6-phase investigation workflow for understanding existing systems. Auto-activates for research tasks.
Optimized for exploration and understanding, not implementation. Includes parallel agent deployment
for efficient deep dives and automatic knowledge capture to prevent repeat investigations.
This skill provides a systematic 6-phase workflow for investigating and understanding existing systems, codebases, and architectures. Unlike development workflows optimized for implementation, this workflow is optimized for exploration, understanding, and knowledge capture.
When to Use This Skill
Investigation Tasks (use this workflow):
"Investigate how the authentication system works"
"Explain the neo4j memory integration"
"Understand why CI is failing consistently"
"Analyze the reflection system architecture"
"Research what hooks are triggered during session start"
Development Tasks (use DEFAULT_WORKFLOW.md instead):
"Implement OAuth support"
"Build a new API endpoint"
"Add feature X"
"Fix bug Y"
Core Philosophy
관련 스킬
Exploration First: Define scope and strategy before diving into code
Parallel Deep Dives: Deploy multiple agents simultaneously for efficient information gathering
Verification Required: Test understanding through practical application
Knowledge Capture: Document findings to prevent repeat investigations
The 6-Phase Investigation Workflow
Phase 1: Scope Definition
Purpose: Define investigation boundaries and success criteria before any exploration.
Tasks:
FIRST: Identify explicit user requirements - What specific questions must be answered?
Use prompt-writer agent to clarify investigation scope
Use ambiguity agent if questions are unclear
Define what counts as "understanding achieved"
List specific questions that must be answered
Set boundaries: What's in scope vs. out of scope
Estimate investigation depth needed (surface-level vs. deep dive)
Purpose: Plan which agents to deploy and what to investigate, preventing inefficient random exploration.
Tasks:
Use architect agent to design exploration strategy
Use patterns agent to check for similar past investigations
Identify key areas to explore (code paths, configurations, documentation)
Select specialized agents for parallel deployment in Phase 3
Create investigation roadmap with priorities
Identify potential dead ends to avoid
Plan verification approach (how to test understanding)
Agent Selection Guidelines:
For code understanding: analyzer, patterns agents
For system architecture: architect, api-designer agents
For performance issues: optimizer, analyzer agents
For security concerns: security, patterns agents
For integration flows: integration, database agents
Success Criteria:
Clear exploration roadmap
List of agents to deploy in Phase 3
Prioritized investigation areas
Deliverables:
Exploration strategy document with:
Investigation roadmap
Agent deployment plan for Phase 3
Priority order for exploration
Expected outputs from each exploration
Phase 3: Parallel Deep Dives
Purpose: Deploy multiple exploration agents simultaneously to gather information efficiently.
CRITICAL: This phase uses PARALLEL EXECUTION by default.
Tasks:
Deploy selected agents in PARALLEL based on Phase 2 strategy
Common parallel patterns:
[analyzer(module1), analyzer(module2), analyzer(module3)] - Multiple code areas
[analyzer, patterns, security] - Multiple perspectives on same area
[architect, database, integration] - System architecture exploration
Each agent explores their assigned area independently
Collect findings from all parallel explorations
Identify connections and dependencies between findings
Note any unexpected discoveries or anomalies
Parallel Agent Examples:
Investigation: "How does the reflection system work?"
→ [analyzer(~/.amplihack/.claude/tools/amplihack/hooks/), patterns(reflection), integration(logging)]
Investigation: "Why is CI failing?"
→ [analyzer(ci-config), patterns(ci-failures), integration(github-actions)]
Investigation: "Understand authentication flow"
→ [analyzer(auth-module), security(auth), patterns(auth), integration(external-auth)]
Success Criteria:
All planned agents deployed and completed
Findings from each exploration collected
Connections between findings identified
Deliverables:
Findings report with:
Summary from each parallel exploration
Code paths and flow diagrams
Architectural insights
Unexpected discoveries
Open questions for verification
Phase 4: Verification & Testing
Purpose: Test and validate understanding through practical application.
