Ticket attachment decision trees, enforcement protocols, communication templates, and worked examples for research outputs
version
1.0.0
category
agent-protocol
author
Claude MPM Team
license
MIT
progressive_disclosure
{"entry_point":{"summary":"Enforce ticket attachment when ticket context exists in research tasks","when_to_use":"When ticket IDs or issue URLs are detected in research requests","quick_start":"Check ticket context -> classify work type -> attach to ticket or save to docs/research/"}}
Important: Research outputs should be attached to tickets when ticket context exists.
When Ticket Attachment is Required
Generally REQUIRED (100% enforcement):
User provides ticket ID/URL explicitly
User says: "Research X for TICKET-123"
User includes ticket URL in request
PM delegation includes ticket context
-> Research should attach findings to TICKET-123
PM passes ticket context in delegation
PM includes "TICKET CONTEXT" section
Delegation mentions: "for ticket {TICKET_ID}"
Task includes: "related to {TICKET_ID}"
-> Research should attach findings to TICKET_ID
mcp-ticketer tools available + ticket context exists
Check: mcp__mcp-ticketer__* tools in tool set
AND: Ticket ID/context present in task
-> Research should attempt ticket attachment (with fallback)
When Ticket Attachment is OPTIONAL
File-based capture ONLY:
No ticket context provided
User asks: "Research authentication patterns" (no ticket mentioned)
PM delegates without ticket context
Ad-hoc research request
-> Research saves to docs/research/ only (no ticketing)
mcp-ticketer tools unavailable
No mcp__mcp-ticketer__* tools detected
AND: No ticketing-agent available
-> Research saves to docs/research/ + informs user about ticketing unavailability
Attachment Decision Tree
Start Research Task
|
v
Check: Ticket context provided?
|
+-- NO --> Save to docs/research/ only (inform user)
|
+-- YES --> Check: mcp-ticketer tools available?
|
+-- NO --> Save to docs/research/ + inform user
| "Ticketing integration unavailable, saved locally"
|
+-- YES --> required TICKET ATTACHMENT
|
v
Classify Work Type
|
+-- Actionable --> Create subtask under ticket
| Link findings
| Save to docs/research/
|
+-- Informational --> Attach file to ticket
Add comment with summary
Save to docs/research/
|
v
Verify Attachment Success
|
+-- SUCCESS --> Report to user
| "Attached to {TICKET_ID}"
|
+-- FAILURE --> Fallback to file-only
Log error details
Report to user with error
Enforcement Language
YOU should attach research findings to {TICKET_ID}
Ticket attachment is required when ticket context exists.
DO NOT complete research without attaching to {TICKET_ID}.
Failure Handling
Important: Attachment failures should NOT block research delivery.
Fallback Chain:
Attempt ticket attachment (MCP tools)
If fails: Log error details + save to docs/research/
Report to user with specific error message
Deliver research results regardless
User Communication Templates
Success Message:
Research Complete and Attached
Research: OAuth2 Implementation Analysis
Saved to: docs/research/oauth2-patterns-2025-11-23.md
Ticket Integration:
- Attached findings to TICKET-123
- Created subtask TICKET-124: Implement token refresh
- Added comment summarizing key recommendations
Next steps available in TICKET-124.
Partial Failure Message:
Research Complete (Partial Ticket Integration)
Research: OAuth2 Implementation Analysis
Saved to: docs/research/oauth2-patterns-2025-11-23.md
Ticket Integration:
- Attached research file to TICKET-123
- Failed to create subtasks (API error: "Rate limit exceeded")
Manual Action Required:
Please create these subtasks manually in your ticket system:
1. Implement token refresh mechanism (under TICKET-123)
2. Add OAuth2 error handling (under TICKET-123)
3. Write OAuth2 integration tests (under TICKET-123)
Full research with implementation details available in local file.
Complete Failure Message:
Research Complete (Ticket Integration Unavailable)
Research: OAuth2 Implementation Analysis
Saved to: docs/research/oauth2-patterns-2025-11-23.md
Ticket Integration Failed:
Error: "Ticketing service unavailable"
Your research is safe in the local file. To attach to TICKET-123:
1. Check mcp-ticketer service status
2. Manually upload docs/research/oauth2-patterns-2025-11-23.md to ticket
3. Or retry: [provide retry command]
Research findings delivered successfully regardless of ticketing status.
Priority Matrix
OPTION 1: Create Subtask (HIGHEST PRIORITY)
Criteria: Ticket context + tools available + ACTIONABLE work
Criteria: File attachment failed (too large, API limit)
Action: mcp__mcp-ticketer__ticket_comment with file reference
OPTION 4: File Only (FALLBACK)
Criteria: No ticket context OR no tools available
Action: Save to docs/research/ + inform user
Work Classification Decision Tree
Start Research
|
v
Conduct Analysis
|
v
Classify Work Type:
|
+-- Actionable Work?
| - Contains TODO items
| - Requires implementation
| - Identifies bugs/issues
| - Proposes changes
|
+-- Informational Only?
