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 seo-researchgit 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/seo-research)<a href="https://agentmods.dev/skills/pavloseo/seohead-seotools/seo-research"><img src="https://agentmods.dev/badge/skills/pavloseo/seohead-seotools/seo-research/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/seo-research"><img src="https://agentmods.dev/badge/skills/pavloseo/seohead-seotools/seo-research.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 | $0.00104 | $0.01638 |
| Opus 5 | $0.00052 | $0.00819 |
| Sonnet 5 | $0.00021 | $0.00328 |
| Haiku 4.5 | $0.00010 | $0.00164 |
Grade A, and why
seo-research 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 10d 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Comprehensive SEO Research
Combines four research tracks into one sequential workflow: Keywords → Competitors → Search Results → Content Gaps
Quick Start
Conduct comprehensive research on [topic/product/service] for [country/language]
Analyze my site's competitors [URL] — keywords, content, and links
Analyze the search results for [keyword] — what is required to rank at the top
Find topics covered by competitors [URL1, URL2] but missing from my site [URL]
TRACK 1 — Keywords
Use when: you need to find keywords for a new page, article, or campaign.
Phases (announce each one as: [Phase X/8: Name])
- Scope — clarify the product, audience, business objective, site DR, target market, and language.
- Discovery — build a keyword set from primary, pain-point, solution-oriented, audience-specific, and industry queries.
- Variations — expand the set with modifiers and long-tail patterns.
- Classification — label intent as informational / navigational / commercial / transactional.
- Scoring — estimate difficulty (1–100) and calculate:
Opportunity = (Volume × Intent Weight) / Difficulty. Intent weights: informational=1, navigational=1, commercial=2, transactional=3. - GEO check — flag question queries, definitions, comparisons, lists, and how-to queries; they perform well in AI-generated answers.
- Clustering — group keywords into pillar and cluster hubs.
- Deliverable — Executive Summary, Quick Wins / Growth / GEO, Topic Clusters, Content Plan, Next Steps.
Intent Matrix
| Intent | User Goal | Signals | Formats |
|---|---|---|---|
| Informational | Learn | what, how, why, guide, tips, examples | Articles, tutorials, FAQs, checklists |
| Navigational | Find a specific site | brand, login, pricing, support | Homepage, product pages, documentation |
| Commercial | Evaluate options before buying | best, top, vs., comparison, reviews, alternative | Comparisons, reviews, rankings |
| Transactional | Buy or order | buy, price, discount, demo, order | Landing pages, pricing pages |
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.
- 10d ago First seen · 148 lines · 104 tokens per session scan A d801af64ef64
seo-research is a skill published in the GitHub repository PavloSEO/seohead-seotools (0 stars, last pushed 7d ago), licensed MIT. It adds 104 tokens to every session and 1,638 once invoked, about $0.0005 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 2026-08-31.
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.
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.
competitive-analysis
Analyze AI-search competitors for a query and recommend ranking strategy. Use when users ask competitor analysis, who ranks, or competitive landscape.
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.