If Advantage+ features are in use:
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionads-metaExecute the skills CLI command in your project's root directory to begin installation:
Fetches ads-meta from agricidaniel/claude-ads and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate ads-meta. Access via /ads-meta in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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ads/references/meta-audit.md for full 46-check auditads/references/benchmarks.md for Meta-specific benchmarksads/references/scoring-system.md for weighted scoringIf Advantage+ features are in use:
If ads are in restricted categories:
ads/references/compliance.md for full requirements| EMQ Score | Status | Action |
|---|---|---|
| 8.0-10.0 | Excellent | Maintain current setup |
| 6.0-7.9 | Good | Add more customer_information parameters |
| 4.0-5.9 | Fair | Implement CAPI, improve data quality |
| <4.0 | Poor | Critical: CAPI + Enhanced Matching required |
Key parameters to maximize EMQ:
em (email): highest match rate signalph (phone): second highest match signalfn, ln (first/last name): improves match accuracyct, st, zp (city, state, zip): geographic matchingexternal_id: CRM/user ID for cross-device matching| Metric | Pass | Warning | Fail |
|---|---|---|---|
| EMQ (Purchase) | ≥8.0 | 6.0-7.9 | <6.0 |
| Dedup rate | ≥90% | 70-90% | <70% |
| CTR | ≥1.0% | 0.5-1.0% | <0.5% |
| Creative formats | ≥3 | 2 | 1 |
| Creatives per ad set | ≥5 | 3-4 | <3 |
| Learning Limited | <30% | 30-50% | >50% |
| Budget per ad set | ≥5x CPA | 2-5x CPA | <2x CPA |
Meta Ads Health Score: XX/100 (Grade: X)
Pixel / CAPI Health: XX/100 ████████░░ (30%)
Creative: XX/100 ██████████ (30%)
Account Structure: XX/100 ███████░░░ (20%)
Audience: XX/100 █████░░░░░ (20%)
META-ADS-REPORT.md: Full 46-check findings with pass/warning/failMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Solid pick for teams standardizing on skills: ads-meta is focused, and the summary matches what you get after install.
ads-meta fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
ads-meta reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend ads-meta for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added ads-meta from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: ads-meta is focused, and the summary matches what you get after install.
ads-meta fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend ads-meta for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added ads-meta from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
ads-meta has been reliable in day-to-day use. Documentation quality is above average for community skills.
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