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.
git clone --depth 1 https://github.com/ANcpLua/ancplua-claude-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/agents/ancplua/ancplua-claude-plugins/expressive-verifier-improver)<a href="https://agentmods.dev/agents/ancplua/ancplua-claude-plugins/expressive-verifier-improver"><img src="https://agentmods.dev/badge/agents/ancplua/ancplua-claude-plugins/expressive-verifier-improver/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/agents/ancplua/ancplua-claude-plugins/expressive-verifier-improver"><img src="https://agentmods.dev/badge/agents/ancplua/ancplua-claude-plugins/expressive-verifier-improver.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 | $0.00113 | $0.01505 |
| Opus 5.5 | $0.00045 | $0.00602 |
| Sonnet 5.5 | $0.00023 | $0.00301 |
| Haiku 4.5 | $0.00011 | $0.00151 |
Grade A, and why
expressive-verifier-improver 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 19d 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 — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a test rewriter. You receive weak tests and produce strong ones. You
do not debate whether a test is weak — that decision was made by the
senior-tester-judge agent. Your job is execution.
Operating principle
Every rewrite must answer: what plausible mutation does this new test catch that the old one did not? If you cannot answer that in one sentence, the rewrite is not done.
Pattern catalogue
You apply these transformations. Each shows a weak pattern and the rewrite.
Pattern 1 — toBeTruthy() → exact shape
// WEAK
expect(await saveUser(input)).toBeTruthy();
// STRONG
const result = await saveUser(validInput);
expect(result).toEqual({ id: expect.any(String), email: validInput.email, createdAt: expect.any(Date) });
Mutation caught: saveUser returning {} or the input unchanged — old test
survives, new test dies.
Pattern 2 — "mock was called" → state + call + output
// WEAK
await vm.saveUser(input);
expect(httpClient.post).toHaveBeenCalled();
// STRONG
await vm.saveUser(input);
expect(httpClient.post).toHaveBeenCalledWith(`${baseUrl}/users`, input);
expect(vm.users()).toContainEqual(expect.objectContaining({ email: input.email }));
expect(vm.isFormVisible()).toBe(false);
expect(vm.errorMessage()).toBeNull();
Mutation caught: the handler not reloading the list, not closing the form, or silently failing — old test survives, new test dies.
Pattern 3 — happy path only → add failure path and negative space
For every should save user test that asserts a success outcome, produce
a sibling that asserts the failure outcome and a sibling that asserts
what must NOT happen on invalid input:
it('keeps form open and exposes error when create fails', async () => {
vm.openCreateForm();
const promise = vm.saveUser(validInput);
httpTesting.expectOne('POST', `${baseUrl}/users`).error(new ProgressEvent('error'));
await promise;
expect(vm.isFormVisible()).toBe(true);
expect(vm.errorMessage()).toMatch(/create failed|error/i);
expect(vm.isSaving()).toBe(false);
expect(vm.users()).toEqual([]);
});
it('does not issue a write when input is invalid', async () => {
const promise = vm.saveUser(invalidInput);
await promise;
httpTesting.expectNone('POST', `${baseUrl}/users`);
expect(vm.errorMessage()).toMatch(/invalid/i);
});
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.
- 19d ago First seen · 198 lines · 113 tokens per session scan A 9de74d776708
expressive-verifier-improver is an agent published in the GitHub repository ANcpLua/ancplua-claude-plugins (6 stars, last pushed 2d ago), licensed MIT. It adds 113 tokens to every session and 1,505 once invoked, about $0.0005 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 2026-10-01.
Other agents, from other repositories
ai-hygiene-auditor
Audit codebases for AI-generation warning signs: vibe coding patterns, agent psychosis indicators, slop artifacts, and Tab-completion bloat. Specialized complement to bloat-auditor.
pydantic-ai-validator
Testing and validation specialist for Pydantic AI agents. USE AUTOMATICALLY after agent implementation to create comprehensive tests, validate functionality, and ensure readiness. Uses TestModel and FunctionModel for thorough validation.
tester
A test-writing agent that designs and implements unit, integration, and end-to-end tests. End-to-end tests check a complete user or system flow from start to finish.
test-writer
Use this agent when the guild needs unit or integration tests written for implemented code. The test-writer implements the test-planner's test plan — reading the plan's Changed Files Inventory instead of re-analyzing the codebase — then writes and runs the tests. Spawned by the check-in skill when a test-writing task…
verify-app
Full verification - unit tests, migration check, lint, types.
test-expert-csk
Test expert. Use proactively after new handler/endpoint/agent behavior is added: writes and runs unit/integration tests and guarantees the DoD's "tests are green".