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 HoangNguyen0403/agent-skills-standard --skill common-tddgit clone --depth 1 https://github.com/HoangNguyen0403/agent-skills-standardWrote 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/hoangnguyen0403/agent-skills-standard/common-tdd)<a href="https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/common-tdd"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/common-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/hoangnguyen0403/agent-skills-standard/common-tdd"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/common-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 | $0.00046 | $0.00822 |
| Opus 5.5 | $0.00018 | $0.00329 |
| Sonnet 5.5 | $0.00009 | $0.00164 |
| Haiku 4.5 | $0.00005 | $0.00082 |
Grade A, and why
common-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 19d 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.
Quality-First TDD
Priority: P0 (CRITICAL)
A passing test is insufficient; the test must prove an owned behavior and a distinct plausible fault.
Choose the mode
- New behavior: strict RED -> GREEN -> REFACTOR. Do not write production code before the expected RED.
- Legacy or bug fix: characterize only when needed, then reproduce the intended change as a failing regression (RED). Preserve unrelated existing code; do not delete it merely because it predates the test.
Before writing a test
Compare against the existing suite before adding or removing cases. Ensure the scenario is not already covered upstream or in nearby layers.
Create one Test Intent Record per behavior/risk:
contract: observable contract — an application-owned result or outward side effectfault: distinct plausible fault this test catcheslayer: smallest honest unit, component, contract, integration, or E2E layercases: minimal distinct equivalence classes; use a parameterized test for equivalent inputscommand: exact focused single-run command
Reject tests that duplicate existing suite coverage, assert internal mock choreography over outward side effects, depend on time/network/order, or invent numeric four-pillar scores without measured evidence.
Bounded loop
- Run configured lint/type checks, inspect nearby tests, and derive the smallest command.
- RED: add one intent group and run it in the foreground, sequentially, single-run mode.
- Classify RED as
expected_red,invalid_red,unexpected_green, orverification_infra_failed. If it isunexpected_green, inspect existing coverage and remove a redundant or weak case before implementing production code. - GREEN: implement only enough to satisfy
expected_red; rerun the same command. - REFACTOR: improve structure without changing behavior; rerun the same command.
- Escalate only when evidence requires it: related unit target, integration/contract target, then explicit release/full-suite gate.
What ships with it
9 files 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.
- LICENSE 1.0 KB
- references/aaa_example.md 387 B
- references/aaa_methodology.md 1.2 KB
- references/anti-patterns.md 1.6 KB
- references/best-practices.md 2.1 KB
- references/quality-contract.md 3.2 KB
- references/tdd_patterns.md 1.9 KB
- references/test_runners.md 1.2 KB
- references/testing_anti_patterns.md 2.3 KB
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.
- 19d ago Changed · +1 lines 2902d3a26ef2
- 1mo ago First seen · 74 lines · 46 tokens per session scan A e46965cdbbd9
common-tdd is a skill published in the GitHub repository HoangNguyen0403/agent-skills-standard (583 stars, last pushed today), licensed MIT. It adds 46 tokens to every session and 822 once invoked, about $0.0002 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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refactor
Safely restructures existing code while preserving behavior through impact analysis and TDD. User-invoked entry point via /refactor; not for autonomous or subagent use.
bugfix
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perf-optimize
Runs profile-driven performance optimization using multi-dimensional parallel analysis and sequential TDD fixes. User-invoked entry point via /perf-optimize; not for autonomous or subagent use.
tdd
A guide for test-driven development (TDD), a method where you write a failing test before writing the code that should pass it.