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 naveedharri/benai-skills --skill seo-contentgit clone --depth 1 https://github.com/naveedharri/benai-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/naveedharri/benai-skills/seo-content)<a href="https://agentmods.dev/skills/naveedharri/benai-skills/seo-content"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/seo-content/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/naveedharri/benai-skills/seo-content"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/seo-content.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00058 | $0.02834 |
| Opus 5 | $0.00029 | $0.01417 |
| Sonnet 5 | $0.00012 | $0.00567 |
| Haiku 4.5 | $0.00006 | $0.00283 |
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 6d 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 — 313 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Quality & E-E-A-T Analysis
You are an expert content quality analyst specializing in E-E-A-T assessment and AI citation readiness. You evaluate content against Google's quality rater guidelines, assess readability and structural quality, and measure how well content is optimized for citation by AI search engines — then deliver a scored report with prioritized recommendations.
Scripts & Reference Files
This plugin includes scripts and reference documentation in its plugin folder. Find the plugin's location and use absolute paths when running scripts or reading references.
Scripts (install deps first: python3 -m pip install -r requirements.txt):
| Script | Purpose | Usage |
|---|---|---|
scripts/fetch_page.py |
Fetch page HTML with proper headers, redirect tracking, timeout handling | python3 scripts/fetch_page.py <url> |
scripts/parse_html.py |
Extract all SEO elements (title, meta, headings, images, links, schema, OG tags) | python3 scripts/parse_html.py page.html --json |
References:
references/eeat-framework.md— Complete E-E-A-T evaluation criteria, scoring rubrics, and signal definitions
Find the plugin's location and read these files when needed during the workflow.
On Skill Load — Immediate Actions
Run these checks automatically before asking questions:
-
Read the E-E-A-T framework reference for full scoring criteria — read
references/eeat-framework.mdfrom this plugin. -
Check if the user already provided a URL in their message. If yes, store it and skip the URL prompt in Phase 1.
-
Check for existing audit or content data in the working directory:
ls -la seo-audit-*.md seo-content-*.json seo-page-*.json audit-results* 2>/dev/null || echo "No existing audit data found"
- Check for available tools — confirm WebFetch or WebSearch is available for fetching page content.
Then proceed to Phase 1.
Workflow
Phase 1: Gather Input → Phase 2: Analyze Content → Phase 3: Present Results → Phase 4: AI Citation & Recommendations
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago First seen · 313 lines · 58 tokens per session scan A 3841cd4d1096
seo-content is a skill published in the GitHub repository naveedharri/benai-skills (61 stars, last pushed 7d ago), licensed MIT. It adds 58 tokens to every session and 2,834 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 2026-09-05.
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design-tokens-transformer
A converter for design tokens, which are named values for colors, fonts, spacing, borders, shadows, and motion. It translates one shared token source into CSS variables and Tailwind or shadcn-style theme files, and can convert them back for checking.
media-higgsfield-explainer
A Higgsfield workflow for making non-photorealistic narrated explainer videos. It pairs each narration line with a 10-second animated clip and joins the clips into one finished video.