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 ezBuilder/code-brain --skill tdd-with-memorygit clone --depth 1 https://github.com/ezBuilder/code-brainWrote 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/ezbuilder/code-brain/tdd-with-memory)<a href="https://agentmods.dev/skills/ezbuilder/code-brain/tdd-with-memory"><img src="https://agentmods.dev/badge/skills/ezbuilder/code-brain/tdd-with-memory/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/ezbuilder/code-brain/tdd-with-memory"><img src="https://agentmods.dev/badge/skills/ezbuilder/code-brain/tdd-with-memory.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 | $0.00035 | $0.00377 |
| Opus 5.5 | $0.00014 | $0.00151 |
| Sonnet 5.5 | $0.00007 | $0.00075 |
| Haiku 4.5 | $0.00003 | $0.00038 |
Grade A, and why
tdd-with-memory 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.
What it actually says
기억을 활용한 TDD 절차:
- 구현 대상을 한 문장으로 정리한다.
- 먼저 관련 결정·컨벤션·교훈을 회상한다:
.ai/bin/ai memory recall --query "<기능/모듈 핵심어>"- 결정만 좁혀 보려면
.ai/bin/ai memory decision list --text "<핵심어>"
- RED: 기대 동작을 표현하는 실패 테스트를 먼저 작성한다.
- GREEN: 테스트를 통과시키는 가장 작은 구현만 한다.
- REFACTOR: 동작을 유지한 채 중복·과설계를 줄인다.
- 좁은 테스트부터 실행하고, 필요하면 린트/타입체크를 돌린다.
- 재사용할 가치가 있는 새 컨벤션/설계 결정을 기억에 남긴다:
.ai/bin/ai memory decision add --text "<채택한 컨벤션/결정>" --tag convention- 반복되는 실패 예방책이면
.ai/bin/ai lessons add --failure ... --cause ... --fix ...
- 완료 보고에 변경/검증/위험을 적는다.
금지:
- 테스트 없이 구현부터 작성
- 통과를 위해 실패 테스트 삭제·약화
- 기존 결정과 모순되는 컨벤션을 회상 없이 도입(충돌 시
memory conflicts로 확인)
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 · 27 lines · 35 tokens per session scan A 0d69f037ed16
tdd-with-memory is a skill published in the GitHub repository ezBuilder/code-brain (11 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 35 tokens to every session and 377 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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