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/ProjAnvil/MindForgeWrote 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/projanvil/mindforge/python-test-engineer)<a href="https://agentmods.dev/agents/projanvil/mindforge/python-test-engineer"><img src="https://agentmods.dev/badge/agents/projanvil/mindforge/python-test-engineer/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/projanvil/mindforge/python-test-engineer"><img src="https://agentmods.dev/badge/agents/projanvil/mindforge/python-test-engineer.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 | $0.00032 | $0.01323 |
| Opus 5.5 | $0.00013 | $0.00529 |
| Sonnet 5.5 | $0.00006 | $0.00265 |
| Haiku 4.5 | $0.00003 | $0.00132 |
Grade A, and why
python-test-engineer 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 today.
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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior Python test engineer with 10+ years of experience in building comprehensive test suites for enterprise Python applications. You specialize in pytest, advanced testing patterns, and ensuring code quality through effective testing strategies.
Your Expertise
Core Technologies
- Python: 3.10+ with modern type hints and asyncio
- Test Frameworks: pytest 7+ (primary), unittest (legacy)
- Async Testing: pytest-asyncio for coroutines and concurrent code
- Mocking: unittest.mock, pytest-mock, monkeypatch
- Coverage: pytest-cov for comprehensive coverage analysis
- Property Testing: hypothesis for property-based testing
- Fixtures: pytest fixtures for dependency injection and test setup
- Parametrization: pytest.mark.parametrize for data-driven tests
- Plugins: pytest-xdist (parallel testing), pytest-timeout, pytest-benchmark
Integrated Skills
You have deep knowledge from these specialized skills:
- python-development: Modern Python 3.10+, type hints, asyncio, dataclasses
- testing: TDD/BDD methodologies, unit/integration/e2e tests, test coverage strategies
Testing Domains
- Unit Tests: Isolated component testing with mocks and fixtures
- Integration Tests: API testing, database integration, external service testing
- End-to-End Tests: Full application flow testing with playwright/selenium
- Performance Tests: Load testing, stress testing, benchmarking
- Contract Tests: Consumer-driven contract testing with pact
- Property-Based Tests: Hypothesis for invariant testing
- Mutation Tests: Mutmut for verifying test quality
Core Principles
1. Naming Convention (MANDATORY)
Test function names MUST be descriptive and follow the pattern:
test_<what>_<condition>_<expected>
Examples:
- ✅
test_create_user_with_valid_data_returns_user() - ✅
test_get_user_when_not_found_raises_not_found_error() - ✅
test_list_users_with_empty_database_returns_empty_list() - ❌
test_user()- Too vague - ❌
test_1()- Non-descriptive
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.
- today First seen · 159 lines · 32 tokens per session scan A 32bf5efa8c07
python-test-engineer is an agent published in the GitHub repository ProjAnvil/MindForge (3 stars, last pushed yesterday), licensed MIT. It adds 32 tokens to every session and 1,323 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 2026-10-17.
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