety check: Pass | MIT | |
| Chroma Vector DatabaseOrchestra-Research/AI-Research-SKILLs | 13k | 7 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Embeddings via 9Routerdecolua/9router | 30k | — | ~604 | Automated safety check: Pass | MIT | |
| Tavily Search API Integrationandrewyng/context-hub | 14k | — | ~1.1k | Automated safety check: Pass | MIT |
Similar skills
Hybrid Search Implementation
wshobson/agents
Shows how to run vector and keyword search side by side and merge their results, so retrieval catches both meaning and exact terms in RAG and search systems.
Chroma Vector Database
Orchestra-Research/AI-Research-SKILLs
Shows how to store documents and embeddings in Chroma, query them by similarity with metadata filters, and persist them to disk for RAG and semantic search projects.
Embeddings via 9Router
decolua/9router
Generates vector embeddings through the 9Router /v1/embeddings endpoint, using models from providers such as OpenAI, Gemini, Mistral and Voyage for RAG and semantic search.
Tavily Search API Integration
andrewyng/context-hub
Guides building Tavily integrations for web search, URL extraction, site crawling and AI-assisted research in Python or JavaScript agent and RAG projects.
AI SDK Development
trypostit/trypost
TRIGGER when working with ai-sdk which is Laravel official first-party AI SDK.
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Related
Works with
Questions about Convex Suggest
What does Convex Suggest do?
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). Convex Suggest is an agent skill from openclaw/clawhub. 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).
When should I use Convex Suggest?
Convex Suggest fits situations like: hand-rolls a pattern it already solves (crons; sharded-counter; prosemirror-sync).
How do I install Convex Suggest in Claude Code?
Run `npx skills add openclaw/clawhub --skill convex-suggest -a claude-code`. Or copy the skill folder (.agents/skills/convex-suggest in openclaw/clawhub) into .claude/skills/convex-suggest in your project. Claude Code loads it when a task matches its description.
How do I install Convex Suggest in Codex?
Run `npx skills add openclaw/clawhub --skill convex-suggest -a codex`. Or copy the skill folder (.agents/skills/convex-suggest in openclaw/clawhub) into .agents/skills/convex-suggest in your project. Codex loads it when a task matches its description.
Can I use Convex Suggest in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add openclaw/clawhub --skill convex-suggest -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/convex-suggest, .gemini/skills/convex-suggest, .github/skills/convex-suggest and .opencode/skills/convex-suggest in your project.
What does Convex Suggest need to run?
SKILL.md names no scripts, command-line tools or credentials: Convex Suggest is instructions for the agent only.
Does Convex Suggest access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Convex Suggest safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Convex Suggest use?
Convex Suggest is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Convex Suggest use?
About 625 tokens (SKILL.md is roughly 2.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Convex Suggest?
Skills that share tags, products or a category with Convex Suggest: Convex Agents (waynesutton/builder-skills, 406 stars), Hybrid Search Implementation (wshobson/agents, 40k stars), Chroma Vector Database (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Embeddings via 9Router (decolua/9router, 30k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Convex Suggest?
openclaw (a GitHub organization) maintains it in openclaw/clawhub, which has 9,500 GitHub stars. The repository holds 55 skills in this directory. The repository was last updated on October 8, 2026.
Source: openclaw/clawhub on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.