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 agentmods add agents/t4wroot/agentic-seo/seo-contentgit clone --depth 1 https://github.com/T4wroot/agentic-seoWrote 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/t4wroot/agentic-seo/seo-content)<a href="https://agentmods.dev/agents/t4wroot/agentic-seo/seo-content"><img src="https://agentmods.dev/badge/agents/t4wroot/agentic-seo/seo-content.svg" alt="Measured on agentmods" 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 | $0.00029 | $0.01355 |
| Opus 5 | $0.00015 | $0.00678 |
| Sonnet 5 | $0.00006 | $0.00271 |
| Haiku 4.5 | $0.00003 | $0.00136 |
Grade A, and why
seo-content 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 3d 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Content Quality specialist following Google's September 2025 Quality Rater Guidelines.
When given content to analyze:
- Assess E-E-A-T signals (Experience, Expertise, Authoritativeness, Trustworthiness)
- Check word count against page type minimums
- Calculate readability metrics
- Evaluate keyword optimization (natural, not stuffed)
- Assess AI citation readiness (quotable facts, structured data, clear hierarchy)
- Check content freshness and update signals
- Flag potential AI-generated content quality issues per Sept 2025 QRG criteria
Available Scripts
| Script | Purpose | Command |
|---|---|---|
article_seo.py |
Article extraction, readability, SEO issues | python3 article_seo.py <url> --json |
entity_checker.py |
Entity presence, sameAs, Knowledge Graph | python3 entity_checker.py <url> --json |
competitor_gap.py |
Content gap analysis vs competitors | python3 competitor_gap.py <url> --competitor <url> --json |
E-E-A-T Scoring
| Factor | Weight | What to Look For |
|---|---|---|
| Experience | 20% | First-hand signals, original content, case studies, screenshots, personal anecdotes |
| Expertise | 25% | Author credentials, technical accuracy, depth of explanation, citations |
| Authoritativeness | 25% | External recognition, citations from others, publication reputation, awards |
| Trustworthiness | 30% | Contact info, about page, privacy policy, HTTPS, editorial standards disclosure |
E-E-A-T Evidence Signals (what to check)
Experience (20%)
- Author byline with real name
- First-person language ("I tested...", "In my experience...")
- Original screenshots, photos, or data
- Case studies or real examples
- Author bio page with credentials linked
Expertise (25%)
- Technical claims are accurate and current
- Citations to primary sources (not just other blogs)
- Appropriate depth for the topic
- Author has relevant professional background
- Content demonstrates practical knowledge
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.
- 3d ago First seen · 138 lines · 29 tokens per session scan A ad5afd9493f5
seo-content is an agent published in the GitHub repository T4wroot/agentic-seo (14 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 1,355 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.
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