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/zevtos/agentpipeWrote 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/zevtos/agentpipe/test)<a href="https://agentmods.dev/commands/zevtos/agentpipe/test"><img src="https://agentmods.dev/badge/commands/zevtos/agentpipe/test/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/commands/zevtos/agentpipe/test"><img src="https://agentmods.dev/badge/commands/zevtos/agentpipe/test.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 | $0.00025 | $0.00751 |
| Opus 5.5 | $0.00010 | $0.00300 |
| Sonnet 5.5 | $0.00005 | $0.00150 |
| Haiku 4.5 | $0.00003 | $0.00075 |
Grade A, and why
test 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 1mo 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are orchestrating comprehensive test coverage for the project. This goes beyond "write some unit tests" — it's a full test strategy with risk-based prioritization.
Context
@CLAUDE.md
Test Target
$ARGUMENTS
Pipeline
Step 1: Coverage Analysis
Before writing any tests:
- Identify the testing framework in use (check package.json, pyproject.toml, Cargo.toml, etc.)
- Run existing tests to establish baseline: what passes, what fails, what's slow
- If coverage tooling exists, run it to identify untested code paths
- Map critical code paths that MUST be tested (auth, payments, data mutations, business rules)
- Identify which test types already exist (unit, integration, e2e)
Present:
- Current coverage: what's tested, what's not
- Risk map: critical untested code paths ranked by risk
- Test strategy: which types of tests to add and why
Step 2: Test Implementation (Tester Agent)
Run the tester agent:
"Analyze the codebase and implement comprehensive tests.
Target: $ARGUMENTS (if empty, focus on highest-risk uncovered code)
Current test coverage: [paste from Step 1]
Write tests in this priority order:
- Critical business logic — domain rules, calculations, state transitions
- API endpoints — request validation, response format, error handling, auth
- Data layer — queries return correct results, constraints enforced, migrations work
- Error paths — what happens when things fail (network, DB, invalid input)
- Edge cases — boundary values, empty inputs, concurrent access
For each test file:
- Follow existing test patterns and conventions
- Use real dependencies where possible (mock only external HTTP services)
- Name tests descriptively: test_[scenario]_[expected_result]
- Include setup/teardown for clean test isolation
Consider advanced strategies where they add value:
- Property-based testing for serialization/deserialization round-trips
- Property-based testing for algorithmic invariants
- Contract tests if there are service-to-service APIs
- Fuzzing for parsers or security-critical input processing"
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.
- 1mo ago First seen · 87 lines · 25 tokens per session scan A 7f91417ee8fb
test is a command published in the GitHub repository zevtos/agentpipe (11 stars, last pushed 4mo ago), licensed MIT. It adds 25 tokens to every session and 751 once invoked, about $0.0001 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.
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test-coverage
Analyze test coverage and identify the highest-value gaps to fill.