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Contains Hooks
This skill uses Claude hooks which can execute code automatically in response to events. Review carefully before installing.
Codebase Exploration
Multi-angle codebase exploration using 3-5 parallel agents.
Quick Start
/ork:explore authentication
Opus 4.6 : Exploration agents use native adaptive thinking for deeper pattern recognition across large codebases.
STEP 0: Verify User Intent with AskUserQuestion
BEFORE creating tasks , clarify what the user wants to explore:
AskUserQuestion(
questions=[{
"question": "What aspect do you want to explore?",
"header": "Focus",
"options": [
{"label": "Full exploration (Recommended)", "description": "Code structure + data flow + architecture + health assessment", "markdown": "```\nFull Exploration (8 phases)\n───────────────────────────\n 4 parallel explorer agents:\n ┌──────────┐ ┌──────────┐\n │ Structure│ │ Data │\n │ Explorer │ │ Flow │\n ├──────────┤ ├──────────┤\n │ Pattern │ │ Product │\n │ Analyst │ │ Context │\n └──────────┘ └──────────┘\n ▼\n ┌──────────────────────┐\n │ Code Health N/10 │\n │ Dep Hotspots map │\n │ Architecture diag │\n └──────────────────────┘\n Output: Full exploration report\n```"},
{"label": "Code structure only", "description": "Find files, classes, functions related to topic", "markdown": "```\nCode Structure\n──────────────\n Grep ──▶ Glob ──▶ Map\n\n Output:\n ├── File tree (relevant)\n ├── Key classes/functions\n ├── Import graph\n └── Entry points\n No agents — direct search\n```"},
{"label": "Data flow", "description": "Trace how data moves through the system", "markdown": "```\nData Flow Trace\n───────────────\n Input ──▶ Transform ──▶ Output\n │ │ │\n ▼ ▼ ▼\n [API] [Service] [DB/Cache]\n\n Traces: request lifecycle,\n state mutations, side effects\n Agent: 1 data-flow explorer\n```"},
{"label": "Architecture patterns", "description": "Identify design patterns and integrations", "markdown": "```\nArchitecture Analysis\n─────────────────────\n ┌─────────────────────┐\n │ Detected Patterns │\n │ ├── MVC / Hexagonal │\n │ ├── Event-driven? │\n │ ├── Service layers │\n │ └── External APIs │\n ├─────────────────────┤\n │ Integration Map │\n │ DB ←→ Cache ←→ Queue │\n └─────────────────────┘\n Agent: backend-system-architect\n```"},
{"label": "Quick search", "description": "Just find relevant files, skip deep analysis", "markdown": "```\nQuick Search (~30s)\n───────────────────\n Grep + Glob ──▶ File list\n\n Output:\n ├── Matching files\n ├── Line references\n └── Brief summary\n No agents, no health check,\n no report generation\n```"}
],
"multiSelect": false
}]
)
Based on answer, adjust workflow:
- Full exploration : All phases, all parallel agents
- Code structure only : Skip phases 5-7 (health, dependencies, product)
- Data flow : Focus phase 3 agents on data tracing
- Architecture patterns : Focus on backend-system-architect agent
- Quick search : Skip to phases 1-2 only, return file list
STEP 0b: Select Orchestration Mode
MCP Probe
ToolSearch(query="select:mcp__memory__search_nodes")
Write(".claude/chain/capabilities.json", { memory, timestamp })
if capabilities.memory:
mcp__memory__search_nodes({ query: "architecture decisions for {path}" })
# Enrich exploration with past decisions
Exploration Handoff
After exploration completes, write results for downstream skills:
Write(".claude/chain/exploration.json", JSON.stringify({
"phase": "explore", "skill": "explore",
"timestamp": now(), "status": "completed",
"outputs": {
"architecture_map": { ... },
"patterns_found": ["repository", "service-layer"],
"complexity_hotspots": ["src/auth/", "src/payments/"]
}
}))
Choose Agent Teams (mesh) or Task tool (star):
- Agent Teams mode (GA since CC 2.1.33) → recommended for 4+ agents
- Task tool mode → for quick/single-focus exploration
ORCHESTKIT_FORCE_TASK_TOOL=1 → Task tool (override)
| Aspect | Task Tool | Agent Teams |
|---|
| Discovery sharing | Lead synthesizes after all complete | Explorers share discoveries as they go |
| Cross-referencing | Lead connects dots | Data flow explorer alerts architecture explorer |
| Cost | ~150K tokens | ~400K tokens |
| Best for | Quick/focused searches | Deep full-codebase exploration |
Fallback: If Agent Teams encounters issues, fall back to Task tool for remaining exploration.
