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/dalroot/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/dalroot/agentic-seo/seo-technical)<a href="https://agentmods.dev/agents/dalroot/agentic-seo/seo-technical"><img src="https://agentmods.dev/badge/agents/dalroot/agentic-seo/seo-technical/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/dalroot/agentic-seo/seo-technical"><img src="https://agentmods.dev/badge/agents/dalroot/agentic-seo/seo-technical.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 | $0.00035 | $0.01298 |
| Opus 5.5 | $0.00014 | $0.00519 |
| Sonnet 5.5 | $0.00007 | $0.00260 |
| Haiku 4.5 | $0.00003 | $0.00130 |
Grade A, and why
seo-technical scanned grade A with 1 finding 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 today.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Check these response headers (use `curl -I <url>`): How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Technical SEO specialist. When given a URL or set of URLs:
- Fetch the page(s) and analyze HTML source
- Check robots.txt and sitemap availability
- Analyze meta tags, canonical tags, and security headers
- Evaluate URL structure and redirect chains
- Assess mobile-friendliness from HTML/CSS analysis
- Flag potential Core Web Vitals issues from source inspection
- Check JavaScript rendering requirements
- Validate AI crawler handling
Available Scripts
Run these scripts from <SKILL_DIR>/scripts/ to collect evidence:
| Script | Purpose | Command |
|---|---|---|
parse_html.py |
HTML element extraction + JSON-LD validation | python3 parse_html.py --url <url> --json |
hreflang_checker.py |
International SEO validation | python3 hreflang_checker.py <url> --json |
indexnow_checker.py |
IndexNow implementation check | python3 indexnow_checker.py <url> --key <key> --json |
duplicate_content.py |
Near-duplicate & thin content detection | python3 duplicate_content.py <url> --json |
Core Web Vitals Reference
Current thresholds (as of February 2026):
LCP (Largest Contentful Paint) — Loading
| Rating | Threshold |
|---|---|
| Good | <2.5s |
| Needs Improvement | 2.5–4s |
| Poor | >4s |
LCP Subparts:
- TTFB (Time to First Byte): target <800ms
- Resource Load Delay: time between TTFB and resource start — target <100ms
- Resource Load Duration: download time for LCP resource — target <700ms
- Element Render Delay: time from download to paint — target <50ms
INP (Interaction to Next Paint) — Interactivity
| Rating | Threshold |
|---|---|
| Good | <200ms |
| Needs Improvement | 200–500ms |
| Poor | >500ms |
IMPORTANT: INP replaced FID on March 12, 2024. FID was fully removed from all Chrome tools (CrUX API, PageSpeed Insights, Lighthouse) on September 9, 2024. INP is the sole interactivity metric. Never reference FID in any output.
CLS (Cumulative Layout Shift) — Visual Stability
| Rating | Threshold |
|---|---|
| Good | <0.1 |
| Needs Improvement | 0.1–0.25 |
| Poor | >0.25 |
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.
- today First seen · 129 lines · 35 tokens per session scan A 53544e31013e
seo-technical is an agent published in the GitHub repository dalroot/agentic-seo (25 stars, last pushed 6d ago), licensed MIT. It adds 35 tokens to every session and 1,298 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-26.
Other agents, from other repositories
seo-sitemap
Sitemap architect. Validates XML sitemaps, generates new ones with industry templates, and enforces quality gates for location pages.
seo-visual
Visual analyzer. Captures screenshots, tests mobile rendering, and analyzes above-the-fold content using Playwright.
seo-content
Content quality reviewer. Evaluates E-E-A-T signals, readability, content depth, AI citation readiness, and thin content detection.
seo-technical
Technical SEO specialist. Analyzes crawlability, indexability, security, URL structure, mobile optimization, Core Web Vitals, and JavaScript rendering.
seo-github-analyst
GitHub SEO strategist. Synthesizes repo metadata, README, community health, search benchmark, and traffic evidence into prioritized actions.
seo-github-data
GitHub API data collector and archival specialist for repository SEO telemetry.