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.
git clone --depth 1 https://github.com/shdsjh123-cpu/claude-code-blog-builderWrote 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/commands/shdsjh123-cpu/claude-code-blog-builder/blog-publish-ready)<a href="https://agentmods.dev/commands/shdsjh123-cpu/claude-code-blog-builder/blog-publish-ready"><img src="https://agentmods.dev/badge/commands/shdsjh123-cpu/claude-code-blog-builder/blog-publish-ready/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/commands/shdsjh123-cpu/claude-code-blog-builder/blog-publish-ready"><img src="https://agentmods.dev/badge/commands/shdsjh123-cpu/claude-code-blog-builder/blog-publish-ready.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 | $0.00024 | $0.00512 |
| Opus 5 | $0.00012 | $0.00256 |
| Sonnet 5 | $0.00005 | $0.00102 |
| Haiku 4.5 | $0.00002 | $0.00051 |
Grade A, and why
blog-publish-ready scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
"$ARGUMENTS" 글을 발행 직전 상태로 최종 검증합니다.
아래 체크리스트를 하나씩 검사하고, 각 항목을 PASS/FAIL/REVIEW 로 표시하세요:
1. 수치 사실 확인
post.md에서 숫자·수치를 모두 추출- 각 숫자가
knowledge/brand-facts.md또는knowledge/conversion-benchmarks.md에 있는지 확인 - 없는 수치는 FAIL (픽션 금지)
2. 금칙어·최상급
knowledge/banned-words.json로드- 본문에서 superlatives / medical_law / ai_cliches 탐지
- 하나라도 있으면 FAIL + 위치 지적
3. 의료법 (병원·시술 키워드일 때만)
- 키워드에 "병원·시술·필러·보톡스·피부·성형·치과·한의원·의원·성과·효과" 등이 있으면
medical-law-checker서브에이전트 호출 권장
4. 이미지 4장 존재 확인
images/thumbnail.pngimages/infographic.pngimages/quote-card.pngimages/process.png- 파일 크기가 10KB 미만이면 생성 실패 가능성 → REVIEW
5. 외부 링크 0건
post.html에서http://,https://탐지- 있으면 FAIL
6. 품질·유사도 재실행
scripts/quality-check.js+scripts/duplicate-check.js- 전 항목 PASS 여야 함
7. metadata.json / guide.md 존재
- 없으면 FAIL
8. output/_index.json 반영
- 해당 글이
posts[]에 있는지 - 없으면 추가
최종 보고
사용자에게 체크리스트 결과를 표로 제시하고, FAIL/REVIEW 항목만 수정 방향 제안. 모든 항목 PASS면 "발행 준비 완료 — 스마트에디터에서 수동 업로드하세요" 안내.
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 · 49 lines · 24 tokens per session scan A 8277fc2ccaf8
blog-publish-ready is a command published in the GitHub repository shdsjh123-cpu/claude-code-blog-builder (22 stars, last pushed 5mo ago), licensed MIT. It adds 24 tokens to every session and 512 once invoked, about $0.0001 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 commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.