Task Management (MANDATORY)
BEFORE doing ANYTHING else, create tasks to show progress:
TaskCreate(subject="Explore: {topic}", description="Deep codebase exploration for {topic}", activeForm="Exploring {topic}")
TaskCreate(subject="Initial file search", activeForm="Searching files")
TaskCreate(subject="Check knowledge graph", activeForm="Checking memory")
TaskCreate(subject="Launch exploration agents", activeForm="Dispatching explorers")
TaskCreate(subject="Assess code health (0-10)", activeForm="Assessing code health")
TaskCreate(subject="Map dependency hotspots", activeForm="Mapping dependencies")
TaskCreate(subject="Add product perspective", activeForm="Adding product context")
TaskCreate(subject="Generate exploration report", activeForm="Generating report")
Workflow Overview
| Phase | Activities | Output |
|---|
| 1. Initial Search | Grep, Glob for matches | File locations |
| 2. Memory Check | Search knowledge graph | Prior context |
| 3. Deep Exploration | 4 parallel explorers | Multi-angle analysis |
| 4. AI System (if applicable) | LangGraph, prompts, RAG | AI-specific findings |
| 5. Code Health | Rate code 0-10 | Quality scores |
| 6. Dependency Hotspots | Identify coupling | Hotspot visualization |
| 7. Product Perspective | Business context | Findability suggestions |
| 8. Report Generation |
Progressive Output (CC 2.1.76)
Output findings incrementally as each phase completes — don't batch until the report:
| After Phase | Show User |
|---|
| 1. Initial Search | File matches, grep results |
| 2. Memory Check | Prior decisions and relevant context |
| 3. Deep Exploration | Each explorer agent's findings as they return |
| 5. Code Health | Health score with dimension breakdown |
For Phase 3 parallel agents, output each agent's findings as soon as it returns — don't wait for all 4 explorers. Early findings from one agent may answer the user's question before remaining agents complete, allowing early termination.
Phase 1: Initial Search
# PARALLEL - Quick searches
Grep(pattern="$ARGUMENTS[0]", output_mode="files_with_matches")
Glob(pattern="**/*$ARGUMENTS[0]*")
Phase 2: Memory Check
mcp__memory__search_nodes(query="$ARGUMENTS[0]")
mcp__memory__search_nodes(query="architecture")
Phase 3: Parallel Deep Exploration (4 Agents)
Load Read("${CLAUDE_SKILL_DIR}/rules/exploration-agents.md") for Task tool mode prompts.
Load Read("${CLAUDE_SKILL_DIR}/rules/agent-teams-mode.md") for Agent Teams alternative.
Phase 4: AI System Exploration (If Applicable)
For AI/ML topics, add exploration of: LangGraph workflows, prompt templates, RAG pipeline, caching strategies.
Phase 5: Code Health Assessment
Load Read("${CLAUDE_SKILL_DIR}/rules/code-health-assessment.md") for agent prompt. Load Read("${CLAUDE_SKILL_DIR}/references/code-health-rubric.md") for scoring criteria.
Phase 6: Dependency Hotspot Map
Load Read("${CLAUDE_SKILL_DIR}/rules/dependency-hotspot-analysis.md") for agent prompt. Load Read("${CLAUDE_SKILL_DIR}/references/dependency-analysis.md") for metrics.
Phase 7: Product Perspective
Load Read("${CLAUDE_SKILL_DIR}/rules/product-perspective.md") for agent prompt. Load Read("${CLAUDE_SKILL_DIR}/references/findability-patterns.md") for best practices.
Phase 8: Generate Report
Load Read("${CLAUDE_SKILL_DIR}/references/exploration-report-template.md").
Common Exploration Queries
- "How does authentication work?"
- "Where are API endpoints defined?"
- "Find all usages of EventBroadcaster"
- "What's the workflow for content analysis?"
Related Skills
ork:implement: Implement after exploration
Version: 2.3.0 (March 2026) — Added progressive output for incremental exploration results
Weekly Installs
93
Repository
yonatangross/orchestkit
GitHub Stars
142
First Seen
Jan 22, 2026
Security Audits
Gen Agent Trust HubPassSocketPassSnykPass
Installed on
gemini-cli85
opencode85
codex83
github-copilot83
claude-code81
cursor81
