claude-blog is a Claude Code skill suite for planning, writing, optimizing, auditing, localizing, and refreshing blog content. It is for content and SEO workflows that produce articles and related publishing artifacts while checking drafts against defined delivery criteria. The catalogue entries provide the skills, agents, plugins, and instruction used by this workflow.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/AgriciDaniel/claude-blognpx agentmods add skills/agricidaniel/claude-blog/blog-auditWrote 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/agricidaniel/claude-blog/blog-audit)<a href="https://agentmods.dev/skills/agricidaniel/claude-blog/blog-audit"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-blog/blog-audit/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/agricidaniel/claude-blog/blog-audit"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-blog/blog-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00083 | $0.02311 |
| Opus 5 | $0.00042 | $0.01156 |
| Sonnet 5 | $0.00017 | $0.00462 |
| Haiku 4.5 | $0.00008 | $0.00231 |
Grade A, and why
blog-audit 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.
How it starts
The opening of the file, as written. The whole thing — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blog Audit: Full-Site Health Assessment
Performs a comprehensive blog health assessment across all posts in the project. Scans for quality scores, orphan pages, topic cannibalization, stale content, and AI citation readiness. Uses the canonical analyzer JSON as the score source and produces a prioritized action queue.
Audit Process
Step 1: Discover Blog Files
Scan the project for all blog content files:
- Recursively glob for
.md,.mdx,.html,.astro,.svelte,.vue,.tsx, and.jsxin common blog directories and CMS export folders - Common paths to check:
content/posts/blog/src/content/_posts/pages/blog/articles/content/blog/**- CMS export folders explicitly provided by the user
src/pages/blog/
- Filter out hidden, vendor, generated, and secret-adjacent paths:
.git/, dot-directories,node_modules/,vendor/,dist/,build/,.next/,coverage/,reports/, generated exports, README, CHANGELOG, LICENSE, config files, SKILL.md, package files,.env*, keys, and private notes - Report: "Found N blog files in [directories]"
If no blog files are found in standard locations, ask for an allow-listed root or only search user-approved content directories. Do not scan the entire project root by default.
Step 2: Canonical Batch Analysis
Run canonical analyzer output first and use it as the source of per-post scores:
python3 scripts/analyze_blog.py <blog-root> --batch --format json
Process files in chunks, cap parallel follow-up work to a small fixed number,
respect context limits, and aggregate deterministic JSON with file, score,
categories, issues, and metadata. Layer the site-wide checks below on top
of analyzer JSON, not separate scoring rubrics.
Content Quality Layer
- Score each post on the 30-point content quality scale
- Check paragraph length (target 40-80 words, hard limit 150)
- Check sentence length (target 15-20 words)
- Evaluate heading structure and question-format headings
- Assess readability using persona and content type: consumer content favors easier bands, professional content can be moderate, and technical content may be denser when clarity remains high
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 · 255 lines · 83 tokens per session scan A 8ea0121c0daf
blog-audit is a skill published in the GitHub repository AgriciDaniel/claude-blog (2,116 stars, last pushed 7d ago), licensed MIT. It adds 83 tokens to every session and 2,311 once invoked, about $0.0004 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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