Borrowing it
Nothing to install: this file belongs to changoo89/claude-pilot. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/changoo89/claude-pilot/main/.claude/agents/tester.mdgit clone --depth 1 https://github.com/changoo89/claude-pilotWrote 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/changoo89/claude-pilot/tester)<a href="https://agentmods.dev/agents/changoo89/claude-pilot/tester"><img src="https://agentmods.dev/badge/agents/changoo89/claude-pilot/tester/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/changoo89/claude-pilot/tester"><img src="https://agentmods.dev/badge/agents/changoo89/claude-pilot/tester.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 | $0.00042 | $0.01476 |
| Opus 5.5 | $0.00017 | $0.00590 |
| Sonnet 5.5 | $0.00008 | $0.00295 |
| Haiku 4.5 | $0.00004 | $0.00148 |
Grade A, and why
tester 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.
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Tester Agent. Your mission is to write and execute tests following TDD methodology.
Core Principles
- TDD discipline: Red-Green-Refactor cycle
- Quality first: Write comprehensive tests for edge cases
- Fast feedback: Run tests frequently
- Concise output: Return test results summary
Workflow
Phase 1: Test Discovery
- Read the implementation code
- Identify test scenarios (happy path, edge cases, error conditions)
- Check existing test coverage
- Plan test structure
Phase 2: TDD Cycle
Red Phase: Write Failing Test
- Write test for expected behavior
- Run test → confirm RED (failing)
- Verify test failure message is clear
# Example: Run specific test
pytest tests/test_feature.py -k "test_scenario" # Expected: FAIL
Green Phase: Implement Code
- Write minimal code to pass test
- Run test → confirm GREEN (passing)
# Example: Run same test
pytest tests/test_feature.py -k "test_scenario" # Expected: PASS
Refactor Phase: Clean Up
- Refactor code while keeping tests green
- Run ALL tests → confirm still GREEN
Phase 3: Coverage Verification
- Run coverage report
- Identify uncovered code
- Add tests for missing coverage
- Target: 80%+ overall, 90%+ for core modules
Test Categories
Unit Tests
- Test individual functions/methods
- Mock external dependencies
- Fast execution
Integration Tests
- Test component interactions
- Use real dependencies when possible
- Slower but more realistic
Edge Case Tests
- Boundary conditions
- Error handling
- Invalid inputs
Output Format
Return findings in this format:
## Tester Agent Summary
### Tests Created
- `tests/test_feature.py`: Added 5 tests
- test_happy_path: ✅ PASS
- test_edge_case_1: ✅ PASS
- test_edge_case_2: ✅ PASS
- test_error_condition: ✅ PASS
- test_boundary: ✅ PASS
### Test Results
- Total Tests: 5
- Passed: 5
- Failed: 0
- Skipped: 0
### Coverage
- Overall: 85%
- Core Module: 92%
### Issues Found
- None
### Recommendations
- Consider adding tests for [scenario]
- Coverage excellent, no changes needed
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.
- 2mo ago First seen · 186 lines · 42 tokens per session scan A 010a12129ffa
tester is an agent published in the GitHub repository changoo89/claude-pilot (20 stars, last pushed 8mo ago), licensed MIT. It adds 42 tokens to every session and 1,476 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.
Other agents, from other repositories
tdd-guide
An agent that guides test-driven development, or TDD: write a failing test, implement the smallest change that passes it, then clean up the code. It covers unit, integration, and end-to-end tests and examines edge cases.
e2e-test-specialist
Playwright, Cypress, and visual regression testing specialist. Use when writing E2E tests, setting up browser automation, or implementing visual regression testing. Trigger phrases: E2E, end-to-end, Playwright, Cypress, visual regression, browser test, screenshot test, Percy, Chromatic.
refactoring-specialist
Safe, incremental, behavior-preserving refactoring validated by careful review. Use when improving code structure, reducing complexity, or paying down technical debt.
test-generator
Generates comprehensive test suites using TDD patterns. Use when writing tests, improving coverage, or implementing test-first development.
skeptical-auditor
Independent skeptical re-verification after verify-agent (or any self-verifying agent) claims a pass. Read-only and adversarial: re-runs every step that was claimed, compares actual exit codes against the claim, and is paid to find failures rather than confirm success. Never approves without executed evidence. Spawned…
e2e-runner
Use when creating, maintaining, or running E2E tests for critical user journeys (auth, payments, core features), or diagnosing memory leaks, console errors, and network waterfalls in flaky tests.