Tasks:
Create hypotheses based on Phase 3 findings
Design practical tests to verify understanding:
Trace specific code paths manually
Examine logs and outputs
Test edge cases and assumptions
Verify configuration effects
Run verification tests
Document what was tested and results
Identify gaps in understanding
Refine hypotheses based on test results
Repeat verification for any unclear areas
Verification Examples:
Understanding: "Authentication uses JWT tokens"
Verification: Trace actual token creation and validation in code
Understanding: "CI fails because of dependency conflict"
Verification: Check CI logs, reproduce locally, verify fix works
Understanding: "Reflection analyzes all user messages"
Verification: Examine reflection logs, trace message processing
Success Criteria:
All hypotheses tested
Understanding verified through practical tests
Gaps in understanding identified and filled
Deliverables:
Verification report with:
Tests performed
Results and observations
Confirmed understanding
Remaining gaps or uncertainties
Phase 5: Synthesis
Purpose: Compile findings into coherent explanation that answers original questions.
Tasks:
Use reviewer agent to check completeness of findings
Use patterns agent to identify reusable patterns discovered
Synthesize findings from Phases 3-4 into coherent explanation
Create visual artifacts (diagrams, flow charts) if helpful
Answer each question from Phase 1 scope definition
Identify what worked well vs. what was unexpected
Note any assumptions or uncertainties remaining
Prepare clear explanation suitable for user
Synthesis Outputs:
Executive Summary: 2-3 sentence answer to main question
Detailed Explanation: Complete explanation with supporting evidence
Visual Aids: Diagrams showing system flow, architecture, etc.
Key Insights: Non-obvious discoveries or patterns
Remaining Unknowns: What's still unclear or uncertain
Success Criteria:
All Phase 1 questions answered
Explanation is clear and complete
Findings supported by evidence from verification
Visual aids clarify complex areas
Deliverables:
Investigation report with all 5 synthesis outputs
Ready for knowledge capture in Phase 6
Phase 6: Knowledge Capture
Purpose: Create durable documentation so this investigation never needs to be repeated.
Tasks:
Store discoveries in memory using store_discovery() from amplihack.memory.discoveries
Update .claude/context/PATTERNS.md if reusable patterns found
Create or update relevant documentation files
Add inline code comments for critical understanding
Optional: Create GitHub issue for follow-up improvements
Optional: Update architecture diagrams if needed
Ensure future investigators can find this knowledge easily
Documentation Guidelines:
## Discovery: [Brief Title]
**Context**: What was investigated and why
**Key Findings**:
- Main insight 1
- Main insight 2
- **Supporting Evidence**: Links to code, logs, or verification tests
- **Implications**: How this affects the project
- **Related Patterns**: Links to similar patterns in PATTERNS.md
Success Criteria:
Discoveries stored in memory for future reference
Relevant documentation files updated
Knowledge is discoverable by future investigators
No information loss
Deliverables:
Discoveries stored in memory
Updated PATTERNS.md (if applicable)
Updated project documentation
Optional: GitHub issues for improvements
Investigation session log in ~/.amplihack/.claude/runtime/logs/
Transitioning to Development Workflow
After investigation completes, if the task requires implementation (not just understanding), transition to DEFAULT_WORKFLOW.md:
Resume at Step 4 (Research and Design) with the knowledge gained from investigation
Or resume at Step 5 (Implement the Solution) if the investigation already provided clear design guidance
Use investigation findings from memory (via get_recent_discoveries()) and session logs to inform design decisions
Example Hybrid Workflow:
User: "/ultrathink investigate how authentication works, then add OAuth support"
Phase 1: Investigation
→ Run INVESTIGATION_WORKFLOW.md (6 phases)
→ Complete understanding of existing auth system
→ Store findings in memory via discoveries adapter
Phase 2: Development
→ Transition to DEFAULT_WORKFLOW.md
→ Resume at Step 4 (Research and Design)
→ Use investigation insights to design OAuth integration
→ Continue through Step 15 (implementation → testing → PR)
When to Transition:
Investigation reveals implementation is needed
User explicitly requested both investigation + development
Follow-up work identified during knowledge capture
Efficiency Targets
Target Efficiency: This workflow targets a 30-40% reduction in message count compared to ad-hoc investigation.
