convex-verify

convex-verify is a skill for Claude Code, Codex from openclaw/clawhub. It costs 42 tokens per session (1,115 once invoked), scanned A, original, MIT.

A test workflow for Convex features, where queries, mutations, and actions handle application data and operations. It seeds test data, runs the feature as different users, and checks both allowed and refused actions in memory.

In plain words
What is it for?
Use it to verify who may call a Convex operation, which records it returns, what changes a mutation makes, and whether another user is correctly blocked.
Why use it?
A successful type check only proves that code is written correctly; it does not prove that users see the right data or that unauthorized users are denied. This workflow specifically checks those real behavior and access rules.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to verify who may call a Convex operation, which records it returns, what changes a mutation makes, and whether another user is correctly blocked.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/openclaw/clawhub/convex-verify
About the project

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.

openclaw/clawhub · 9,547 stars · on GitHub · clawhub.ai

Install

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.

Any agent
npx skills add openclaw/clawhub --skill convex-verify
Clone the repo
git clone --depth 1 https://github.com/openclaw/clawhub

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for convex-verify

README.md
[![agentmods](https://agentmods.dev/badge/skills/openclaw/clawhub/convex-verify/github.svg)](https://agentmods.dev/skills/openclaw/clawhub/convex-verify)
Your own site
<a href="https://agentmods.dev/skills/openclaw/clawhub/convex-verify"><img src="https://agentmods.dev/badge/skills/openclaw/clawhub/convex-verify/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.

agentmods 80×15 button for convex-verify

Your own site · 80×15
<a href="https://agentmods.dev/skills/openclaw/clawhub/convex-verify"><img src="https://agentmods.dev/badge/skills/openclaw/clawhub/convex-verify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,115 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, 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 22
    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]
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00042 $0.01115
Opus 5.5 $0.00017 $0.00446
Sonnet 5.5 $0.00008 $0.00223
Haiku 4.5 $0.00004 $0.00112

Measured 2mo ago against content hash b7aff41a73c0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

convex-verify 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 2mo 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.agents/skills/convex-verify/SKILL.md · 35 lines

How it starts

The opening of the file, as written. The whole thing — 35 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Prove a feature works — seed, drive, assert

A green typecheck proves the code parses; it does not prove a non-owner is actually denied, that a query returns the right rows, or that a mutation has the effect it claims. This capability closes that gap with the loop the whole field is missing: seed → drive → assert, run in-process with convex-test so it needs no deployment. Its highest-value assertions are the NEGATIVE ones — the caller who should be refused — because those are exactly the authz defects the 30-app corpus shows are the #1 real bug and the ones a happy-path demo never catches.

Workflow

  1. IDENTIFY the feature to prove: the specific exported query/mutation/action (or a small set) the user just built/changed, and its intended behavior — who should be allowed, what data should come back, what a mutation should change. If the intent is unstated, ask one focused question rather than guessing the contract.
  2. SET UP convex-test: ensure convex-test + vitest are dev deps AND a vitest.config.ts sets test.environment: "edge-runtime" with server.deps.inline: ["convex-test"] — WITHOUT that config, convexTest(schema) fails at runtime with import.meta.glob is not a function (verified). Also install @edge-runtime/vm. Then convexTest(schema) gives a t handle. Reuse the project's existing test setup if present (compose with the test capability, don't fork it).
  3. SEED realistic data through the app's OWN functions where possible (so the seed exercises the same validators/mutations a real user would), falling back to t.run(async (ctx) => ctx.db.insert(...)) for fixtures the public API can't create. Seed at least: the caller's own rows AND a second user's rows, so cross-user access is testable.
  4. DRIVE the feature as DIFFERENT identities with t.withIdentity({ subject, tokenIdentifier, ... }): call the function as (a) the legitimate owner, (b) a different authenticated user, and (c) unauthenticated (t with no identity). Use the real identity shape the app's auth uses (subject/tokenIdentifier), matching how ownership is resolved.
  5. ASSERT behavior — POSITIVE and NEGATIVE:
    • positive: the owner gets the expected rows / the mutation made the expected change (expect(await t.withIdentity(owner).query(api.x.y, args)).toEqual(...)).
    • NEGATIVE (the load-bearing half): a different user calling the same function is REFUSED — await expect(t.withIdentity(other).mutation(api.x.cancel, {id})).rejects.toThrow(/forbidden|not authorized|403/) — and an unauthenticated caller is refused where auth is required. A feature is not proven until the wrong caller is shown to be blocked.
    • data-scope: a list/query returns ONLY the caller's rows, never the second user's (assert the second user's row is absent).
  6. RUN the tests (npx vitest run) and report: what was proven (each positive + negative assertion that passed), and — critically — any assertion that FAILED, because a failed negative assertion is a real authz hole found before ship. Emit findings on the bus (specs/finding.schema.json, class authz/correctness, evidence kind probe-result with the exact failing call) for anything that didn't behave.
  7. Do NOT weaken a test to make it pass: if the owner-only query returns another user's row, the FIX is in the function (hand to convex-authz), not in the assertion. A test changed until it's green proves nothing.

Read the full file on GitHub · 35 lines

Changes

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.

  1. 2mo ago First seen · 35 lines · 42 tokens per session scan A b7aff41a73c0

Subscribe to this mod's changes

convex-verify is a skill published in the GitHub repository openclaw/clawhub (9,547 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 1,115 once invoked, about $0.0002 per session on Opus 5.5. 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.

Related

convex-verify compared with skills from other repositories

convex-verify next to 6 skills from other repositories
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