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 PavloSEO/seohead-seotools --skill tech-auditgit clone --depth 1 https://github.com/PavloSEO/seohead-seotoolsWrote 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/pavloseo/seohead-seotools/tech-audit)<a href="https://agentmods.dev/skills/pavloseo/seohead-seotools/tech-audit"><img src="https://agentmods.dev/badge/skills/pavloseo/seohead-seotools/tech-audit/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/pavloseo/seohead-seotools/tech-audit"><img src="https://agentmods.dev/badge/skills/pavloseo/seohead-seotools/tech-audit.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 | $0.00236 | $0.02347 |
| Opus 5 | $0.00118 | $0.01174 |
| Sonnet 5 | $0.00047 | $0.00469 |
| Haiku 4.5 | $0.00024 | $0.00235 |
Grade A, and why
tech-audit scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
`curl -sL "https://$URL"` → `<meta name=generator>` (WordPress/Bitrix/Tilda with How it starts
The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tech Audit — What a Site Is Built With: Stack, Analytics, Pixels, and Widgets
Detect the technologies on a single page: which CMS or site builder it uses, which framework renders the HTML, what runs on the backend, how traffic is measured, which advertising pixels and chats are installed, who processes payments, and who protects the site. For SEO, this answers "what can actually be changed on this site," "how is traffic measured," and "how many third-party scripts weigh down the page."
This is not a manual source-code review, but a tool in the seohead toolkit
(CLI + MCP + HTTP). In MCP, it is seo_tech_detect. After one request to the page,
all further analysis is static signature matching against header, value, cookie,
html, and script. Every match includes the marker (evidence) that triggered it,
making the conclusion verifiable.
When to Use It
- "what is the site built with," "which site engine," "which CMS," "is it WordPress," "site stack";
- "which technologies," "what does the site use," "how is traffic measured," "which pixels are installed";
- "which widgets / chats / support tools," "which consent banner," "which payment systems";
- "does it use Cloudflare / protection," "who hosts the frontend (Vercel / Netlify / CloudFront)";
- checking a headless combination (CMS + Next.js/Nuxt) before a rendering audit;
- a quick competitor profile before an audit — what it uses and how it differs.
Workflow
1. Technologies on a single page — the only command:
seohead tech-detect --url https://example.com
After one request, the tool inspects the HTML, headers, cookies, and script src
attributes using ~200 built-in signatures. The response contains:
generator— the complete contents of<meta name=generator>(often includes the CMS version);technologies— each entry withcategory,evidence(the marker that identified it), andversionwhen exposed ingeneratororx-powered-by;by_category— the same technologies grouped by category;scripts_total— the total number of external scripts on the page;third_party_hosts— third-party domains from which scripts are loaded;external_db— the status of the external fingerprint database (see below);findings— plain-language conclusions assembled from the signatures.
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.
- 8d ago First seen · 143 lines · 236 tokens per session scan A c27624d60df9
tech-audit is a skill published in the GitHub repository PavloSEO/seohead-seotools (0 stars, last pushed 5d ago), licensed MIT. It adds 236 tokens to every session and 2,347 once invoked, about $0.0012 per session on Opus 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 2026-08-31.
Other skills, from other repositories
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.
geo-loop
Run one bounded eGEOagents loop iteration over a workspace domain - read the charter and fresh collector data, do ONE unit of work, write substrate artifacts, append one Timeline entry and one LOG line. Use for loop mode, /geo:loop, scheduled GEO runs, or continuous monitoring.
competitive-analysis
Analyze AI-search competitors for a query and recommend ranking strategy. Use when users ask competitor analysis, who ranks, or competitive landscape.
content-scoring
Score content against the 10 GEO criteria with evidence and prioritized fixes. Use when users ask to score, rate, evaluate, or estimate ranking strength.
validation-doctor
Check Brave Search and Chrome DevTools MCP availability and provide exact setup snippets. Use when validation dependencies are missing or uncertain.
geo-content-research
Researches what prompts people ask AI engines (ChatGPT, Gemini, Perplexity, Claude) about a product category and produces a prompts.csv artifact — a prioritized, strictly-schema'd list of the queries where the brand should be cited. Feeds the monitor workflow.