- Background research
- Reference material
- No immediate actions
- Comparative analysis
|
v
Save to docs/research/{filename}.md (generally)
|
v
Check Ticketing Tools Available?
|
+-- NO --> Inform user (file-based only)
|
+-- YES --> Check Context:
|
+-- Issue ID?
| |
| +-- Actionable --> Create subtask
| +-- Informational --> Attach + comment
|
+-- Project/Epic?
| |
| +-- Actionable --> Create issue in project
| +-- Informational --> Attach to project
|
+-- No Context --> File-based only
|
v
Inform User:
- File path: docs/research/{filename}.md
- Ticket ID: {ISSUE_ID or SUBTASK_ID} (if created/attached)
- Action: What was done with research
|
v
Done (Non-blocking)
Worked Examples
Example 1: Issue-Based Actionable Research
User: "Research OAuth2 implementation patterns for ISSUE-123"
Research Agent Actions:
1. Conducts OAuth2 research using vector search and grep
2. Identifies actionable work: Need to implement OAuth2 flow
3. Saves to: docs/research/oauth2-implementation-patterns-2025-11-22.md
4. Checks: mcp-ticketer tools available? YES
5. Detects: ISSUE-123 context
6. Classifies: Actionable work (implementation required)
7. Creates subtask:
- Title: "Research: OAuth2 Implementation Patterns"
- Parent: ISSUE-123
- Description: Link to docs/research file + summary
- Tags: ["research", "authentication"]
8. Links subtask to ISSUE-123
9. Attaches research document
10. Informs user:
"Research completed and saved to docs/research/oauth2-implementation-patterns-2025-11-22.md
Created subtask ISSUE-124 under ISSUE-123 with action items:
- Implement OAuth2 authorization flow
- Add token refresh mechanism
- Update authentication middleware
Full research findings attached to ISSUE-123."
Example 2: Project-Level Informational Research
User: "Analyze database scaling options for Project-AUTH"
Research Agent Actions:
1. Conducts database scaling research
2. Finds: Comparative analysis, no immediate action required
3. Saves to: docs/research/database-scaling-analysis-2025-11-22.md
4. Checks: mcp-ticketer tools available? YES
5. Detects: No ISSUE ID, but Project-AUTH exists
6. Classifies: Informational (no immediate action)
7. Attaches to Project-AUTH:
- file_path: docs/research/database-scaling-analysis-2025-11-22.md
- description: "Database scaling options analysis"
8. Adds comment to Project-AUTH:
- "Completed database scaling analysis. Key findings:
- PostgreSQL can scale to 10K QPS with read replicas
- Aurora Serverless recommended for variable workloads
- Redis caching reduces DB load by 40%
Full analysis: docs/research/database-scaling-analysis-2025-11-22.md"
9. Informs user:
"Research completed and saved to docs/research/database-scaling-analysis-2025-11-22.md
Attached findings to Project-AUTH with summary of scaling options.
Recommendation: Review analysis before making infrastructure decisions."
Example 3: Ad-Hoc Research (No Ticketing Context)
User: "Research latest trends in AI agents"
Research Agent Actions:
1. Conducts AI agents research using WebSearch and analysis
2. Compiles findings on current trends
3. Saves to: docs/research/ai-agents-trends-2025-11-22.md
4. Checks: mcp-ticketer tools available? YES
5. Detects: No ISSUE ID, no Project context
6. Classifies: Informational, no ticketing context
7. Logs: "No ticketing context available for AI agents research"
8. Informs user:
"Research completed and saved to docs/research/ai-agents-trends-2025-11-22.md
Key trends identified:
- Multi-agent systems gaining traction
- Tool use and function calling becoming standard
- Focus on reliability and error recovery
No ticketing context available. To track this research:
- Create issue: 'Review AI agent trends'
- Or attach to existing project/epic"
Example 4: File Write Error with Fallback
User: "Research performance bottlenecks in API layer"
Research Agent Actions:
1. Conducts performance research
2. Identifies bottlenecks: N+1 queries, missing indexes
3. Attempts: Write to docs/research/api-performance-bottlenecks-2025-11-22.md
4. Error: Permission denied (docs/research/ doesn't exist or no write permission)
5. Fallback: mkdir -p docs/research/ && retry
6. If still fails: Try ./research/api-performance-bottlenecks-2025-11-22.md
7. If still fails: Try ./api-performance-bottlenecks-2025-11-22.md
8. Success: Saved to ./api-performance-bottlenecks-2025-11-22.md
9. Informs user:
"Research completed but encountered permission error with docs/research/
Saved to: ./api-performance-bottlenecks-2025-11-22.md
To fix permissions:
mkdir -p docs/research && chmod u+w docs/research
mv ./api-performance-bottlenecks-2025-11-22.md docs/research/
Key findings:
- N+1 query problem in user endpoint (fix: add eager loading)
- Missing index on orders.created_at (add migration)
- API response time: 800ms avg, target <200ms"
