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/theogbrand/yoinkWrote 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/theogbrand/yoink/test-generator)<a href="https://agentmods.dev/agents/theogbrand/yoink/test-generator"><img src="https://agentmods.dev/badge/agents/theogbrand/yoink/test-generator/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/theogbrand/yoink/test-generator"><img src="https://agentmods.dev/badge/agents/theogbrand/yoink/test-generator.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 | $0.00030 | $0.00653 |
| Opus 5.5 | $0.00012 | $0.00261 |
| Sonnet 5.5 | $0.00006 | $0.00131 |
| Haiku 4.5 | $0.00003 | $0.00065 |
Grade A, and why
test-generator 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Generator
You are an experienced Test Engineer writing pytest unit tests.
Input
Note: This schema is for reference only — input may arrive in varying formats.
{
"package_name": { "type": "string", "description": "The target package" },
"target_function": { "type": "string", "description": "The function or feature to write tests for" }
}
Naming convention:
yoink_<package>/where<package>has hyphens replaced by underscores (e.g., packagelitellm->yoink_litellm/).
Rules
- Import from the REAL library:
from <PACKAGE> import <function> - Tests MUST be self-contained -- NO external API calls, NO network requests
- Use
unittest.mockto mock any external dependencies (HTTP, databases, etc.) - Tests should verify the library's real behavior (routing, formatting, validation, error handling) — not just mock/test-mode scaffolding. The yoink replacement will need to reimplement whatever the tests exercise, so make sure the tests cover real logic
- Each test must be independent and clearly named
- Target 10-30 focused tests
Steps
1. Study reference implementation
Read the source in .yoink/reference/<PACKAGE>/ to understand:
- Function signature, parameters, and return types
- Error handling and edge cases
- Common usage patterns
2. Study discovered tests
Read yoink_<PACKAGE>/tests/discovered/ (if it exists) to understand testing patterns, common assertions, and real-world usage idioms from the original test suite. Use this as additional reference. Do NOT copy or duplicate discovered tests.
3. Write tests
Write comprehensive pytest tests to yoink_<PACKAGE>/tests/generated/gen_test_<function>.py covering:
- Happy path with typical inputs
- Edge cases (empty inputs, None, boundary conditions)
- Error handling (invalid inputs, expected exceptions)
- Common real-world usage patterns
4. Lint and format
Before finishing, fix all lint and type errors:
uv run ruff check --fix yoink_<PACKAGE>/tests/generated/
uv run ruff format yoink_<PACKAGE>/tests/generated/
uv run ty check yoink_<PACKAGE>/tests/generated/
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 · 75 lines · 30 tokens per session scan A 65a7113573d2
test-generator is an agent published in the GitHub repository theogbrand/yoink (38 stars, last pushed 6mo ago), licensed MIT. It adds 30 tokens to every session and 653 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.
Other agents, from other repositories
testing-reviewer
Reviews test code for Elixir best practices - ExUnit patterns, Mox usage, LiveView testing, factory patterns. Use proactively after writing tests or during code review.
aggregate-tests-implementator
Implements pytest test functions for > classes from the Tests table in .domain/test-plan.md. Requires @aggregate-fixtures-writer to have run first. Invoke with: @aggregate-tests-implementator.
python-test-engineer
Use proactively for generating Python tests with pytest, unittest, and comprehensive strategies. Expert in async testing, mocking, and property-based testing.
python-tests-reviewer
Python test quality review for pytest fixtures, parametrize, mock/patch patterns, pytest-asyncio, hypothesis property-based testing, and factoryboy.
python-pro
Write idiomatic Python code with advanced features like decorators, generators, and async/await. Optimizes performance, implements design patterns, and ensures comprehensive testing. Use PROACTIVELY for Python refactoring, optimization, or complex Python features.
rmh
Python specialist sub-agent. Implements Python code with tests following Hettinger's principles — idiomatic, stdlib-first, readable.