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 dalroot/agentic-seo --skill competitor-researchgit 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/skills/dalroot/agentic-seo/competitor-research)<a href="https://agentmods.dev/skills/dalroot/agentic-seo/competitor-research"><img src="https://agentmods.dev/badge/skills/dalroot/agentic-seo/competitor-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/dalroot/agentic-seo/competitor-research"><img src="https://agentmods.dev/badge/skills/dalroot/agentic-seo/competitor-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 | $0.00080 | $0.01351 |
| Opus 5.5 | $0.00032 | $0.00540 |
| Sonnet 5.5 | $0.00016 | $0.00270 |
| Haiku 4.5 | $0.00008 | $0.00135 |
Grade A, and why
competitor-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 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.
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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SEO Content: Competitor Research
Guides competitor research for SEO, content, backlinks, and positioning. Use when planning content, auditing articles, building links, or evaluating market position.
When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.
Research Types
| Type | Purpose | Output |
|---|---|---|
| Keyword/topic | Topics competitors rank for; gaps | Keyword opportunities; content ideas |
| Content | Structure, length, gaps vs top rankers | Length target; H2 structure; content gaps |
| Backlink | Link profile; sites linking to competitors | Link gap; outreach targets |
| Pricing | Competitor pricing, positioning | Pricing context; differentiation |
| SEO metrics | Organic traffic, rankings vs competitors | Benchmark; opportunity areas |
Competitor Keyword / Topic Analysis
| Method | Practice |
|---|---|
| Reverse engineering | Analyze competitor titles, H1, URL; identify topics they rank for |
| SERP overlap | Keywords with overlapping top-ranking pages → same cluster; #4–10 = opportunity |
| site: operator | site:competitor.com to see indexed pages |
| Tool | Ahrefs, Semrush—competitor keyword overlap, gap analysis |
Output: Keyword opportunities; topics competitors cover that you don't.
Competitor Content Analysis
| Element | Check |
|---|---|
| Word count | Top 10 average; length target for your content |
| H2 structure | Topics covered; structure to adopt |
| Content gaps | What top rankers cover that you miss |
| Keyword placement | Primary keyword in title, H1, first 100 words |
| Format | Lists, tables, FAQ; match or improve |
Use when: Auditing or creating articles; see article-page-generator for Research Phase integration.
Competitor Article Fetch Workflow (for Article Analysis)
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 · 127 lines · 80 tokens per session scan A 2653d8cfe159
competitor-research is a skill published in the GitHub repository dalroot/agentic-seo (25 stars, last pushed 6d ago), licensed MIT. It adds 80 tokens to every session and 1,351 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-10-26.
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