Deep Research

Coordinate deep technical research with intelligent caching for cross-project reuse and team knowledge sharing.

Quick Start

When research is needed:

• Resolve scripts path - Find plugins/core/skills/deep-research/scripts/ (or Glob for **/deep-research/scripts/cache_manager.py )

• Check cache first - Run python3 {scripts_dir}/cache_manager.py check "{topic}"

• If cached and valid - Run cache_manager.py get "{slug}" and return content directly (no agent needed)

• If cache miss - Invoke deep-researcher agent for EXA research, which caches via cache_manager.py put

• Report findings - Include cache status and promote suggestion

Cache Architecture

Tier Location Purpose Shared

1 ~/.claude/plugins/research/

Fast, cross-project User only

2 docs/research/

Curated, version controlled Team

Operations

Operation Trigger Fast Path? Action

Research /research <topic> or natural language Yes (cache hit) Check cache → return if valid, else research → cache

Promote /research promote <slug>

Yes Run promote.py {slug} directly

Refresh /research refresh <slug>

No Spawn agent → fresh research → cache → update promoted

List /research list

Yes Run cache_manager.py list (project-scoped by default, --all for everything)

Project Scoping

Research entries are automatically associated with the current git repository when cached. The list operation filters by current project by default, so each project sees only its relevant research. Use --all to see everything.

• Auto-detection: Project name derived from git rev-parse --show-toplevel basename

• Multi-project: Entries can belong to multiple projects (associations merge, never replace)

• Backward compatible: Existing entries without project associations appear in --all but not in project-scoped views

Scripts

All cache operations use Python scripts in scripts/ :

Script Purpose

research_utils.py

Shared utilities (imported by all scripts)

cache_manager.py

Cache CRUD: get, put, check, list, delete

promote.py

Tier 1 → Tier 2 promotion with team notes

index_generator.py

README index generation for both tiers

Slug Normalization

Convert topics to cache keys:

• "Domain-Driven Design" → domain-driven-design

• "DDD" → domain-driven-design (via alias)

• "React Hooks" → react-hooks

Output Format

After research, report:

Research: {Topic}

Cache: {Hit | Miss | Expired} Source: {Cached | Fresh research} Path: ~/.claude/plugins/research/entries/{slug}/

[Brief summary of findings]

Run /research promote {slug} to add to project docs.

Agent Delegation

For actual research execution (cache miss or refresh only), delegate to deep-researcher agent:

• Has MCP tool access (EXA web search, code context)

• Uses cache_manager.py put for cache write operations

• Structures research output consistently

Additional Resources

• WORKFLOW.md - Detailed process flows

• EXAMPLES.md - Usage examples

• TROUBLESHOOTING.md - Common issues and solutions