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
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 skills add AgriciDaniel/claude-blog --skill blog-schemagit clone --depth 1 https://github.com/AgriciDaniel/claude-blogWrote 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-schema)<a href="https://agentmods.dev/skills/agricidaniel/claude-blog/blog-schema"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-blog/blog-schema/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-schema"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-blog/blog-schema.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 | $0.00073 | $0.02316 |
| Opus 5 | $0.00036 | $0.01158 |
| Sonnet 5 | $0.00015 | $0.00463 |
| Haiku 4.5 | $0.00007 | $0.00232 |
Grade A, and why
blog-schema 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 — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blog Schema: JSON-LD Structured Data Generation
Generates complete, validated JSON-LD schema markup for blog posts using the @graph pattern. Combines multiple schema types into a single script tag with stable @id references for entity linking.
Workflow
Step 1: Read Content
Read the blog post and extract all schema-relevant data:
- Title (headline)
- Author (name, job title, social links, credentials)
- Dates (datePublished, dateModified / lastUpdated)
- Description (meta description)
- FAQ section (question and answer pairs)
- Images (cover image URL, dimensions, alt text; inline images)
- Organization info (site name, URL, logo)
- Word count (approximate from content length)
- Tags/categories (for BreadcrumbList category)
- Slug (from filename or frontmatter)
Step 2: Generate BlogPosting Schema
Complete BlogPosting with recommended properties when applicable:
{
"@type": "BlogPosting",
"@id": "{siteUrl}/blog/{slug}#article",
"headline": "Concise post title",
"description": "Concise page-specific meta description",
"datePublished": "YYYY-MM-DD",
"dateModified": "YYYY-MM-DD",
"author": { "@id": "{siteUrl}/author/{author-slug}#person" },
"publisher": { "@id": "{siteUrl}#organization" },
"image": { "@id": "{siteUrl}/blog/{slug}#primaryimage" },
"mainEntityOfPage": {
"@type": "WebPage",
"@id": "{siteUrl}/blog/{slug}"
},
"wordCount": 2400,
"articleBody": "First 200 characters of content as excerpt..."
}
Google's Article structured data docs do not define required Article
properties. Include headline, datePublished, author, publisher, and
image when applicable, validate with the Rich Results Test, and treat missing
fields as warnings unless the target surface requires them. Recommended
properties: description, dateModified, mainEntityOfPage, wordCount, articleBody
(excerpt).
Step 3: Generate Person Schema
Author schema with stable @id for cross-referencing:
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 · 288 lines · 73 tokens per session scan A 32ad2c76bba9
blog-schema is a skill published in the GitHub repository AgriciDaniel/claude-blog (2,125 stars, last pushed today), licensed MIT. It adds 73 tokens to every session and 2,316 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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