Research

Research Tool Selection

Pick the right tool for the query type:

See .claude/rules/search-tools.md for the full tool routing guide. Research-specific additions:

If Context7 isn't configured, fall back to WebSearch + WebFetch. Don't block on missing tools.

Phase 2: Research Dispatch

Launch up to 3 parallel Haiku subagents for data gathering. Each agent returns structured findings.

Agent A: Community Research (Haiku)

Search for community discussion, questions, and solutions on the topic.

Reddit (use Reddit MCP tools):

• search_reddit with the topic across: r/ClaudeCode, r/LocalLLaMA, r/ClaudeAI, r/MachineLearning
• For top 3-5 posts by relevance, fetch full threads with get_post_details (include comments)
• Note: upvote counts, comment counts, recurring questions, contradicting answers

Hacker News / Dev Blogs (use WebSearch):

• Search the topic on Hacker News, dev blogs, GitHub Discussions
• 3-angle minimum (3 distinct search queries before reporting sparse results)

Return format:

## Community Sources
- [Source title](URL) — [1-sentence summary of the key finding] — [N upvotes/comments]
- ...

## Key Themes
- [Theme 1]: [what the community says]
- [Theme 2]: [what the community says]

## Contradictions
- [Source A] says X, but [Source B] says Y

Agent B: Documentation & Expert Research (Haiku)

Search for authoritative sources: official docs, research papers, expert blog posts.

Context7 for library/framework docs:

• If topic involves a known library, resolve-library-id → query-docs
• If miss or not a library topic, skip to WebSearch

WebSearch for:

• Official documentation on the topic
• Blog posts from recognized practitioners
• GitHub repos/issues with relevant implementations

Return format:

## Authoritative Sources
- [Source title](URL) — [Verified/Single-source] — [1-sentence finding]
- ...

## Technical Details
- [Key technical finding with citation]
- ...

Agent C: Local Research (Haiku)

Search [Your Name]'s workspace for first-party experience on the topic.

Search in:

• Documents/Field-Notes/ — briefings, retros, research notes
• Documents/Content-Pipeline/00-Seeds/ — session-mined seeds
• .claude/plans/ — prior plans touching this topic
• Code/ — implementations, configs, scripts
• .claude/ — skills, rules, agents (the Jules infrastructure itself)

Return format:

## First-Party Experience
- [File path] — [what [Your Name]'s setup does differently]
- ...

## Production Data Points
- [Specific metric, config, or outcome from the codebase]
- ...

Phase 3: Source Synthesis

Use a Sonnet subagent to merge all research outputs. The synthesis agent should:

1. Deduplicate sources across agents
2. Categorize findings: consensus views, contradicting positions, coverage gaps
3. Identify where [Your Name]'s production experience adds something the internet doesn't have
4. Flag sources older than 6 months as potentially stale

Present a brief summary to [Your Name]:

Found N sources across community/docs/local. Key tension: [main disagreement]. Your edge: [what your setup reveals that others don't have]. Proceeding to draft — say "show sources" to review the full inventory.

Save the full source inventory alongside the research document.

Source review is opt-in. Don't wait for approval unless [Your Name] asks to see sources. Proceed to drafting.

Phase 4: Report Drafting

Draft a structured research report using a Sonnet subagent with:

1. The synthesized research from Phase 3
2. The report template from references/report-template.md (if available)
3. Technical register — practitioner voice, not academic
4. A critical constraint: the "What I Think" section MUST reference specific files, configs, metrics, or experiences from [Your Name]'s actual setup (from Agent C's findings). No generic observations dressed up as personal experience.

Phase 5: Voice Check

Review the draft for AI writing patterns:

• Opening and close get full [Your Name] voice treatment (problem-I-hit opener, wry close)
• Analytical middle can be more informational (findings are data, not personality)
• Check against anti-patterns: em-dashes, hedge words, preamble, corporate chatbot

Phase 6: Save + Present

1. Write the finished report to Documents/Field-Notes/Research/YYYY-MM-DD-<Topic-Slug>.md

2. Save research artifacts alongside:

   • Documents/Field-Notes/Research/<Topic-Slug>/sources.md — full source inventory
   • Documents/Field-Notes/Research/<Topic-Slug>/research-notes.md — merged subagent outputs

3. Present a 3-5 bullet summary of key findings.

4. Offer chain options when appropriate:

   • "This is starting to look like a decision. Want to run /think?"
   • "There's enough here to scope an implementation. Want to run /build?"
   • "Ready to turn this into content? Want to run /write?"
   • "Want to go deeper on [specific sub-topic]?"
   • "I'll save this — pick it up later with 'continue research on [topic]'."

Don't push chaining. Offer it once. [Your Name] decides.

Model Guidance