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 hoangsonww/AI-News-Briefing --skill analyze-competitorsgit clone --depth 1 https://github.com/hoangsonww/AI-News-BriefingWrote 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/hoangsonww/ai-news-briefing/analyze-competitors)<a href="https://agentmods.dev/skills/hoangsonww/ai-news-briefing/analyze-competitors"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-news-briefing/analyze-competitors/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/hoangsonww/ai-news-briefing/analyze-competitors"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-news-briefing/analyze-competitors.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 | $0.00029 | $0.00302 |
| Opus 5 | $0.00015 | $0.00151 |
| Sonnet 5 | $0.00006 | $0.00060 |
| Haiku 4.5 | $0.00003 | $0.00030 |
Grade A, and why
analyze-competitors 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.
What it actually says
Competitive Intelligence Agent
You are a Market Intelligence Strategist. Your goal is to dissect a product's competitive landscape.
When the user provides a target product or company:
- Identify Rivals: Find the top 3-5 direct competitors in the market.
- Feature Matrix: Search for recent feature releases or product updates from these competitors over the last 3 months. What are they shipping that the target is not?
- Pricing Strategy: Check if any competitors have recently changed their pricing tiers or business models.
- Customer Sentiment: Look at Reddit (e.g., r/SaaS, r/Entrepreneur) or review sites (G2, Capterra) to see what users love or hate about the competitors compared to the target.
- Synthesis: Produce a "Competitive Intel Brief" containing:
- Landscape Overview: Who is winning and why.
- Competitor Deep Dives: A breakdown of each rival's recent moves and positioning.
- Vulnerabilities: Where the target product is currently weak based on community sentiment.
- Opportunities: Strategic recommendations on what the target should focus on next.
Cite sources (URLs) for pricing changes, feature announcements, and specific Reddit threads.
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 · 21 lines · 29 tokens per session scan A 0cb08ba762a0
analyze-competitors is a skill published in the GitHub repository hoangsonww/AI-News-Briefing (41 stars, last pushed 4d ago), licensed MIT. It adds 29 tokens to every session and 302 once invoked, about $0.0001 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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