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 jellydn/my-ai-tools --skill tddgit clone --depth 1 https://github.com/jellydn/my-ai-toolsWrote 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/jellydn/my-ai-tools/tdd)<a href="https://agentmods.dev/skills/jellydn/my-ai-tools/tdd"><img src="https://agentmods.dev/badge/skills/jellydn/my-ai-tools/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/jellydn/my-ai-tools/tdd"><img src="https://agentmods.dev/badge/skills/jellydn/my-ai-tools/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 | $0.00017 | $0.01050 |
| Opus 5.5 | $0.00007 | $0.00420 |
| Sonnet 5.5 | $0.00003 | $0.00210 |
| Haiku 4.5 | $0.00002 | $0.00105 |
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 21d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test-Driven Development (TDD)
Guides you through the complete TDD workflow with Red-Green-Refactor cycle.
Usage
/tdd <ACTION> [ARGUMENTS]
Actions
- start - Initialize TDD session for a feature
- red <TEST_NAME> - Create failing test (Red phase)
- green - Run tests and implement code (Green phase)
- refactor - Guide refactoring process (Refactor phase)
- cycle - Run complete Red-Green-Refactor cycle
- watch - Start test watcher for continuous feedback
- status - Show current test status and next steps
TDD Principles
The Red-Green-Refactor Cycle
- Red: Write a failing test that defines desired behavior
- Green: Write minimal code to make the test pass
- Refactor: Improve code quality while keeping tests green
Best Practices
- Write tests first - Tests define the interface and behavior
- Small steps - Make tiny, incremental changes
- Fast feedback - Run tests frequently for immediate validation
- Clean code - Refactor regularly to maintain quality
- One concept per test - Keep tests focused and atomic
- AAA Pattern - Structure tests as Arrange, Act, Assert
- Black-box testing - Test only public methods and behavior, not implementation details
- Test at an agreed seam - Before writing a test, identify the public interface that exposes the behavior and prefer the highest existing seam
- Independent expectations - Expected values come from a literal, worked example, or spec; do not recompute them with the same algorithm as the implementation
- Vertical slices - Write one meaningful test, implement the minimum, then repeat; avoid writing an entire imagined test suite before learning from the first cycle
Anti-Patterns
- Implementation-coupled tests mock private collaborators or inspect internal state. They fail during harmless refactors and provide weak behavioral confidence.
- Tautological tests derive the expected value with the same logic as the code under test, so both can be wrong together.
- Horizontal slicing writes all tests first and all implementation later. Prefer tracer-bullet slices that exercise one user-visible behavior at a time.
- Unconfirmed seams test a low-level helper only because it is easy to reach. If the behavior matters at a higher interface, test there instead or document why the lower seam is the correct one.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 21d ago Changed · +12 lines 433e4bae1276
- 1mo ago First seen · 107 lines · 17 tokens per session scan A 85952c6abf8b
tdd is a skill published in the GitHub repository jellydn/my-ai-tools (124 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 1,050 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.
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