Transforms surface-level reading into deep learning through systematic analysis using 10+ proven thinking frameworks. Guides users from understanding to application through structured workflows.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondeep-reading-analystExecute the skills CLI command in your project's root directory to begin installation:
Fetches deep-reading-analyst from ovachiever/droid-tings 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 deep-reading-analyst. Access via /deep-reading-analyst 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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Transforms surface-level reading into deep learning through systematic analysis using 10+ proven thinking frameworks. Guides users from understanding to application through structured workflows.
User provides content
↓
Ask: Purpose + Depth Level + Preferred Frameworks
↓
┌─────────────────┬─────────────────┬─────────────────┬─────────────────┐
│ Level 1 │ Level 2 │ Level 3 │ Level 4 │
│ Quick │ Standard │ Deep │ Research │
│ 15min │ 30min │ 60min │ 120min+ │
├─────────────────┼─────────────────┼─────────────────┼─────────────────┤
│ • SCQA │ Level 1 + │ Level 2 + │ Level 3 + │
│ • 5W2H │ • Critical │ • Mental Models │ • Cross-source │
│ • Structure │ • Inversion │ • First Princ. │ • Web search │
│ │ │ • Systems │ • Synthesis │
│ │ │ • Six Hats │ │
└─────────────────┴─────────────────┴─────────────────┴─────────────────┘
Ask User (conversationally):
Default if no response: Level 2 (Standard mode) with auto-selected frameworks
Based on content type, auto-suggest:
📄 Strategy/Business articles → SCQA + Mental Models + Inversion
📊 Research papers → 5W2H + Critical Thinking + Systems Thinking
💡 How-to guides → SCQA + 5W2H + First Principles
🎯 Opinion pieces → Critical Thinking + Inversion + Six Hats
📈 Case studies → SCQA + Mental Models + Systems Thinking
Always start here regardless of depth level.
📄 Content Type: [Article/Paper/Report/Guide]
⏱️ Estimated reading time: [X minutes]
🎯 Core Thesis: [One sentence]
Structure Overview:
├─ Main Argument 1
│ ├─ Supporting point 1.1
│ └─ Supporting point 1.2
├─ Main Argument 2
└─ Main Argument 3
Key Concepts: [3-5 terms with brief definitions]
Load references/scqa_framework.md and apply:
## SCQA Structure
**S (Situation)**: [Background/context the article establishes]
**C (Complication)**: [Problem/challenge identified]
**Q (Question)**: [Core question being addressed]
**A (Answer)**: [Main solution/conclusion]
📊 Structure Quality:
- Clarity: [★★★★☆]
- Logic flow: [★★★★★]
- Completeness: [★★★☆☆]
Quick scan using references/5w2h_analysis.md:
## Information Completeness
✅ Well-covered: [What, Why, How]
⚠️ Partially covered: [Who, When]
❌ Missing: [Where, How much]
🔴 Critical gaps: [List 1-2 most important missing pieces]
Select based on depth level and user preference:
Core: Structure + SCQA + 5W2H Quick Check
Output:
Add: Critical Thinking + Inversion
Load and apply:
references/critical_thinking.md:
references/inversion_thinking.md:
## Critical Analysis
### Argument Strength: [X/10]
Strengths:
- [Point 1]
Weaknesses:
- [Point 1]
Logical fallacies detected:
- [If any]
## Inversion Analysis
🚨 How this could fail:
1. [Failure mode 1] → Mitigation: [...]
2. [Failure mode 2] → Mitigation: [...]
Missing risk factors:
- [Risk 1]
Add: Mental Models + First Principles + Systems + Six Hats
Load and apply:
references/mental_models.md:
references/first_principles.md:
references/systems_thinking.md:
references/six_hats.md:
## Multi-Model Analysis
### Mental Models Applied:
1. **[Model 1 from X discipline]**
Insight: [...]
2. **[Model 2 from Y discipline]**
Insight: [...]
3. **[Model 3 from Z discipline]**
Insight: [...]
