Borrowing it
Nothing to install: this file belongs to Pauesome/Paid-Media-MCP. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Pauesome/Paid-Media-MCP/main/.claude/skills/competitor-teardown/SKILL.mdgit clone --depth 1 https://github.com/Pauesome/Paid-Media-MCPWrote 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/pauesome/paid-media-mcp/competitor-teardown)<a href="https://agentmods.dev/skills/pauesome/paid-media-mcp/competitor-teardown"><img src="https://agentmods.dev/badge/skills/pauesome/paid-media-mcp/competitor-teardown/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/pauesome/paid-media-mcp/competitor-teardown"><img src="https://agentmods.dev/badge/skills/pauesome/paid-media-mcp/competitor-teardown.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 | $0.00096 | $0.01677 |
| Opus 5 | $0.00048 | $0.00839 |
| Sonnet 5 | $0.00019 | $0.00335 |
| Haiku 4.5 | $0.00010 | $0.00168 |
Grade A, and why
competitor-teardown 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 — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitor Teardown — Spain
Fetches and analyses a competitor landing page to surface positioning choices, persuasion tactics, and differentiation opportunities for your account. Cross-channel — applies to Google Ads, Meta, and TikTok landing pages equally.
Required Inputs
client_id(required) — so the recommendation section can contrast the competitor against this account's positioningcompetitor_url(required) — fully qualified URL to the competitor landing or home pagepage_context(optional) — what role the page plays (Google Ads brand landing, Meta lead-gen LP, homepage, product page). If omitted, inferred from URL structure.
Fail fast on missing URL or client_id.
Account Context
If you maintain notes for the account, extract your account's:
- Value proposition and differentiation angles
- Sector compliance constraints (what the account CAN'T say — e.g. Special Ad Category restrictions, Ley 16/2011 disclosures for credit products)
- Target audience and objections
- Existing positioning language
Recommendations should contrast the competitor's positioning with this account's positioning — not produce generic "how to market" advice.
Data Collection
-
WebFetch the
competitor_url— the only data source required. Extract:- Full visible copy (headline, sub-headline, body, bullets)
- CTA text and placement (above-fold, mid-page, sticky)
- Trust signals (logos, testimonials, case studies, certifications, ratings, counts)
- Pricing (if shown) and pricing framing (monthly vs annual, free trial, money-back)
- Form fields (for lead-gen pages)
- Navigation structure and footer links (to understand product portfolio)
-
Optional: WebFetch one or two sub-pages if linked from the main page and relevant (e.g. pricing page, product page, about page). Don't cascade; keep fetch count low.
Teardown Framework
1. Value Proposition Decomposition
| Question | What to extract |
|---|---|
| What problem do they solve? | Pain language, problem agitation |
| Who is their ICP? | Explicit callouts, industry/role signals |
| What transformation do they promise? | Before/after, outcomes, results |
| What's their unique mechanism? | Proprietary method, tech, process |
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 · 176 lines · 96 tokens per session scan A 9e0fe41b5b93
competitor-teardown is a skill published in the GitHub repository Pauesome/Paid-Media-MCP (1 stars, last pushed 2mo ago), licensed MIT. It adds 96 tokens to every session and 1,677 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…