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 agents/prgilabert/agent-ecosystem-generator/test-reviewergit clone --depth 1 https://github.com/prgilabert/agent-ecosystem-generatorWrote 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/prgilabert/agent-ecosystem-generator/test-reviewer)<a href="https://agentmods.dev/agents/prgilabert/agent-ecosystem-generator/test-reviewer"><img src="https://agentmods.dev/badge/agents/prgilabert/agent-ecosystem-generator/test-reviewer.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 5.1 | $0.00068 | $0.00201 |
| Opus 5 | $0.00034 | $0.00101 |
| Sonnet 5 | $0.00014 | $0.00040 |
| Haiku 4.5 | $0.00007 | $0.00020 |
Grade A, and why
test-reviewer 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.
What it actually says
test-reviewer
Role
Verifies test coverage for the diff.
Inputs
Inputs are passed as parameters by the orchestrator.
Workflow
- Fetch diff.
- For each changed non-test file, search for a matching test file modification.
- Emit {file, has_test_change, matching_test_path}.
Output
A plain-text summary to the orchestrator.
Things you must not do
- Do not modify files outside the provided output path.
- Do not set
permissionMode: bypassPermissions.
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 · 33 lines · 68 tokens per session scan A e06092c2a24c
test-reviewer is an agent published in the GitHub repository prgilabert/agent-ecosystem-generator (8 stars, last pushed 4mo ago), licensed MIT. It adds 68 tokens to every session and 201 once invoked, about $0.0003 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 2026-08-31.
Other agents, from other repositories
semble-search
Code search agent for exploring any codebase. Use for finding code by intent, locating implementations, understanding how something works, or discovering related code. Prefer over runshellcommand/readfile for any semantic or exploratory question.
code-quality-reviewer
Code quality reviewer: bug detection, security vulnerabilities, performance issues, linting, type checking, test coverage.
test-generator
Test specialist: coverage gap analysis, unit/integration test generation, fixtures, API mocking (MSW), HTTP recording.
web-research-analyst
Web research: browser automation, Tavily API, competitive intelligence, documentation capture, technical recon.
claude-design-orchestrator
Parses claude.ai/design handoff bundles: validates schema, dedups proposed components against the codebase via component-search, reconciles tokens, and tracks bundle→PR provenance so design intent stays linked to shipped code.
eval-runner
LLM evaluation specialist who runs structured eval datasets, computes quality metrics using DeepEval/RAGAS, tracks regression across model versions, and reports to Langfuse for tracing and scoring.