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/imgompanda/fireauto/fireauto-mem-search-guidenpx skills add imgompanda/fireauto --skill fireauto-mem-search-guidegit clone --depth 1 https://github.com/imgompanda/fireautoWrote 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/imgompanda/fireauto/fireauto-mem-search-guide)<a href="https://agentmods.dev/skills/imgompanda/fireauto/fireauto-mem-search-guide"><img src="https://agentmods.dev/badge/skills/imgompanda/fireauto/fireauto-mem-search-guide.svg" alt="Measured on agentmods" 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 | $0.00118 | $0.00450 |
| Opus 5 | $0.00059 | $0.00225 |
| Sonnet 5 | $0.00024 | $0.00090 |
| Haiku 4.5 | $0.00012 | $0.00045 |
Grade A, and why
fireauto-mem-search-guide 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 6d 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
개발 지식 데이터베이스 활용 가이드
fireauto-mem은 사용자의 모든 개발 세션에서 자동으로 축적된 지식 DB입니다. 사용자가 명시적으로 요청하지 않아도, 관련 지식이 있을 때 능동적으로 활용하세요.
언제 능동적으로 활용하나요?
- 사용자가 파일을 수정할 때 → 그 파일과 관련된 과거 지식 확인
- 버그를 수정할 때 → 비슷한 버그 수정 이력 확인
- 설계 결정이 필요할 때 → 과거 결정 사항과 그 이유 참고
- 새 기능 구현 시 → 관련 패턴이나 주의사항 확인
- 사용자가 과거 작업을 참조할 때 → 직접 검색
활용 흐름
-
memory-search로 관련 지식 탐색
- 현재 작업의 키워드로 검색 (파일명, 기술명, 패턴명)
- type 필터: bugfix, feature, pattern, decision, gotcha, refactor
-
memory-detail로 상세 확인
- 검색 결과에서 관련성 높은 항목의 전체 내용 확인
-
memory-related로 연관 지식 탐색
- 발견한 지식과 연결된 다른 지식 확인
-
답변에 자연스럽게 반영
- "이 프로젝트에서 이전에 비슷한 패턴을 사용했어요: ..."
- "관련 주의사항이 있어요: ..."
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.
- 6d ago First seen · 39 lines · 118 tokens per session scan A f31f5926db9c
fireauto-mem-search-guide is a skill published in the GitHub repository imgompanda/fireauto (140 stars, last pushed 4mo ago), licensed MIT. It adds 118 tokens to every session and 450 once invoked, about $0.0006 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.
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