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 agentmods add skills/ezbuilder/code-brain/diagnose-with-memorynpx skills add ezBuilder/code-brain --skill diagnose-with-memorygit clone --depth 1 https://github.com/ezBuilder/code-brainWhat 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 | $0.00032 | $0.00382 |
| Opus 5 | $0.00016 | $0.00191 |
| Sonnet 5 | $0.00006 | $0.00076 |
| Haiku 4.5 | $0.00003 | $0.00038 |
Grade A, and why
diagnose-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 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.
What it actually says
기억을 활용한 진단 절차:
- 증상을 한 문장으로 정리한다.
- 먼저 과거 경험을 회상한다:
.ai/bin/ai memory recall --query "<증상 핵심어>"(결정·실패·교훈·절차 통합)- 또는
.ai/bin/ai lessons recall --query "<증상 핵심어>"(교훈만)
- 회상된 실패가 현재 버전/환경에서도 유효한지 확인한다(날짜·버전 관측이지 영구 금지가 아님).
- 관련 파일과 기존 패턴을 찾는다.
- 원인을 확인한 뒤 가장 작은 수정만 적용한다.
- 좁은 테스트부터 실행해 검증한다.
- 새로 배운 것을 기억에 남긴다:
- 재현 가능한 실패:
.ai/bin/ai memory decision add --kind failure --text "<무엇이 실패>" --observed-version <pkg>=<버전> --retest-after <YYYY-MM-DD> - 일반화된 교훈:
.ai/bin/ai lessons add --failure "<현상>" --cause "<원인>" --fix "<해결>"
- 재현 가능한 실패:
- 완료 보고에 변경/검증/위험을 적는다.
금지:
- 회상 없이 같은 실패를 반복 진단
- 원인 모른 채 우회 코드 작성
- 영구 금지로 기록(항상 버전·날짜 관측으로)
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 · 27 lines · 32 tokens per session scan A 76e334d4dca8
diagnose-with-memory is a skill published in the GitHub repository ezBuilder/code-brain (11 stars, last pushed 2d ago), licensed Apache-2.0. It adds 32 tokens to every session and 382 once invoked, about $0.0002 per session on Opus 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
docs
Routes one document to its Diataxis mode (tutorial, how-to guide, reference, explanation), drafts or edits it under that mode's constraints, and checks its markdown form against CommonMark 0.31.2. Use when: writing or generating documentation, deciding where a doc belongs, moving or reorganizing docs, splitting a…
close-session
End-of-session ritual — audit today's patterns against accumulated memory, propose promotions, refresh MEMORY.md, and write the session handoff. Use when the user says "/memory-kit:close-session", "закрой сессию", "закрываем", "we're done for today", "wrap up".
innate-memory
Innate procedural knowledge layer for coding, debugging, and analysis sessions. ACTIVATE when: (1) user says "remember", "save", "log", "follow this rule", "don't forget", "recall", or "what did we learn"; (2) a non-obvious solution, workaround, constraint, or invariant was discovered during this session; (3) starting…
kayba-stage-5-action-plan
Triage each insight into discard/code-fix/prompt-fix and produce a prioritized action plan with specific recommendations. Trigger when the user says "run stage 5", "make action plan", "triage skills", or when invoked by the kayba-pipeline orchestrator. Requires eval outputs from stages 1-4.
kayba-stage-2-domain-context
Gather domain context about the repository and agent — system prompt, tool definitions, domain docs, and behavior patterns from traces. Trigger when the user says "run stage 2", "gather context", "domain context", or when invoked by the kayba-pipeline orchestrator.
kayba-stage-1-api-analysis
Fetch pre-computed insights from the Kayba API and build a structured summary. Does NOT upload traces or trigger generation — analysis is assumed to already exist. Trigger when the user says "run stage 1", "get insights", "fetch skills", "kayba analyze", or when invoked by the kayba-pipeline orchestrator. Requires the…