Research Synthesis

When to Use

Use when:

• User claims need supporting data
• Need recent examples/trends
• Looking for citations or authoritative sources
• Extracting info from specific URLs
• Checking technical docs or library APIs
• Filling knowledge gaps during brainstorming/drafting

Skip when:

• Info clearly from personal experience
• User says "don't research, just write"
• Topic is purely opinion-based

Evidence Comes From Tool Results

Every statistic, study, company example, spec, and quote you add to the braindump comes from a tool result in this session, with its source attached. Training-data recall is not a source for a published post. When you find nothing: say so and offer to research ("I don't have data on OKR failure rates. Should I research this?") rather than filling the gap.

Research Tool Selection (Priority Order)

Priority 1: Built-in Tools (Always Try First)

Priority 2: Parallel Search (Advanced Synthesis)

Priority 3: Context7 (Technical Docs)

Decision tree:

Need research?
├─ Specific URL? → WebFetch → Parallel Search
├─ Technical docs/APIs? → Context7
├─ General search? → WebSearch → Parallel Search
└─ Complex synthesis? → Parallel Search

Rationale: Built-in tools (WebFetch, WebSearch) are faster and always available. Parallel Search provides advanced agentic mode for synthesis and deep content extraction. Context7 for official docs only.

Synthesizing Findings

Patterns, Not Lists

❌ Bad (data dump):

Research shows:
- Stat 1
- Stat 2
- Stat 3

✅ Good (synthesized narrative):

Found pattern: 3 recent studies show 60-70% OKR failure rates.
- HBR: 70% failure, metric gaming primary cause
- McKinsey: >100 OKRs correlate with diminishing returns
- Google: Shifted from strict OKRs to "goals and signals"

Key insight: Failure correlates with treating OKRs as compliance exercise.

Look For

• Patterns: What do multiple sources agree on?
• Contradictions: Where do sources disagree?
• Gaps: What's missing?
• Surprises: What's unexpected or counterintuitive?

Source Attribution Format

## Research

### OKR Implementation Failures
60-70% failure rate (HBR, McKinsey). Primary causes: metric gaming, checkbox compliance.

**Sources:**
- HBR: "Why OKRs Don't Work" - 70% fail to improve performance
- McKinsey: Survey of 500 companies
- Google blog: Evolution of goals system

**Key Quote:**
> "When OKRs become performance evaluation, they stop being planning."
> - John Doerr, Measure What Matters

Integration with Conversation

Research flows naturally into conversation:

Proactive: "That's a strong claim - checking... [uses tool] Three studies support it. Adding to braindump."

Requested: "Find X... [uses tool] Found several cases. Should I add all to braindump or focus on one approach?"

During Drafting: "Need citation... [uses tool] Found supporting research. Adding to draft with attribution."

Adding to Braindump

Always ask before updating (unless context is clear): "Found X, Y, Z. Add to braindump under Research?"

Update sections:

• Research: Studies, data, citations
• Examples: Concrete cases and stories
• Quotes: Notable quotations with attribution
• Sources: Full references

Quality Checklist

Before adding to braindump:

• Synthesized into narrative, not just listed
• Source attribution included
• Relevance to core argument clear
• Key insights/patterns highlighted
• Contradictions/gaps noted if relevant

Common Pitfalls

1. Information overload: Synthesize 3-5 key findings, not 20 sources
2. Missing attribution: Always cite for later reference
3. Irrelevant research: Found ≠ useful
4. Breaking flow: Don't interrupt creative flow for minor fact-checks
5. Uncritical acceptance: Note when sources disagree/have limitations

Integration with Other Skills

• brainstorming: Research validates/challenges ideas
• blog-writing: Provides citations and examples
• Throughout: Update braindump.md with structured findings

For detailed examples, see reference/examples.md