mirror of
https://github.com/basicmachines-co/basic-memory
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4bfec8a88e
New capability to research topics and save structured reports: /research command: - /research <topic> [folder] - Investigates using web search, codebase search, and existing notes - Produces structured report with findings and analysis - Saves to research/ folder by default research skill (model-invoked): - Triggers on "research", "investigate", "look into", "explore" - Gathers information from multiple sources - Synthesizes findings into actionable reports - Links to sources and related notes Report structure: - Summary and research question - Key findings with evidence - Analysis and recommendations - Open questions and sources - Observations and relations for knowledge graph 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> Signed-off-by: phernandez <paul@basicmachines.co>
141 lines
2.6 KiB
Markdown
141 lines
2.6 KiB
Markdown
---
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description: Research a topic and save a structured report to Basic Memory
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argument-hint: <topic> [folder]
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allowed-tools: mcp__basic-memory__write_note, mcp__basic-memory__search_notes, mcp__basic-memory__read_note, mcp__basic-memory__build_context, WebSearch, WebFetch, Grep, Glob, Read
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---
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# Research
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Research a topic thoroughly and produce a structured report saved to Basic Memory.
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## Arguments
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- `$1` - Topic to research (required)
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- `$2` - Folder to save report (optional, default: "research")
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## Your Task
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Conduct thorough research on: **$ARGUMENTS**
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### 1. Check Existing Knowledge
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First, see what we already know:
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```python
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mcp__basic-memory__search_notes(query="$1", project="main")
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```
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Read any relevant existing notes to avoid duplicating research.
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### 2. Gather Information
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Depending on the topic, use appropriate tools:
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**For codebase topics:**
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- Search code with Grep/Glob
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- Read relevant files
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- Check tests for examples
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**For external topics:**
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- Use WebSearch for current information
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- Fetch documentation with WebFetch
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- Look for official sources
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**For Basic Memory context:**
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- Build context from related notes
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- Check for prior decisions or research
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### 3. Analyze Findings
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Synthesize what you learned:
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- Identify key concepts
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- Note patterns and trade-offs
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- Form recommendations if applicable
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- Flag uncertainties
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### 4. Produce Report
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Create a structured report with this format:
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```markdown
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---
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title: "Research: [Topic]"
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type: research
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tags:
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- research
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- [relevant-tags]
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---
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# Research: [Topic]
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## Summary
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[2-3 sentence executive summary]
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## Research Question
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[What we investigated and why]
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## Key Findings
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### [Finding 1]
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[Details and evidence]
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### [Finding 2]
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[Details and evidence]
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### [Finding 3]
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[Details and evidence]
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## Analysis
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[Synthesis, patterns, trade-offs, recommendations]
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## Open Questions
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- [Areas needing more investigation]
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## Sources
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- [Links to sources]
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- [[Related Notes]] from Basic Memory
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## Observations
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- [finding] Key insight #research
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- [recommendation] Suggested approach based on research
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## Relations
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- researches [[Topic]]
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- relates-to [[Related Concepts]]
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```
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### 5. Save Report
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```python
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mcp__basic-memory__write_note(
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title="Research: $1",
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content="[report content]",
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folder="$2" or "research",
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tags=["research", ...],
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project="main"
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)
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```
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### 6. Present Summary
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After saving, present:
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- Key findings summary
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- Main recommendation (if applicable)
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- Where the report was saved
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- Offer to dive deeper into any aspect
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## Examples
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```
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/research MCP protocol
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/research "database migration patterns"
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/research "authentication options" decisions
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/research "React vs Vue" architecture
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```
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