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/treylom/knowledge-manager/km-content-extractionnpx skills add treylom/knowledge-manager --skill km-content-extractiongit clone --depth 1 https://github.com/treylom/knowledge-managerWrote 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/treylom/knowledge-manager/km-content-extraction)<a href="https://agentmods.dev/skills/treylom/knowledge-manager/km-content-extraction"><img src="https://agentmods.dev/badge/skills/treylom/knowledge-manager/km-content-extraction.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 | $0.00057 | $0.00982 |
| Opus 5 | $0.00028 | $0.00491 |
| Sonnet 5 | $0.00011 | $0.00196 |
| Haiku 4.5 | $0.00006 | $0.00098 |
Grade A, and why
km-content-extraction 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 3d 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
KM Content Extraction (Codex)
km-workflow Phase 2 의 추출 라우터. 입력 형식을 먼저 판정하고, 아래 표의 도구를 실제로 호출한다 — 도구 호출 없이 콘텐츠를 추측·요약하는 것은 금지. 전문(이미지 파이프라인·병렬 처리·포맷별 상세)은 플러그인
skills/km-content-extraction.md(1,087줄) 참조.
소스별 추출 라우팅 (필수 도구 호출)
| 소스 유형 | 🚨 필수 도구 호출 |
|---|---|
| 한글 (HWP/HWP3/HWPX/HWPML) | kordoc: npx kordoc <files> -d <outdir> → 변환 md 를 Read — anydoc 은 HWP 미지원, 한글 문서는 처음부터 kordoc |
1순위 Read → 2순위 opendataloader-pdf → 3순위 marker_single — 🔴 anydoc 으로 보내지 않는다(다단 레이아웃 순서 붕괴) |
|
| Word (DOCX) | 1순위 npx -y @firecrawl/anydoc "[파일]" → 2순위 Read — 표가 복잡해 깨지면 kordoc |
| Excel (XLSX) | 1순위 npx -y @firecrawl/anydoc "[파일]" (수식 없는 표 한정) — 수식·분석·편집은 xlsx 계열 도구 |
| CSV | Read (anydoc 편입 보류 — 헤더 밀림) |
| PowerPoint | Read (anydoc 미편입 — 슬라이드 경계 소실) |
| TXT/MD | Read |
| 이미지 | Read (Vision) |
| 일반 웹/소셜 | → $km:km-browser-abstraction / $km:km-social-media |
| Vault 종합 | → $km:km-search |
한국어 로컬 문서 fallback = kordoc
입력이 로컬 문서인데 기본 경로(Read·anydoc)로 충실히 못 읽는 형식 — HWP·HWPX, 표가 복잡한 XLSX/DOCX, 한국어 PDF — 은 kordoc 으로 마크다운 변환 후 진행한다:
npx kordoc <files> -d <outdir> # HWP3/HWP/HWPX/HWPML/PDF/XLS/XLSX/DOCX → Markdown
<files>복수 일괄 지원. 산출 =<outdir>/<파일명>.md.- 변환 md 는 원문 보존 검증(표 행수·수치 표본 대조) 후 사용한다.
- PDF 입력은
pdfjs-dist@4peer 의존 필요(v6 비호환).
anydoc ↔ kordoc 역할 분리
| anydoc | kordoc | |
|---|---|---|
| 고유 영역 | epub · rtf · odt/ods/odp | HWP3/HWP/HWPX/HWPML (anydoc 미지원) |
| 겹치는 영역 | DOCX · XLS/XLSX · PDF | DOCX · XLS/XLSX · PDF |
| 성격 | 순수 Rust · 1회 호출 = 1문서 | Node · 한국어 특화 · 복수 일괄 |
- DOCX·XLSX 기본 = anydoc. 깨지거나 한글(HWP) 계열이면 kordoc.
- 🔴 PDF 는 anydoc 금지(순서 붕괴) — 위 표의 다단 경로 유지.
Phase 2 완료 검증 (필수)
□ 해당 소스 유형의 도구를 실제로 호출했는가?
□ 도구 응답에서 추출된 실제 텍스트를 확인했는가 (추측 아님)?
□ 변환 문서는 원문 보존 검증(표 행수·수치 표본)을 했는가?
⚠️ 미완료 시 Phase 3(분석) 진행 금지.
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.
- 3d ago First seen · 57 lines · 57 tokens per session scan A 74e8e20b5e36
km-content-extraction is a skill published in the GitHub repository treylom/knowledge-manager (230 stars, last pushed today), licensed MIT. It adds 57 tokens to every session and 982 once invoked, about $0.0003 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 2026-09-01.
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