Ad-Hoc Approach
Investigation Workflow
70-90 messages
40-60 messages
Frequent backtracking
Planned exploration
Redundant investigation
Parallel deep dives
Unclear scope
Explicit scope definition
Lost knowledge
Documented insights
Efficiency Gains Come From:
Scope Definition prevents scope creep and wandering
Exploration Strategy prevents random unproductive exploration
Parallel Deep Dives maximize information gathering speed
Verification Phase catches misunderstandings early
Synthesis ensures all questions answered
Knowledge Capture prevents repeat investigations
Comparison to DEFAULT_WORKFLOW.md
Similarities (Structural Consistency)
Both workflows share core principles:
Explicit phases with clear deliverables
Agent-driven execution at each phase
Quality gates preventing premature progression
Knowledge capture and documentation
TodoWrite tracking for progress management
Differences (Investigation vs. Development)
Aspect
Investigation Workflow
DEFAULT_WORKFLOW.md
Goal
Understanding
Implementation
Phases
6 phases
Multi-step workflow
Execution
Exploration-first
Implementation-first
Parallel Focus
Phase 3 (Deep Dives)
Various steps
Testing
Understanding verification
Code validation
Deliverable
Documentation
Working code
Git Usage
Optional
Required (branches, PRs)
Phase Mapping (For User Familiarity)
Investigation Phase
DEFAULT_WORKFLOW Equivalent
Purpose
Phase 1: Scope Definition
Step 1: Requirements Clarification
Define what success looks like
Phase 2: Exploration Strategy
Step 4: Research and Design
Plan the approach
Phase 3: Parallel Deep Dives
Step 5: Implementation
Execute the plan (explore vs. build)
Phase 4: Verification
Steps 7-8: Testing
Validate results
Phase 5: Synthesis
Step 11: Review
Ensure quality and completeness
Phase 6: Knowledge Capture
Step 15: Cleanup
Make results durable
Integration with UltraThink
UltraThink Workflow Detection: When /ultrathink is invoked, it automatically detects investigation tasks using keywords and suggests this workflow.
Automatic Workflow Suggestion:
User: "/ultrathink investigate how authentication works"
UltraThink: Detected investigation task. Using INVESTIGATION_WORKFLOW.md
→ Reading workflow from .claude/workflow/INVESTIGATION_WORKFLOW.md
→ Following 6-phase investigation workflow
→ Starting Phase 1: Scope Definition
Customization
To customize this workflow:
Edit ~/.amplihack/.claude/workflow/INVESTIGATION_WORKFLOW.md to modify, add, or remove phases
Adjust agent deployment strategies for your needs
Add project-specific investigation patterns
Update efficiency targets based on your metrics
Changes take effect immediately for future investigations.
Success Metrics
Track these metrics to validate workflow effectiveness:
Message Count: Target 30-40% reduction vs. ad-hoc (to be validated)
Investigation Time: Track time to completion
Knowledge Reuse: How often memory retrieval prevents repeat work
Completeness: Percentage of investigations with full documentation
User Satisfaction: Clear understanding achieved
Key Principles
Scope first, explore second - Define boundaries before diving in
Parallel exploration is key - Deploy multiple agents simultaneously in Phase 3
Verify understanding - Test your hypotheses in Phase 4
Capture knowledge - Always store discoveries in memory in Phase 6
This workflow optimizes for understanding, not implementation
When in doubt about investigation vs. development: