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.
npx skills add genai-io/san --skill tddgit clone --depth 1 https://github.com/genai-io/sanWrote 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/skills/genai-io/san/tdd)<a href="https://agentmods.dev/skills/genai-io/san/tdd"><img src="https://agentmods.dev/badge/skills/genai-io/san/tdd/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/skills/genai-io/san/tdd"><img src="https://agentmods.dev/badge/skills/genai-io/san/tdd.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00073 | $0.00634 |
| Opus 5.5 | $0.00029 | $0.00254 |
| Sonnet 5.5 | $0.00015 | $0.00127 |
| Haiku 4.5 | $0.00007 | $0.00063 |
Grade A, and why
tdd 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TDD: red, green, refactor
Write the test before the code. A test written first specifies the behavior, fails for a known reason, and gives you a definition of done you can run. A test written after tends to describe whatever the code happens to do — bugs included.
Step 1: Find the test runner
Don't assume the command. Detect how this project runs and writes tests: look at
existing test files for the framework and conventions, and at the build/config
for the invocation (go test ./..., npm test, pytest, cargo test, …).
Match what's already there — same framework, same layout, same style.
Step 2: Name the behavior as tests (RED)
State the change as concrete cases before writing any implementation:
- The main success path — the behavior actually requested.
- The edges — empty, zero, boundary, maximum, unexpected input.
- The failures — what should error, and how it should error.
Write these as tests. For a bug fix, the first test reproduces the bug. Keep each test focused on one behavior with a clear name.
Step 3: Watch them fail
Run the tests and confirm they fail — and fail for the right reason (the behavior is missing), not a typo or an import error. A test you never saw fail proves nothing. This is the gate: do not write implementation until you've seen red.
Step 4: Implement to green
Write the minimum code that makes the tests pass. No features the tests don't demand, no speculative abstraction. Run the tests until they're green.
Step 5: Refactor on green
Now improve the shape — naming, duplication, structure — with the tests staying green the whole way. The tests let you clean up without fear; if one goes red, the last change altered behavior, so undo it.
Test what callers see, not how it's built
- Assert on observable behavior and return values, not private internals — tests bound to implementation break on every refactor and defeat Step 5.
- Keep tests isolated: no shared mutable state, no ordering dependency, each runs alone. Prefer real behavior; mock only what you can't run (network, clock, external services).
- Cover the edges and error paths, not just the happy case — that's where the bugs the persona is trying to prevent actually live.
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 · 69 lines · 73 tokens per session scan A 949f986e0619
tdd is a skill published in the GitHub repository genai-io/san (66 stars, last pushed today), licensed Apache-2.0. It adds 73 tokens to every session and 634 once invoked, about $0.0003 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 skills, from other repositories
tdd
Test-driven development — write the failing test first, then the code. Triggers on TDD, test first, write tests, test-driven.
systematic-debugging
4-phase root cause debugging: understand bugs before fixing.
kotlin-testing
Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices.
test-driven-development
TDD: enforce RED-GREEN-REFACTOR, tests before code.
rust-testing
Rust testing patterns including unit tests, integration tests, async testing, property-based testing, mocking, and coverage. Follows TDD methodology.
cpp-testing
Use only when writing/updating/fixing C++ tests, configuring GoogleTest/CTest, diagnosing failing or flaky tests, or adding coverage/sanitizers.