Deep Research Skill | Agent Skills

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

Agent Skills: Deep Research

Install this agent skill to your local

Skill Files