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 superamped/ai-marketing-skills --skill competitor-content-analysisgit clone --depth 1 https://github.com/superamped/ai-marketing-skillsWrote 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/superamped/ai-marketing-skills/competitor-content-analysis)<a href="https://agentmods.dev/skills/superamped/ai-marketing-skills/competitor-content-analysis"><img src="https://agentmods.dev/badge/skills/superamped/ai-marketing-skills/competitor-content-analysis/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/superamped/ai-marketing-skills/competitor-content-analysis"><img src="https://agentmods.dev/badge/skills/superamped/ai-marketing-skills/competitor-content-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00051 | $0.02391 |
| Opus 5 | $0.00026 | $0.01196 |
| Sonnet 5 | $0.00010 | $0.00478 |
| Haiku 4.5 | $0.00005 | $0.00239 |
Grade A, and why
competitor-content-analysis 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 12d 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 — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitor Content Analysis
Usage
Use before building or refreshing your content strategy — map the competitive content landscape first. Also useful for identifying content gaps and opportunities vs. a specific competitor, or understanding what's earning a competitor organic traffic and why.
Process
Step 1: Gather Inputs
Ask the user for:
- Competitor name — the company to analyze
- Competitor URL — their homepage domain
- Your product description — what you sell and who it's for (needed to assess relevance of competitor content)
- Keyword data (optional) — if the user has previously run competitor-keyword-analysis, they can provide that data. Otherwise, this skill will attempt to pull it via Keywords Everywhere MCP if connected.
Step 2: Content Inventory via Sitemap
Fetch {url}/sitemap.xml (and {url}/sitemap_index.xml if it's an index). Extract:
- Total page count by section (blog, guides, resources, docs, landing pages, etc.)
- URL patterns — how content is organized (
/blog/,/resources/,/guides/,/learn/,/glossary/,/templates/,/vs/,/alternatives/,/compare/) - Publication dates — when pages were published (if sitemap includes
<lastmod>) - Publishing velocity — how many new pages per month (recent 6 months)
If sitemap is unavailable, fall back to fetching the blog index and resource pages, then use keyword data to infer content scope from ranking URLs.
Step 3: Content Categorization
From the sitemap URLs and page fetches, categorize content into types:
| Content Type | URL Patterns to Look For | What It Signals |
|---|---|---|
| Blog posts | /blog/, /posts/ |
Core content engine — topics, frequency, depth |
| Guides / pillar pages | /guides/, /learn/, /resources/, /academy/ |
Hub-and-spoke SEO strategy, authority building |
| Comparison pages | /vs/, /compare/, /alternatives/, *-vs-*, *-alternative* |
Commercial intent capture, direct competitor targeting |
| "Best of" / listicle pages | best-*, top-* |
Category keyword capture |
| Glossary / definitions | /glossary/, /dictionary/, what-is-* |
Programmatic SEO, awareness-stage traffic |
| Templates / tools | /templates/, /tools/, /calculator/, /generator/ |
Product-led content, high-intent capture |
| Case studies | /case-studies/, /customers/, /success-stories/ |
Social proof content, bottom-of-funnel |
| Webinars / video | /webinars/, /events/, /videos/ |
Event-driven content, lead capture |
| White papers / ebooks | /whitepapers/, /ebooks/, /reports/ |
Gated content for lead gen |
| Landing pages | /solutions/, /for/, /use-cases/ |
Segment-specific or use-case-specific targeting |
| Changelog / updates | /changelog/, /updates/, /whats-new/ |
Product velocity signaling |
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.
- 12d ago First seen · 216 lines · 51 tokens per session scan A 11968e4f0b61
competitor-content-analysis is a skill published in the GitHub repository superamped/ai-marketing-skills (67 stars, last pushed 24d ago), licensed MIT. It adds 51 tokens to every session and 2,391 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.
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