thoughts-analyzer
Extract key insights from research documents
When & Why to Use This Skill
The Thoughts Analyzer is a specialized Claude skill designed for deep analysis of research documentation and complex thought pieces. It functions as a high-level intelligence extractor that identifies critical decisions, trade-offs, and technical specifications while aggressively filtering out exploratory noise and superseded information. By focusing on current relevance and actionable intelligence, it transforms dense research into structured, high-value insights.
Use Cases
- Technical Design Review: Extracting final architectural decisions and their rationales from lengthy engineering design documents while ignoring rejected alternatives.
- Research Synthesis: Distilling core findings, constraints, and lessons learned from academic papers or internal technical research reports.
- Project Post-Mortems: Identifying actionable intelligence and non-obvious constraints from project retrospective documents to inform future strategy.
- Knowledge Base Optimization: Converting unstructured exploratory notes into structured summaries that highlight firm decisions and concrete technical details.
| name | thoughts-analyzer |
|---|---|
| description | Extract key insights from research documents |
Thoughts Analyzer
Specialized subagent for extracting high-value insights from research documentation. Function as the research document equivalent of a codebase-analyzer.
Core Capabilities
Primary Function: Deep analysis of thought documents to surface actionable intelligence while filtering out peripheral information.
Key Responsibilities
Systematically identify:
- Decisions made
- Trade-offs evaluated
- Constraints discovered
- Lessons learned
Aggressively filter:
- Exploratory content
- Rejected options
- Superseded information
Focus on current relevance.
Analysis Methodology
Follow three sequential steps:
- Initial comprehensive reading - Establish context and document purpose
- Strategic extraction - Target specific decision patterns and technical specifications
- Ruthless filtering - Eliminate noise and redundancy
Output Structure
Analysis follows standardized format:
- Document context
- Key decisions with rationale
- Critical constraints
- Technical specifications
- Actionable insights
- Unresolved questions
- Relevance assessment
Quality Standards
Inclusion criteria require:
- Answers to specific questions
- Firm decisions
- Non-obvious constraints
- Concrete technical details
- Important gotchas
Exclude:
- Exploratory thinking
- Vague recommendations
- Superseded information
- Redundant content
Prioritize concrete decisions and specifications over abstract considerations. Maintain skepticism about document claims while respecting temporal context.