Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Hainrixz/claude-seo-ai/plugin install claude-seo-aiWrote 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/hainrixz/claude-seo-ai/score)<a href="https://agentmods.dev/skills/hainrixz/claude-seo-ai/score"><img src="https://agentmods.dev/badge/skills/hainrixz/claude-seo-ai/score/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/hainrixz/claude-seo-ai/score"><img src="https://agentmods.dev/badge/skills/hainrixz/claude-seo-ai/score.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 | $0.00779 |
| Opus 5 | $0.00029 | $0.00390 |
| Sonnet 5 | $0.00012 | $0.00156 |
| Haiku 4.5 | $0.00006 | $0.00078 |
Grade A, and why
score 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 4d 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.
What it actually says
/claude-seo-ai:score
Recompute and show the two 0–100 scores by running the seo-score skill, which uses scripts/score.mjs for a reproducible number.
Runs live under <root>/<host>/<run-id>/, where <root> is --out › $CLAUDE_SEO_AI_HOME › ${CLAUDE_PLUGIN_DATA}/runs › ~/.claude-seo-ai/runs, and <host> is the lower-cased host with : → _ (local targets become local/<basename>-<hash>). score.mjs --run takes a directory or a findings file — it does not understand the word latest, so resolve the pointer yourself with Read before you call it: <root>/<host>/latest.json is { run, path, updated_at } and path is the absolute run directory; <root>/index.json lists every host with its latest run id.
- No argument (default): read
<root>/index.json, take the host whoselatestrun id sorts highest (run ids are UTCYYYY-MM-DDTHH-mm-ssZ, so string order is chronological), read that host'slatest.json, thennode "${CLAUDE_PLUGIN_ROOT}/scripts/score.mjs" --run <path from latest.json>. latest:<host>→ read<root>/<host>/latest.jsonand pass itspathto--run.- A run directory →
node "${CLAUDE_PLUGIN_ROOT}/scripts/score.mjs" --run <run-dir>(it reads<run-dir>/findings.json). - A findings JSON path →
node "${CLAUDE_PLUGIN_ROOT}/scripts/score.mjs" --findings <path>(add--vertical a,b,--multilingualand--environment production|preview|staging|localwhen the file carries no run context;--manifest <crawl.json>adds the site rollup,--strictexits 2 if any finding fails schema validation,--validate-onlyreports the per-finding schema verdict without scoring). - If no
index.json/latest.jsonexists, or the run has nofindings.json, tell the user to run/claude-seo-ai:audit <url>first — never score from memory.
Show both scores with bands, the per-category breakdown, any severity-gating cap (cap_reasons), the unscored state when no category is active, and the needs_api / manual_review / dropped counts. Two scores, never blended. When an axis comes back provisional: true (state: "partial"), say the band and its coverage % in the same sentence — a band built on a third of the model is not the same claim as a measured one, and the per-axis warnings[] name what was not measured. With a rollup, read pages_scored against pages_count: a page listed in unscored_pages[] did not answer 2xx, so it was never scored — name those pages and their status instead of letting the site score stand for a sample that was not measured.
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.
- 4d ago Changed · +2 lines 8ed7c82a67d6
- 6d ago Changed · +3 lines · +7 tokens per session 5e3fac527722
- 12d ago First seen · 16 lines · 51 tokens per session scan A 7efd803a436b
score is a skill published in the GitHub repository Hainrixz/claude-seo-ai (59 stars, last pushed 5d ago), licensed MIT. It adds 58 tokens to every session and 779 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 skills, from other repositories
linkedin-post
Draft a daily LinkedIn post for S M Moshiur Rahman about business development, grounded in a real problem he hit that day and real numbers from OmniRank. Use when he says "linkedin post", "today's post", "draft a post", or describes friction he wants written up.
audit
Use when asked to audit a site's SEO, check AEO or answer-engine readiness, diagnose why a page is not ranking or not being cited by AI, verify structured data, or run pre-deploy discoverability checks on built HTML.
geo-artifacts
Use when asked to generate or fix llms.txt, llms-full.txt or facts.json, make a site citable or ingestible by ChatGPT, Claude, Perplexity or Gemini, or publish machine-readable ground truth for AI crawlers.
web-optimization
Audit or generate web content optimized for traditional search (SEO), AI generative answer engines like ChatGPT/Perplexity/Google AI Overviews (GEO), and answer engines / featured snippets / voice (AEO). Use when the user asks to improve a page's ranking or AI-citability, run an SEO/GEO/AEO audit of a URL or file, add…
fire-your-seo-agency
A procedure for improving how a website appears in search engines and how AI answer systems find and cite it. It covers search, answer-engine, generative-AI, and Naver visibility.
ansvisor-aeo-coach-standalone
Standalone (no-MCP) version of the Ansvisor AEO Coach. Use this only when the user's Claude client cannot connect to the Ansvisor MCP server (e.g. claude.ai web without a Connector configured). Fetches live data from the Ansvisor REST API directly with the user's API key via code execution. For clients that support…