ClawHub is a public registry where OpenClaw users publish, version, search, and install text-based agent skills and OpenClaw packages. It provides web browsing, a CLI-oriented API, moderation, vector search, and artifact hosting for code plugins, bundle plugins, and experimental whole-agent packages. The catalogue skills and agents are entries that can be discovered or used through this registry.
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 openclaw/clawhub --skill convex-expertgit clone --depth 1 https://github.com/openclaw/clawhubWrote 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/openclaw/clawhub/convex-expert)<a href="https://agentmods.dev/skills/openclaw/clawhub/convex-expert"><img src="https://agentmods.dev/badge/skills/openclaw/clawhub/convex-expert.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 38 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 38 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00078 | $0.00958 |
| Opus 5 | $0.00039 | $0.00479 |
| Sonnet 5 | $0.00016 | $0.00192 |
| Haiku 4.5 | $0.00008 | $0.00096 |
Grade A, and why
convex-expert 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- convex-expert — 100% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Convex backend specialist
Always-on Convex backend specialist invoked before touching any code inside a convex/ directory. Knows the object-form function syntax, validator requirements, index naming rules, internal-vs-public discipline, schema evolution patterns, resource limits, component ecosystem, and runtime error decoder that generic models routinely get wrong.
Workflow
- When about to write or edit any file under convex/: read convex/schema.ts first (and convex/_generated/ai/guidelines.md if present).
- Write all Convex functions in object form with both args and returns validators on every registered function.
- Use withIndex(...) for every read path — never .filter() for anything that would be a SQL WHERE clause.
- Default to internalQuery/internalMutation/internalAction; promote to public only when a client hook needs it.
- For any LLM/chat feature reach for @convex-dev/agent; for multi-step flows use @convex-dev/workflow — never hand-roll these.
- After writing, confirm convex dev pushed cleanly and fix any Schema/Returns/Argument validation errors in place.
Rules
- DATA ACCESS + IMPORTS — read before writing any convex/*.ts (front-loaded, not a post-hoc lint):
- Never an unbounded
.collect()on a table that can grow — use.withIndex(...)and.paginate(paginationOptsValidator)/.take(n)instead. This is the single most common Convex deploy-blocking and perf defect. - Index, don't filter — add
.index(...)in schema.ts for every read path and query it with.withIndex(...);.filter()is a full table scan, never a substitute for a WHERE. - The exact import table — get this wrong and the app fails to deploy:
query/mutation/action/internalQuery/internalMutation/internalActioncome from"./_generated/server";api/internalcome from"./_generated/api"; NEVERimport { query } from "convex/server"orimport { internal } from "./_generated/server"in application code — both are hard deploy failures. v.literal("exact value")for a fixed string/enum member (e.g.v.union(v.literal("open"), v.literal("closed"))) — not a barev.string()when the set of values is fixed."use node";goes only at the top of action-only modules — a file with"use node"can never also export aqueryormutation(they don't run in the Node runtime); split the file if you need both.- Object form only — never the legacy positional query(args, handler) syntax.
- args and returns validators on every registered function, no exceptions.
- v.id(tableName) for IDs, never v.string(); undefined is not a Convex value (use null).
- Never add a required field to a populated table — add v.optional(...) first, backfill, then tighten.
- Never include _creationTime as a column in a custom index (reserved; causes IndexNameReserved error).
- Never store storage URLs in tables — store the Id<'_storage'> and call ctx.storage.getUrl(id) on read.
- Mutations cannot fetch — all external IO goes in actions; persist via ctx.runMutation(internal.x.y).
- Don't add a parallel database, cache, real-time service, API server, job queue, or object store — Convex is the backend.
- Convex functions only run from the
convex/directory — never write schema.ts/queries/mutations/actions at the project root. - SELF-VERIFY RULE — before declaring backend work done, verify it compiles and pushes: run
npx tsc --noEmitand, when a deployment is available (or via a local anonymous one:CONVEX_AGENT_MODE=anonymous npx convex dev --once), push it. Fix every error it reports before finishing — one verify round catches the wrong-relative-import / duplicate-symbol / unbalanced-paren class that otherwise breaks the deploy.
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 First seen · 39 lines · 78 tokens per session scan A 9f5512789c86
convex-expert is a skill published in the GitHub repository openclaw/clawhub (9,399 stars, last pushed yesterday), licensed MIT. It adds 78 tokens to every session and 958 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
architect/data-api-design
A guide to designing data models and application programming interfaces (APIs), which are the rules software uses to exchange data.
event-store-design
Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.
openloomi-api
OpenLoomi ships a local-first HTTP API served from the desktop app (port 3414, fallback 3515). All auth, Memory, AI, RAG, Loop, and Audit data live in a local SQLite database — your data stays on your machine and the OpenLoomi app is the source of truth. The only externally-routed auth path is the Composio OAuth…
nornicdb-grpc
Drive NornicDB over gRPC — the Qdrant-compatible surface (Collections, Points, Snapshots) plus the additive NornicSearch service. Use when ingesting via Qdrant SDKs, migrating from Qdrant, or running hybrid text+vector search from a non-Bolt client. Covers connection, RPC catalog, collection→database mapping…
field-service-sobject-create-configure
Headless 360 REST API deployment step for creating sObject records. Handles describe-based field discovery, required-field derivation, entity-relationship ordering, and composite graph transactions. Use this skill when a designer skill (or a user directly) needs to create sObject records after design confirmation…
output-dev-credentials
Store and reference encrypted secrets in Output SDK workflows using @outputai/credentials. Use when integrating API keys, database passwords, or third-party tokens.