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 Infrasity-Labs/dev-gtm-claude-skills --skill blog-rewritegit clone --depth 1 https://github.com/Infrasity-Labs/dev-gtm-claude-skillsWrote 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/infrasity-labs/dev-gtm-claude-skills/blog-rewrite)<a href="https://agentmods.dev/skills/infrasity-labs/dev-gtm-claude-skills/blog-rewrite"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/blog-rewrite/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/infrasity-labs/dev-gtm-claude-skills/blog-rewrite"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/blog-rewrite.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 | $0.00159 | $0.04478 |
| Opus 5 | $0.00079 | $0.02239 |
| Sonnet 5 | $0.00032 | $0.00896 |
| Haiku 4.5 | $0.00016 | $0.00448 |
Grade A, and why
blog-rewrite 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 9d 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.
This is a copy
88% identical to blog-rewrite — 64 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 374 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blog Rewriter: Optimize Existing Posts
Rewrites and optimizes existing blog posts for dual ranking: Google search and AI citation platforms. Preserves the author's voice while applying the 6 pillars of optimization.
Key references:
references/quality-scoring.md- 5-category scoring (Content 30, SEO 25, E-E-A-T 15, Technical 15, AI Citation 15)references/eeat-signals.md- Experience, expertise, authority, trust markersreferences/internal-linking.md- Linking strategy and anchor text rulesreferences/visual-media.md- Image sourcing and chart stylingskills/blog/references/synthesis-contract.md- 6 LAWs for re-citation hygiene during rewrite (v1.8.0; cross-skill ref lives in the orchestrator's references dir)skills/blog/references/research-quality.md- cross-source clustering for replacement-statistic research (v1.8.0)
Cross-reference
For 21 evidence-led optimization prompts (AI-detector test, CTR audit, schema, PAA rewording, technical audit, ChatGPT visibility) directly applicable to rewrite work, see /blog flow optimize.
Workflow
Phase 1: Audit (Read-Only)
- Read the blog post - Detect format (MDX, markdown, HTML)
- Run the quality checklist against
references/quality-scoring.md:- Count fabricated vs sourced statistics
- Check answer-first formatting (H2 -> stat in first sentence?)
- Count images and charts (type diversity?)
- Measure paragraph lengths (any > 150 words?)
- Check heading hierarchy (H1 -> H2 -> H3, no skips?)
- Look for FAQ schema
- Check freshness signals (lastUpdated, dateModified)
- Assess self-promotion level
- Evaluate citation tier quality
- AI content detection scan:
- Burstiness score - Measure sentence length variance across the post. Low variance (most sentences within 3-5 words of each other) is a strong AI signal. Calculate: standard deviation of sentence word counts. Target SD > 6.
- Known AI phrase scan - Check for these high-frequency AI phrases:
- "in today's digital landscape", "it's important to note", "dive into"
- "game-changer", "navigate the landscape", "revolutionize", "seamlessly"
- "cutting-edge", "harness the power of", "leverage" (as verb)
- "delve", "crucial", "elevate", "foster", "landscape" (overused)
- "multifaceted", "robust", "tapestry", "embark"
- Full list in
agents/blog-writer.md
- Vocabulary diversity - Calculate Type-Token Ratio (TTR): unique words / total words. Low TTR (< 0.40) suggests AI-generated repetitive phrasing. Target TTR > 0.50 for natural prose.
- AI content percentage estimate - Based on burstiness, phrase density, and TTR, estimate what percentage of the content reads as AI-generated (0-100%). Report as: "AI content estimate: ~X%"
- Second-order structural reflex scan (v1.8.0) - The first-order checks above
are vocabulary-level. The second-order pass catches what survives them: structural
and rhythmic tics LLMs default to after the obvious words are replaced. Run against
skills/blog/references/ai-slop-detection.md. Flag at minimum:- Question-cadence H2s above 70% of headings
- Three or more "Here..." paragraph openers
- Three-clause sentence rhythm above 50% in any 200-word window
- More than 2 hedge words ("may," "often," "typically," "generally") in any 20-word span
- Symmetric-list bloat (list-item word-count SD below 5)
- More than 2 wrap-up rhetorical questions ("What does this mean for...?")
- More than half of H2 openers starting with a transition word
- "The key insight is..." or "What's important here is..." as sentence openers
- Listicle pre-list intro above 250 words
- Opening-word repetition: top three first-words above 25% share
- Paragraph-shape SD below 25 (visual monotony)
A draft is only "AI-detection clean" when both passes are clean. The two-namespace
terminology (first-order/second-order for slop-detection vs Tier 1/2/3 for source
authority) is intentional: see
skills/blog/references/ai-slop-detection.mdfor why the labels diverged in v1.8.1.
- Video embed check:
- Count existing YouTube embeds in the post
- If 0 embeds, flag: "No video embeds. YouTube has the strongest AI visibility correlation (0.737)"
- If present, check: lazy loading? aria-labels? noscript fallback? VideoObject schema?
- Cannibalization check:
- Identify the post's primary keyword from title, H1, and first paragraph
- Search the blog directory for other posts targeting the same keyword:
- Grep headings and meta descriptions across all blog posts
- Flag any posts with significant keyword overlap
- If cannibalization found, report:
- Which posts compete for the same keyword
- Recommend: merge (combine into one stronger post) or differentiate (shift one post to a related but distinct keyword)
- Calculate current score across 5 categories:
- Score across 5 categories (Content Quality 30, SEO Optimization 25, E-E-A-T Signals 15, Technical Elements 15, AI Citation Readiness 15)
- Total: 0-100
- Present audit summary with specific findings, AI detection results, video status, cannibalization status, and score
- Enter plan mode - Present section-by-section optimization plan
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.
- 9d ago First seen · 374 lines · 159 tokens per session scan A d85977efcf71
blog-rewrite is a skill published in the GitHub repository Infrasity-Labs/dev-gtm-claude-skills (124 stars, last pushed 2mo ago), licensed MIT. It adds 159 tokens to every session and 4,478 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to blog-rewrite, differing in 64 lines, and is treated as a copy.
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