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 minghinmatthewlam/agent-guards --skill tddgit clone --depth 1 https://github.com/minghinmatthewlam/agent-guardsWrote 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/minghinmatthewlam/agent-guards/tdd)<a href="https://agentmods.dev/skills/minghinmatthewlam/agent-guards/tdd"><img src="https://agentmods.dev/badge/skills/minghinmatthewlam/agent-guards/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/minghinmatthewlam/agent-guards/tdd"><img src="https://agentmods.dev/badge/skills/minghinmatthewlam/agent-guards/tdd.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 | $0.00052 | $0.00613 |
| Opus 5.5 | $0.00021 | $0.00245 |
| Sonnet 5.5 | $0.00010 | $0.00123 |
| Haiku 4.5 | $0.00005 | $0.00061 |
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 2d 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.
This is a copy
88% identical to tdd — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TDD Bug Fix
When fixing a bug with a clear, cheap test path, make the broken behavior executable before changing production code. The goal is a focused regression test that fails before the fix and passes after it.
Do not force a test when it would be impractical. If the available test would require broad harness setup, brittle mocks, slow end-to-end infrastructure, production-only state, vague reproduction steps, or large unrelated fixture churn, skip adding a new test and use the closest useful verification instead.
Workflow
- Understand the bug. Identify the intended behavior, current behavior, affected path, and smallest observable reproduction.
- Choose the narrowest executable check. Prefer the closest unit, component, integration, or regression test already used for that codepath. If no practical test path is obvious, do not create one from scratch just to satisfy the workflow.
- Write the failing test first. Add the smallest focused test that would have caught the bug. The test should encode intended behavior, not mirror the current implementation.
- Run the new test before fixing. Confirm it fails for the intended reason. If it passes or fails for an unrelated reason, correct the test or reproduction before editing the implementation.
- Fix the bug. Make the smallest production change that satisfies the intended behavior while preserving nearby contracts.
- Rerun the regression test. Confirm the test now passes.
If a Failing Test Is Impractical
Use the closest executable regression check instead: a targeted script, manual reproduction command, browser automation, snapshot comparison, log assertion, or focused integration check.
Prefer no new test over a bad test. A bad test is one that mostly tests mocks, encodes current implementation details, depends on timing or unrelated global state, needs expensive infrastructure for a small fix, or would be deleted immediately after proving the fix.
Guardrails
- Do not change tests merely to match a wrong implementation.
- Do not weaken existing assertions unless the expected behavior has genuinely changed and the reason is clear.
- Keep the regression test focused on the bug. Avoid broad fixture churn or unrelated coverage expansion.
- If the bug is flaky, make the test deterministic where possible and document the signal being locked down.
- If the bug exposes a broader class of failures, first land the focused regression path, then consider additional sibling coverage.
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.
- 2d ago First seen · 43 lines · 52 tokens per session scan A 7b34a1316259
tdd is a skill published in the GitHub repository minghinmatthewlam/agent-guards (47 stars, last pushed 2d ago), licensed MIT. It adds 52 tokens to every session and 613 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to tdd, differing in 2 lines, and is treated as a copy.
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