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 mattmre/EVOKORE-MCP-PUBLIC --skill competitive-ads-extractorgit clone --depth 1 https://github.com/mattmre/EVOKORE-MCP-PUBLICWrote 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/mattmre/evokore-mcp-public/competitive-ads-extractor)<a href="https://agentmods.dev/skills/mattmre/evokore-mcp-public/competitive-ads-extractor"><img src="https://agentmods.dev/badge/skills/mattmre/evokore-mcp-public/competitive-ads-extractor/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/mattmre/evokore-mcp-public/competitive-ads-extractor"><img src="https://agentmods.dev/badge/skills/mattmre/evokore-mcp-public/competitive-ads-extractor.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 | $0.00046 | $0.01808 |
| Opus 5 | $0.00023 | $0.00904 |
| Sonnet 5 | $0.00009 | $0.00362 |
| Haiku 4.5 | $0.00005 | $0.00181 |
Grade A, and why
competitive-ads-extractor 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 7d 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.
This is a copy
100% identical to competitive-ads-extractor — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 295 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitive Ads Extractor
This skill extracts your competitors' ads from ad libraries and analyzes what's working—the problems they're highlighting, use cases they're targeting, and copy/creative that's resonating.
When to Use This Skill
- Researching competitor ad strategies
- Finding inspiration for your own ads
- Understanding market positioning
- Identifying successful ad patterns
- Analyzing messaging that works
- Discovering new use cases or pain points
- Planning ad campaigns with proven concepts
What This Skill Does
- Extracts Ads: Scrapes ads from Facebook Ad Library, LinkedIn, etc.
- Captures Screenshots: Saves visual copies of all ads
- Analyzes Messaging: Identifies problems, use cases, and value props
- Categorizes Ads: Groups by theme, audience, or format
- Identifies Patterns: Finds common successful approaches
- Provides Insights: Explains why certain ads likely perform well
How to Use
Basic Extraction
Extract all current ads from [Competitor Name] on Facebook Ad Library
Scrape ads from [Company] and analyze their messaging
Specific Analysis
Get all ads from [Competitor] focusing on their messaging
about [specific problem]. What pain points are they highlighting?
Competitive Set
Extract ads from these 5 competitors: [list].
Compare their approaches and tell me what's working.
Specific Platform
Get LinkedIn ads from [Competitor] and analyze their
B2B positioning strategy
Example
User: "Extract ads from Notion on Facebook Ad Library and tell me what messaging is working for them."
Process:
Accessing Facebook Ad Library...
Searching for: Notion
Found: 23 active ads
Extracting screenshots...
[████████████████████] 100%
Saved to: competitor-ads/notion/
- ad-001-collaboration.png
- ad-002-productivity.png
- ad-003-templates.png
...
Analyzing messaging...
Output:
# Notion Ad Analysis
## Overview
- Total Ads: 23 active
- Primary Themes: Productivity (35%), Collaboration (30%),
Templates (20%), AI Features (15%)
- Ad Formats: Static images (60%), Video (40%)
- CTA Patterns: "Try for free", "Get started"
## Key Problems They're Highlighting
1. **Scattered Information** (8 ads)
Copy: "Stop switching between 10 different tools"
Why it works: Direct pain point many teams face
2. **Meeting Overload** (5 ads)
Copy: "Replace unnecessary meetings with async updates"
Why it works: Post-COVID remote work pain point
3. **Lost Documentation** (4 ads)
Copy: "Never ask 'where is that doc?' again"
Why it works: Universal workplace frustration
## Successful Creative Patterns
### Pattern 1: Before/After Split
- Shows chaotic tool landscape → Clean Notion workspace
- Used in 6 high-performing ads
- Visual metaphor is immediately clear
### Pattern 2: Feature Showcase
- GIF of actual product usage
- Shows specific feature in 5 seconds
- Used for new features (AI, templates)
### Pattern 3: Social Proof
- "Join 20M users" messaging
- Customer logos
- Used in 4 ads targeting enterprise
## Copy That's Working
Best Headlines:
1. "Your team's knowledge, finally in one place"
→ Benefit-focused, addresses pain directly
2. "The all-in-one workspace"
→ Clear positioning, broad appeal
3. "AI that actually helps you work"
→ Addresses AI skepticism, practical angle
Best Body Copy Patterns:
- Short sentences (under 10 words)
- Focus on outcomes not features
- Include specific numbers ("Cut meetings by 50%")
## Audience Targeting Insights
Based on ad variations:
- Startup founders: Solo productivity angle
- Team leads: Collaboration and alignment
- Enterprise: Security and compliance mentions
- Students: Free plan, templates, organization
## Recommendations for Your Ads
1. **Test the "tool sprawl" pain point**
→ Strong resonance based on their ad frequency
2. **Use product screenshots over abstract visuals**
→ All their top ads show actual UI
3. **Lead with the problem, not the solution**
→ "Tired of X?" performs better than "Introducing Y"
4. **Keep copy under 100 characters**
→ Their shortest ads seem most frequent
5. **Test before/after visual formats**
→ Proven pattern in their creative
## Files Saved
- All ads: ~/competitor-ads/notion/
- Analysis: ~/competitor-ads/notion/analysis.md
- Best performers: ~/competitor-ads/notion/top-10/
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.
- 7d ago First seen · 295 lines · 46 tokens per session scan A 1f2c32ab9644
competitive-ads-extractor is a skill published in the GitHub repository mattmre/EVOKORE-MCP-PUBLIC (3 stars, last pushed 3mo ago), licensed MIT. It adds 46 tokens to every session and 1,808 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to competitive-ads-extractor, differing in 5 lines, and is treated as a copy.
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