Research Skill
Multi-backend research orchestrator. Routes to the cheapest effective tool for each task.
Modes
| Command | Backend | Cost | Sources | Time | Best For |
|---|---|---|---|---|---|
/research "topic" |
Researcher subagent | $0 (subscription) | 15-25 | 3-5 min | General web research |
/research --quick "topic" |
WebSearch + WebFetch (inline) | $0 | 5-8 | 1-2 min | Quick lookups |
/research --deep "topic" |
Researcher subagent (max depth) | $0 | 40-80 | 10-20 min | Comprehensive research |
/research --company "name" |
Exa company_research | Free credits | 10-15 | 2-3 min | Company/product intel |
/research --code "pattern" |
CLI agents swarm (Gemini) | $0 | N/A | 3-5 min | Code patterns, library comparison |
/research --paper "topic" |
research-paper-analyst agent | $0 | arXiv | 5-10 min | Academic papers |
/research --audit "repo/code" |
CLI agents (Gemini + Cursor) | $0-20/mo | N/A | 5-10 min | Code audit, pre-PR review |
/research --external "topic" |
CLI agents (Gemini) | $0 | Web | 3-5 min | Offload from Opus context |
/research --unified "topic" --project <name> |
Claude Web + Gemini Drive-backed dispatch | $0 | Shared Drive context | 5-15 min | Paired cross-platform research on identical inputs |
Workflow: Default Research
- Research prompt gate — before
--deepor external research dispatch, run/research-prompt-quality(CHECK-FIRST + GROUND). Do not ship flat or redundant prompts. - Check BrainLayer first —
brain_search(query)may already have what you need - Launch researcher subagent in background:
Task(subagent_type: "researcher", prompt: "Research: {topic}", run_in_background: true) - Continue working while research runs
- Read results when notified — researcher saves to
docs.local/research/[date]-[slug].md - Digest to BrainLayer if worth keeping:
brain_digest(content)then delete the file
Workflow: Quick Research (inline)
No subagent — run directly in current context:
- Run 3-5
WebSearchqueries in parallel WebFetchtop 3-5 results- Synthesize inline
- Continue working
Use when you need a quick answer, not a report.
Workflow: Company Research
For job leads, freelance prospects, meeting prep:
company_research_exa(company_name)— get company overviewweb_search_exa("company_name funding team size tech stack")— deeper intelbrain_search("company_name")— check if we've seen them before- Output structured brief:
- What they do (1 sentence)
- Tech stack / relevant tech
- Recent news / funding
- Connection to our skills
- Red flags
Workflow: Code Research
For library comparison, pattern discovery, architecture decisions:
- BrainLayer check:
brain_search("topic")— past decisions? - Exa code context:
get_code_context_exa("pattern/library")— real code examples - CLI agent (Gemini):
run.sh gemini "Compare X vs Y for [use case]"— free, detailed analysis - Optional: Cursor audit:
run.sh cursor "Review this code pattern: ..."— GPT-5.2 perspective
Workflow: External Research (offload from Opus)
When the main Claude Code session is expensive Opus and you want cheap research:
# Gemini does the research, saves to file (FREE)
~/.claude/commands/cli-agents/scripts/run.sh gemini "Research: {full prompt}" docs.local/research/$(date +%Y%m%d)-research.md
Then read the output file. Gemini is free (1K/day) and good for general research.
Workflow: Deep Research (Claude Web-quality)
For comprehensive research matching Claude Web's 463-source depth:
- Launch researcher subagent with explicit depth:
Task(subagent_type: "researcher", prompt: "COMPREHENSIVE deep research on: {topic}. Target 40+ sources. Run 25+ search queries. Cross-reference all claims.", run_in_background: true) - Supplement with CLI agents for extra perspectives:
run.sh gemini "Deep research on {topic} — focus on {angle A}" /tmp/research-gemini.md - Merge results — researcher report + Gemini output = comprehensive coverage
- Store in BrainLayer —
brain_storethe synthesis for future retrieval
Workflow: Pre-PR Audit
Extra eyes before PR loop:
- Gemini review:
run.sh gemini "Review this diff for bugs, security issues, and missed edge cases: $(git diff main..HEAD)"— free - Cursor review:
run.sh cursor "Audit this code change: ..."— GPT-5.2 perspective - Both in parallel — compare their findings
- Fix issues before pushing
Workflow: Unified Multi-Platform Research
Use this when you want Claude Web and Gemini to research the same question against the same Drive-backed context.
- Verify the project folders exist in Drive:
python3 skills/golem-powers/research/_shared/drive-paths.py ensure-project-folders <project> - Compute the shared dispatch plan:
bash skills/golem-powers/research/scripts/unified-dispatch.sh --project <project> --topic "Compare BrainLayer vs Mem0 for long-term memory" - Dispatch Claude Desktop with the shared Drive project:
/claude-desktop-research(was/claude-web-research— renamed 2026-04-30; alias active until 2026-05-30)- reads
Drive/Research/<project>/context/ - writes
Drive/Research/<project>/results/R{NN}-claude-desktop-result.md
- Dispatch Gemini with the same Drive project:
/gemini-research- reads the identical Drive folder ID for
Drive/Research/<project>/context/ - writes
Drive/Research/<project>/results/R{NN}-gemini-result.md
- Hand the paired results to
/research-ab-testwithout platform guessing.
Example:
/research --unified "Compare BrainLayer vs Mem0 for long-term memory" --project brainlayer
Unified mode is successful only when both dispatches reference the same Drive folder ID and produce pre-attributed paired result paths.
Integration Points
| System | How Research Connects |
|---|---|
/large-plan |
Research phases auto-route here. Plan scaffold includes research tasks per phase |
/architectural-conformance-audit |
Pre-R0 sprint gate: feed the research output through the audit before any sprint hooks fire. Surfaces cited counter-examples vs impl mismatches |
/gemini-research |
Gemini Deep Research and NotebookLM MCP workflows when the task needs notebook-backed synthesis |
/jobs pipeline |
Company research before applying. --company mode |
| Gems pipeline | Research-backed gem discovery via --paper mode |
| Meeting notes | Pre-meeting research on participants/companies |
| PR loops | Pre-PR code audit via --audit mode |
| BrainLayer | All research results stored for future retrieval |
Cost Summary
| Backend | Cost | Limit |
|---|---|---|
| WebSearch/WebFetch | $0 (included in subscription) | Unlimited |
| Exa | Free credits (2K one-time) | Then $5/1K |
| Gemini CLI | $0 | 1K requests/day |
| Researcher subagent | $0 (subscription) | Context window |
| Cursor CLI | $20/mo (Cursor Pro) | Unlimited |
| research-paper-analyst | $0 (subscription) | Context window |
Default stack is 100% free: WebSearch + Exa free credits + Gemini CLI.
Output Location
| Type | Location |
|---|---|
| Quick research | Inline (no file) |
| Standard research | /tmp/research-[slug].md (ephemeral) |
| Worth keeping | docs.local/research/[date]-[slug].md |
| BrainLayer | Auto-stored via brain_store |
Future: n8n Deep Research Pipeline
When n8n orchestrator is set up (packages/orchestrator), add:
- Scheduled research (e.g., weekly job market scan)
- 400+ source deep research via recursive search loops
- Automated BrainLayer ingestion of research results
- Research templates (company intel, tech comparison, market scan)
Template exists: n8n deep research workflow