Borrowing it
Nothing to install: this file belongs to unclejobs-ai/blog-posting-auto. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/unclejobs-ai/blog-posting-auto/main/.claude/skills/blog-pipeline/SKILL.mdgit clone --depth 1 https://github.com/unclejobs-ai/blog-posting-autoWrote 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/unclejobs-ai/blog-posting-auto/blog-pipeline)<a href="https://agentmods.dev/skills/unclejobs-ai/blog-posting-auto/blog-pipeline"><img src="https://agentmods.dev/badge/skills/unclejobs-ai/blog-posting-auto/blog-pipeline/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/unclejobs-ai/blog-posting-auto/blog-pipeline"><img src="https://agentmods.dev/badge/skills/unclejobs-ai/blog-posting-auto/blog-pipeline.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 | $0.00096 | $0.01664 |
| Opus 5 | $0.00048 | $0.00832 |
| Sonnet 5 | $0.00019 | $0.00333 |
| Haiku 4.5 | $0.00010 | $0.00166 |
Grade B, and why
blog-pipeline scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
- 금지표현 grep 0건: `grep -nE -f .claude/style/forbidden.patterns workspace/{RUN_ID}/draft.md` How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/blog-pipeline
블로그 글 한 편을 6단계 서브에이전트 직렬 실행으로 생성하고 Notion에 발행하는 워크플로우. Researcher가 모은 사실을 Fact-Checker가 원본 URL 재방문으로 검증, downstream(Planner/Writer/Reviewer)은 verified.md만 사실 근거로 사용.
실행 순서
오케스트레이터(메인 세션)가 다음을 순서대로 수행:
0. 준비
RUN_ID+TODAY생성: slug는 주제에서 한국어→영어 음차 또는 핵심 명사.RUN_ID="$(date +%Y%m%d-%H%M%S)-{slug}" TODAY="$(date +%Y-%m-%d)" mkdir -p workspace/$RUN_IDTODAY는 모든 서브에이전트 호출 시 prompt에 박아 전달 — Researcher 최신성 쿼리, Fact-Checker staleness 판정 기준.workspace/{RUN_ID}/meta.json초기 기록:{ "run_id": "...", "topic": "...", "today": "YYYY-MM-DD", "started_at": "ISO-8601", "stages": {} }.env존재 +NOTION_DATABASE_ID채워졌는지 확인. 없으면 사용자에게 알리고 Publisher 단계는 skip 옵션 안내.
1. Researcher
Agent(subagent_type="blog-researcher", prompt=<<<
RUN_ID: {RUN_ID}
TODAY: {TODAY} ← 최신성 쿼리 기준
TOPIC: {사용자 입력 주제}
workspace/{RUN_ID}/research.md 생성.
모든 WebSearch 쿼리에 {TODAY 연도} 또는 "최신" 키워드 포함.
각 사실에 source-date 메타 부착.
>>>)
검증: workspace/{RUN_ID}/research.md 존재 + 4KB 이상 + 각 사실에 (source-date: ...) 메타 존재.
1.5. Fact-Checker
Agent(subagent_type="blog-fact-checker", prompt=<<<
RUN_ID: {RUN_ID}
TODAY: {TODAY} ← staleness 판정 기준 (TODAY-12개월 미만 출처만 통과)
workspace/{RUN_ID}/research.md의 각 주장을 원본 URL 재방문해 검증.
time-sensitive(가격·시간·정책·버전) 사실은 source-date 12개월 초과면 rejected (stale-source).
research.verified.md + research.rejected.md 생성.
>>>)
검증:
research.verified.md존재 +research.rejected.md존재 (빈 파일이어도 OK)- stdout 통계 라인
[fact-checker] ... verified=M rejected=N-M ratio=M/N%캡처 - verified 비율 < 50% → 자동 RETRY: Researcher 재호출 (최대 2회). 그래도 50% 미만이면 사용자 결정 요청.
- verified 비율 ≥ 50%면 다음 단계 진행.
2. Planner
Agent(subagent_type="blog-planner", prompt=<<<
RUN_ID: {RUN_ID}
workspace/{RUN_ID}/research.verified.md를 읽고 plan.md 작성.
research.md는 참고만, verified에 없는 사실은 절대 사용 금지.
>>>)
검증: plan.md 존재 + 섹션 5개 이상.
3. Writer
Agent(subagent_type="blog-writer", prompt=<<<
RUN_ID: {RUN_ID}
plan.md 따라 draft.md 작성.
사실 출처는 research.verified.md만.
>>>)
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.
- 12d ago First seen · 163 lines · 96 tokens per session scan B 62f1243266d6
blog-pipeline is a skill published in the GitHub repository unclejobs-ai/blog-posting-auto (42 stars, last pushed 3mo ago), licensed MIT. It adds 96 tokens to every session and 1,664 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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