Research Synthesizer
- 210 installs
- 8 repo stars
- Updated January 22, 2026
- jmsktm/claude-settings
Consolidate scattered notes, papers, competitor pages, and interview transcripts into structured briefs, comparisons, and decision-ready summaries early in discovery.
About
Research synthesizer helps Claude ingest disparate sources—articles, docs, transcripts, and competitor intel—and output structured briefs, theme maps, and decision summaries so teams move from raw discovery to clear ideas before prototyping or building.
- Multi-source theme extraction
- Competitive and market comparison tables
- Citation-aware summary briefs
- Open questions and risk flags
- Decision-ready executive synopses
Research Synthesizer by the numbers
- 210 all-time installs (skills.sh)
- Ranked #2,792 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 2, 2026 (Skillselion catalog sync)
npx skills add https://github.com/jmsktm/claude-settings --skill research-synthesizerAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 210 |
|---|---|
| repo stars | ★ 8 |
| Last updated | January 22, 2026 |
| Repository | jmsktm/claude-settings ↗ |
What it does
Consolidate scattered notes, papers, competitor pages, and interview transcripts into structured briefs, comparisons, and decision-ready summaries early in discovery.
Files
Research Synthesizer
Synthesize insights from multiple research sources into cohesive analysis
When to Use This Skill
Use this skill when you need to:
- Analyze data and extract insights
- Conduct thorough investigation
- Synthesize complex information
Not recommended for:
- Tasks requiring creative content generation
- business operations
Quick Reference
| Action | Command/Trigger |
|---|---|
| Create research synthesizer | research synthesis |
| Review and optimize | review research synthesizer |
| Get best practices | research synthesizer best practices |
Core Workflows
Workflow 1: Initial Research Synthesizer Creation
Goal: Create a high-quality research synthesizer from scratch
Steps: 1. Discovery - Understand requirements and objectives 2. Planning - Develop strategy and approach 3. Execution - Implement the plan 4. Review - Evaluate results and iterate 5. Optimization - Refine based on feedback
Workflow 2: Advanced Research Synthesizer Optimization
Goal: Refine and optimize existing research synthesizer for better results
Steps: 1. Research - Gather relevant information 2. Analysis - Evaluate options and approaches 3. Decision - Choose the best path forward 4. Implementation - Execute with precision 5. Measurement - Track success metrics
Best Practices
1. Start with Clear Objectives Define what success looks like before beginning work.
2. Follow Industry Standards Leverage proven frameworks and best practices in research.
3. Iterate Based on Feedback Continuously improve based on results and user input.
4. Document Your Process Keep track of decisions and outcomes for future reference.
5. Focus on Quality Prioritize excellence over speed, especially in early iterations.
Checklist
Before considering your work complete:
- [ ] Objectives clearly defined and understood
- [ ] Research and discovery phase completed
- [ ] Strategy or plan documented
- [ ] Implementation matches requirements
- [ ] Quality standards met
- [ ] Stakeholders informed and aligned
- [ ] Results measured against goals
- [ ] Documentation updated
- [ ] Feedback collected
- [ ] Next steps identified
Common Mistakes
| Mistake | Why It's Bad | Better Approach |
|---|---|---|
| Skipping research | Leads to misaligned solutions | Invest time in understanding context |
| Ignoring best practices | Reinventing the wheel | Study successful examples first |
| No clear metrics | Can't measure success | Define KPIs upfront |
Integration Points
- Tools: Integration with common research platforms and tools
- Workflows: Fits into existing analysis and research workflows
- Team: Collaborates with research and analytics stakeholders
Success Metrics
Track these metrics to measure effectiveness:
- Quality of output
- Time to completion
- Stakeholder satisfaction
- Impact on business goals
- Reusability of approach
---
This skill is part of the ID8Labs Skills Marketplace. Last updated: 2026-01-07
Related skills
Setup Matt Pocock SkillsScaffold the per-repo configuration that Matt Pocock’s engineering agent skills rely on so they understand the issue tracker, triage labels, and domain documentation la495k196k
Lark AppsConnect Claude, Cursor or custom agents directly to Lark (Feishu) for messaging, document automation, approval workflows and enterprise data access.402k
CavemanSlash token usage by roughly 75% while keeping every technical detail intact when working with Claude Code, Cursor or similar agents.391k94.7k
Lark Skill MakerQuickly turn any Lark/Feishu OpenAPI call or multi-step workflow into a reusable agent skill with its own SKILL.md.386k16k
Running Claude Code Via Litellm CopilotRun Claude Code at a fraction of the cost by routing requests through LiteLLM to the GitHub Copilot Chat API.270k72
Codex PetGenerate a complete Codex Pet spritesheet and metadata from one reference image without needing an OpenAI key or Codex Pro.246k10