Cross-model pattern: [Key insight from combining models]
### First Principles Breakdown:
Core assumptions:
1. [Assumption 1] → Valid: [Yes/No/Conditional]
2. [Assumption 2] → Valid: [Yes/No/Conditional]
Fundamental truth: [What remains after stripping assumptions]
### Systems Map:
[Variable A] ──reinforces──> [Variable B] ↑ | | | balances reinforces | | └─────────<────────────────┘
Leverage point: [Where small change = big impact]
### Six Hats Perspective:
🤍 Facts: [Objective data]
❤️ Feelings: [Intuitive response]
🖤 Cautions: [Risks and downsides]
💛 Benefits: [Positive aspects]
💚 Ideas: [Creative alternatives]
💙 Process: [Meta-thinking]
Add: Cross-source comparison via web_search
Use web_search to find 2-3 related sources, then:
references/comparison_matrix.md## Multi-Source Analysis
### Source 1: [This article]
S-C-Q-A: [Summary]
Key claim: [...]
### Source 2: [Found article]
S-C-Q-A: [Summary]
Key claim: [...]
### Source 3: [Found article]
S-C-Q-A: [Summary]
Key claim: [...]
## Synthesis
**Consensus**: [What all agree on]
**Divergence**: [Where they differ]
**Unique value**: [What each contributes]
**Integrated view**: [Your synthesis]
Generate based on user goal:
## Applicable Solutions
[Extract 2-3 methods from content]
## Application Plan
Problem: [User's specific issue]
Relevant insights: [From analysis]
Action steps:
1. [Concrete action with timeline]
2. [Concrete action with timeline]
3. [Concrete action with timeline]
Success metrics: [How to measure]
## Risk Mitigation (from Inversion)
Potential failure points:
- [Point 1] → Prevent by: [...]
- [Point 2] → Prevent by: [...]
## Learning Notes
Core concepts (explained simply):
1. **[Concept 1]**: [Definition + Example]
2. **[Concept 2]**: [Definition + Example]
Mental models gained:
- [Model 1]: [How it works]
Connections to prior knowledge:
- [Link to something user already knows]
## Deeper Understanding (First Principles)
Fundamental question: [...]
Core principle: [...]
## Verification Questions
1. [Question to test understanding]
2. [Question to test application]
3. [Question to test evaluation]
## Key Arguments & Evidence
[Structured extraction with page/paragraph numbers]
## Quotable Insights
"[Quote 1]" — Context: [...]
"[Quote 2]" — Context: [...]
## Critical Analysis Notes
Strengths: [For citing]
Limitations: [For balanced discussion]
## Alternative Perspectives (from Mental Models)
[What other disciplines would say about this]
## Gaps & Counterfactuals
What the article doesn't address:
- [Gap 1]
- [Gap 2]
## Decision Framework
Options presented: [A / B / C]
Multi-model evaluation:
- Economic lens: [...]
- Risk lens (Inversion): [...]
- Systems lens: [...]
## Six Hats Decision Analysis
🤍 Facts: [Objective comparison]
🖤 Risks: [What could go wrong]
💛 Benefits: [Upside potential]
💚 Alternatives: [Other options not considered]
💙 Recommendation: [Synthesized advice]
## Scenario Analysis (from Inversion)
Best case: [...]
Worst case: [...]
Most likely: [...]
Always end with:
## 🎯 Immediate Takeaways (Top 3)
1. **[Insight 1]**
Why it matters: [Personal relevance]
One action: [Specific, time-bound]
2. Make 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
pproenca/dot-skills
mattpocock/skills
Registry listing for deep-reading-analyst matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in deep-reading-analyst — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in deep-reading-analyst — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend deep-reading-analyst for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: deep-reading-analyst is focused, and the summary matches what you get after install.
deep-reading-analyst has been reliable in day-to-day use. Documentation quality is above average for community skills.
deep-reading-analyst has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: deep-reading-analyst is focused, and the summary matches what you get after install.
deep-reading-analyst fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added deep-reading-analyst from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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