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 hyperfx-ai/marketing-skills --skill competitor-intelgit clone --depth 1 https://github.com/hyperfx-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/hyperfx-ai/marketing-skills/competitor-intel)<a href="https://agentmods.dev/skills/hyperfx-ai/marketing-skills/competitor-intel"><img src="https://agentmods.dev/badge/skills/hyperfx-ai/marketing-skills/competitor-intel/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/hyperfx-ai/marketing-skills/competitor-intel"><img src="https://agentmods.dev/badge/skills/hyperfx-ai/marketing-skills/competitor-intel.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 | $0.00107 | $0.03732 |
| Opus 5 | $0.00053 | $0.01866 |
| Sonnet 5 | $0.00021 | $0.00746 |
| Haiku 4.5 | $0.00011 | $0.00373 |
Grade A, and why
competitor-intel 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitor Intel
End-to-end competitor research and monitoring. Define the set, pull from every public surface that matters, diff against last run (or your own), and produce a brief that's actually useful — battle card, weekly digest, board update, or comparison-page input.
Out of scope — defer to other skills
| Request | Send them to |
|---|---|
| Competitor paid ads (Facebook / Instagram active ads) | meta-ads-library |
| Pure SEO / keyword research with HyperSEO as the primary surface | seo-research — uses the same HyperSEO toolkit but goes much deeper on keyword work |
| Generating creative (images / copy) for a comparison campaign once the intel is in | ad-creative-generation |
| Pulling data from competitor email programs | Not feasible — opt-in only. Use firecrawl_urls_scrape on their landing pages instead. |
competitor-intel is the integration layer — it pulls from every source and synthesizes. It uses HyperSEO for the rank/backlink/intersection slice but isn't the SEO research skill itself.
Requirements
- Hyper MCP installed and connected. https://app.hyperfx.ai/mcp
- At least one of these toolkits connected at https://app.hyperfx.ai/apps:
- Firecrawl (highly recommended — backbone for any site/blog/pricing-page work)
- HyperSEO (needed for rank, backlink, domain-overlap analysis)
- Apify scrapers — Instagram, TikTok, LinkedIn, Twitter, Reddit, Google search, Google Trends
- Image generation (optional — only if the brief feeds a comparison-page or battle-card asset downstream)
If none of those tool prefixes appear in the agent's tool list (firecrawl_*, hyperseo_*, scrape_instagram*, scrape_tiktok*, search_tweets, scrape_reddit*, search_google_results, scrape_google_trends, web_scrape_page), stop and tell the user to enable the Hyper MCP and connect at least Firecrawl + one social scraper. The LinkedIn scraper (scrape_linkedin_profiles) is only present when that specific integration is enabled — gracefully skip the LinkedIn slice if it's missing rather than failing the whole brief.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 225 lines · 107 tokens per session scan A 02cbee2946c4
competitor-intel is a skill published in the GitHub repository hyperfx-ai/marketing-skills (85 stars, last pushed 15d ago), licensed MIT. It adds 107 tokens to every session and 3,732 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 2026-08-30.
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