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 shaan-ad/pm-os --skill competitive-intelgit clone --depth 1 https://github.com/shaan-ad/pm-osWrote 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/shaan-ad/pm-os/competitive-intel)<a href="https://agentmods.dev/skills/shaan-ad/pm-os/competitive-intel"><img src="https://agentmods.dev/badge/skills/shaan-ad/pm-os/competitive-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/shaan-ad/pm-os/competitive-intel"><img src="https://agentmods.dev/badge/skills/shaan-ad/pm-os/competitive-intel.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 | $0.00038 | $0.01594 |
| Opus 5.5 | $0.00015 | $0.00638 |
| Sonnet 5.5 | $0.00008 | $0.00319 |
| Haiku 4.5 | $0.00004 | $0.00159 |
Grade A, and why
competitive-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 1mo 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 — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitive Intel
You research a competitor and produce a structured battlecard. You use web fetching and search to gather data, then cross-reference against the user's own product strategy.
Before Running
- Check that
knowledge/exists. If not, tell the user: "No knowledge base found. Run/pm-setupfirst." - Read
knowledge/pm-context.mdfor product context. - Read
knowledge/okrs.mdfor current objectives. - Check if
knowledge/strategy.mdexists and read it if so.
Step 1: Identify the Competitor
Ask: "Which competitor do you want to research? Share a URL or company name."
If they provide a URL: Note it and proceed to research.
If they provide a name: Use WebSearch to find their website URL, then confirm with the user.
If they mention a competitor already in knowledge/competitors/: Ask if they want to update the existing battlecard or start fresh.
Step 2: Research
Gather data from multiple sources. Use the tools available to you, and skip gracefully if any tool is unavailable.
2a: Website Analysis
Use WebFetch to retrieve:
- Homepage: Company positioning, tagline, hero messaging, target audience
- Pricing page (usually
/pricing): Plans, pricing model, feature tiers - Features page (usually
/featuresor/product): Feature list, categories, flagship capabilities - About page (usually
/about): Company story, team size, mission, investors - Blog (usually
/blog, first page): Recent posts, content themes, product announcements
For each page:
- If
WebFetchsucceeds, extract the relevant information - If
WebFetchfails or is unavailable, note it and move on. Do not block the entire skill.
2b: Web Search
Use WebSearch for:
- "{company name} funding round" : Recent funding, valuation
- "{company name} reviews {current year}" : Customer sentiment on G2, Capterra, Reddit
- "{company name} vs {user's product name}" : Direct comparisons
- "{company name} news" : Recent announcements, partnerships, acquisitions
- "{company name} product launch" : Recent feature releases
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.
- 1mo ago First seen · 170 lines · 38 tokens per session scan A 40001fa81cf8
competitive-intel is a skill published in the GitHub repository shaan-ad/pm-os (31 stars, last pushed 6mo ago), licensed MIT. It adds 38 tokens to every session and 1,594 once invoked, about $0.0002 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 2026-08-30.
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