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 agentmods add commands/get-convex/convex-agent-plugins/convex-verifygit clone --depth 1 https://github.com/get-convex/convex-agent-pluginsWrote 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/commands/get-convex/convex-agent-plugins/convex-verify)<a href="https://agentmods.dev/commands/get-convex/convex-agent-plugins/convex-verify"><img src="https://agentmods.dev/badge/commands/get-convex/convex-agent-plugins/convex-verify.svg" alt="Measured on agentmods" 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 | $0.00037 | $0.01085 |
| Opus 5 | $0.00018 | $0.00543 |
| Sonnet 5 | $0.00007 | $0.00217 |
| Haiku 4.5 | $0.00004 | $0.00109 |
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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 30 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.
Steps
- 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.
- SET UP
convex-test: ensureconvex-test+vitestare dev deps AND avitest.config.tssetstest.environment: "edge-runtime"withserver.deps.inline: ["convex-test"]— WITHOUT that config,convexTest(schema)fails at runtime withimport.meta.glob is not a function(verified). Also install@edge-runtime/vm. ThenconvexTest(schema)gives athandle. Reuse the project's existing test setup if present (compose with thetestcapability, don't fork it). - 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. - 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 (twith no identity). Use the real identity shape the app's auth uses (subject/tokenIdentifier), matching how ownership is resolved. - 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).
- positive: the owner gets the expected rows / the mutation made the expected change (
- 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. - 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.
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.
- 5d ago First seen · 30 lines · 37 tokens per session scan A d47aac48c85b
convex-verify is a command published in the GitHub repository get-convex/convex-agent-plugins (112 stars, last pushed 7d ago), licensed MIT. It adds 37 tokens to every session and 1,085 once invoked, about $0.0002 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 commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.