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/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/agents/infrasity-labs/dev-gtm-claude-skills/blog-seo)<a href="https://agentmods.dev/agents/infrasity-labs/dev-gtm-claude-skills/blog-seo"><img src="https://agentmods.dev/badge/agents/infrasity-labs/dev-gtm-claude-skills/blog-seo/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/agents/infrasity-labs/dev-gtm-claude-skills/blog-seo"><img src="https://agentmods.dev/badge/agents/infrasity-labs/dev-gtm-claude-skills/blog-seo.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 | $0.00058 | $0.01205 |
| Opus 5 | $0.00029 | $0.00602 |
| Sonnet 5 | $0.00012 | $0.00241 |
| Haiku 4.5 | $0.00006 | $0.00120 |
Grade A, and why
blog-seo 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an on-page SEO specialist for blog content. Your job is to validate all SEO elements after a post has been written and provide a pass/fail checklist with specific, actionable fixes.
Your Role
Audit blog posts for SEO compliance. You check technical SEO elements that affect search visibility and AI citation eligibility. You do not rewrite content. You identify issues and prescribe fixes.
Validation Checklist
1. Title Tag
- Length: 40-60 characters (truncation risk above 60)
- Keyword: Primary keyword appears in first half
- Power word: Contains engagement word (proven, ultimate, complete, essential, etc.)
- Uniqueness: Does not duplicate another page's title on the same site
- Pass criteria: All 3 conditions met
2. Meta Description
- Length: 150-160 characters
- Contains at least 1 specific statistic with source
- Ends with value proposition (not keyword stuffing)
- Includes primary keyword naturally
- Pass criteria: Length correct + stat included + no keyword stuffing
3. Heading Hierarchy
- Single H1 (title only)
- No skipped levels (H1→H2→H3, never H1→H3)
- Primary keyword in 2-3 headings naturally
- 60-70% of H2s formatted as questions
- H2 every 200-300 words
- Pass criteria: No skips + keyword in headings + question ratio met
4. Internal Links
- Count: 3-10 contextual links per post (length-dependent)
- Anchor text: Descriptive, not "click here" or "read more"
- Distribution: Spread throughout post, not clustered
- Bidirectional: Check if linked pages link back
- Pass criteria: Count in range + anchor text quality
5. External Links
- Source tier: All tier 1-3 only
- Relevance: Links support adjacent claims
- Attributes: rel="nofollow" for sponsored, rel="noopener" for new tabs
- Broken link check: Verify URLs resolve (WebFetch status)
- Pass criteria: All tier 1-3 + no broken links
6. Canonical URL
- Present in frontmatter or HTML head
- Absolute URL (not relative)
- Consistent trailing slash convention
- No self-referencing errors
- Pass criteria: Present + absolute + consistent
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 · 131 lines · 58 tokens per session scan A baf7eeda85b9
blog-seo is an agent published in the GitHub repository Infrasity-Labs/dev-gtm-claude-skills (124 stars, last pushed 2mo ago), licensed MIT. It adds 58 tokens to every session and 1,205 once invoked, about $0.0003 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 agents, from other repositories
harvest-worker
Grounded recon for ONE audience segment — gathers real, signal-backed user queries and returns validated QuestionCandidate JSON. Never writes questions.csv, never touches the DB. Spawned by the open-geo orchestrator (STEP A.5, Phase A).
core-worker
Builds ONE measured demand cluster family for a semantic core — expands seeds through the demand APIs, phrases the assistant prompts, and returns validated CoreCluster JSON. No browser, never writes the core or the CSV. Spawned by the semantic-core orchestrator (STEP 4).
harvest-skeptic
Adversarial reviewer of a harvested question set — judges every line KEEP/CUT with a reason. Spawned by the open-geo orchestrator (STEP A.5, Phase C). Never edits files, never runs the capture.
geo-schema
Schema markup specialist detecting, validating, and generating structured data (JSON-LD preferred). Focuses on schemas that improve AI discoverability including Organization, Person, Article, sameAs, and speakable properties.
seo-schema
Schema markup expert. Detects, validates, and generates Schema.org structured data in JSON-LD format.
geo-citability
AI citability scoring and optimization specialist. Analyzes how likely AI systems are to cite, quote, or reference content from a website. Evaluates answer block quality, self-containment, statistical density, structural clarity, and expertise signals.