# Research Synthesis

> Synthesize user, design, market, or literature research with evidence grading, bias checks, quotes-to-insights traceability, and unknowns.

- Skill: `mphaxise/research-synthesis` (Agent Skill)
- Install (CLI): `npx skillmds@latest add mphaxise/research-synthesis`
- Raw SKILL.md: https://api.skillmd.com/api/skills/mphaxise/research-synthesis/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: mphaxise (https://skillmd.com/u/mphaxise)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/mphaxise/research-synthesis

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# Research Synthesis

Use this skill when raw research, interviews, notes, surveys, articles, or source material need to become decision-ready insight.

This is a Praneet-specific hand-port enhancement. It deepens GBrain research workflows with design-research rigor, evidence confidence, and responsible interpretation.

## Workflow

1. Define the decision the research should inform.
2. Inventory sources:
   - user interviews
   - usability notes
   - surveys or analytics
   - market sources
   - academic or web research
   - local brain pages
3. Grade evidence:
   - direct user evidence
   - observed behavior
   - self-report
   - secondary research
   - anecdote or hypothesis
4. Check bias:
   - sample bias
   - missing users
   - power dynamics
   - selection effects
   - recency and confirmation bias
5. Synthesize:
   - key insights
   - supporting quotes or evidence
   - confidence level
   - implications
   - what remains unknown
6. Save durable outputs through `reports`, `article-enrichment`, `concept-synthesis`, or `capture`.

## Guardrails

- Do not turn weak evidence into strong claims.
- Keep quotes traceable to sources and respect privacy.
- Separate participant voice from your interpretation.
- Call out when affected-user research is missing.