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/talkpython/agentic-ai-for-python-courseWrote 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/talkpython/agentic-ai-for-python-course/test-review)<a href="https://agentmods.dev/commands/talkpython/agentic-ai-for-python-course/test-review"><img src="https://agentmods.dev/badge/commands/talkpython/agentic-ai-for-python-course/test-review/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/talkpython/agentic-ai-for-python-course/test-review"><img src="https://agentmods.dev/badge/commands/talkpython/agentic-ai-for-python-course/test-review.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 | $0.00000 | $0.00144 |
| Opus 5.5 | $0.00000 | $0.00058 |
| Sonnet 5.5 | $0.00000 | $0.00029 |
| Haiku 4.5 | $0.00000 | $0.00014 |
Grade A, and why
test-review 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.
What it actually says
Review Unit Tests Command
Act as a software quality engineer and python expert.
We have a series of unit tests in this project. Our job today is to review them and ensure they still pass. This includes checking that:
- Unit tests exist and are executable by pytest.
- pytest is installed in the virtual environment and specified as a dev dependency.
- There is a proper pytest.ini configuration file and it is optimized for our code structure.
- All unit tests pass.
- Unit tests should not emit warnings (it should be a "clean run").
Perform this review and analysis and give a summary to the user.
Do NOT create any markdown report files unless instructed further below by the user.
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 · 16 lines · 0 tokens per session scan A ca9456e110c9
test-review is a command published in the GitHub repository talkpython/agentic-ai-for-python-course (75 stars, last pushed 11mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 144 tokens. 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 commands, from other repositories
coding-flow
Light coding workflow: features, fixes, refactors, unit tests, etc.; scales small to large.
modernization-flow-testing
Phase 3 Testing (optional) of modernization-flow.
pr-enhance
Command "pr-enhance" from ruvnet/ruflo, covering pr-enhance, usage, options, examples and enhance pr.
run-all-tests-and-fix
Execute the full test suite and systematically fix any failures, ensuring code quality and functionality.
pm-tests
List missing unit-test companions for core/changed sources. Do not write tests into the business tree unless the user confirms.
create-python-tests
Command "create-python-tests" from codeready-toolchain/tarsy, covering writing tests for python llm service, running tests, from project root, from llm-service/ directory and critical rules.