Bostonaholic Rpikit Parallel Agents

Parallel Agents

Dispatch multiple agents concurrently for independent problems.

Purpose

Sequential investigation of independent problems wastes time. When multiple issues have different root causes and don't affect each other, dispatching agents in parallel reduces total resolution time significantly.

When to Use

Use parallel agents when:

• 3+ test files failing with different root causes
• Multiple subsystems broken independently
• Independent tasks in a plan that don't share state
• Bulk operations across unrelated files

Do NOT use when:

• Failures might be related (fixing one might fix others)
• Tasks have sequential dependencies
• Changes could conflict with each other
• Shared state exists between tasks

Decision Framework

Before parallelizing, ask:

1. Are these problems truly independent?
   - Different files?
   - Different subsystems?
   - No shared data or state?

2. Could fixing one affect another?
   - Shared dependencies?
   - Common configuration?
   - Overlapping code paths?

3. Will changes conflict?
   - Same file modifications?
   - Related API changes?
   - Interconnected tests?

If any answer suggests dependency, work sequentially instead.

The Parallel Process

Step 1: Identify Independent Problems

Group failures or tasks by independence:

Test failures example:
- auth.test.js: Login validation errors (auth subsystem)
- api.test.js: Endpoint routing issues (api subsystem)
- db.test.js: Connection pool exhaustion (database subsystem)

Assessment: Independent subsystems, can parallelize

Step 2: Create Focused Agent Prompts

Each agent needs a self-contained, focused prompt:

Good prompt structure:
- ONE clear problem to solve
- ALL necessary context included
- SPECIFIC about expected output
- NO dependencies on other agents

Example prompts:

Agent 1 - Auth fixes:
"Fix the login validation errors in auth.test.js.
The tests expect [specific behavior].
Current error: [error message].
Do not modify files outside src/auth/."

Agent 2 - API fixes:
"Fix the endpoint routing issues in api.test.js.
Routes should map to [expected handlers].
Current error: [error message].
Do not modify files outside src/api/."

Agent 3 - Database fixes:
"Fix the connection pool exhaustion in db.test.js.
Pool should handle [expected load].
Current error: [error message].
Do not modify files outside src/db/."

Step 3: Dispatch Concurrently

Use Task tool with multiple invocations in a single message:

Task tool invocations (all in one message):
1. Agent for auth fixes
2. Agent for API fixes
3. Agent for database fixes

All agents run concurrently.

Step 4: Review Results

When agents complete:

For each agent result:
1. Read the summary
2. Verify the claimed fix
3. Check for conflicts with other agents
4. Run affected tests

Step 5: Integrate Changes

If no conflicts:

1. Accept all changes
2. Run full test suite
3. Verify no regressions

If conflicts exist:

1. Identify conflicting changes
2. Resolve conflicts manually
3. Run full test suite
4. Verify resolution is correct

Agent Prompt Requirements

Must Have

• Focused scope: One problem domain only
• Self-contained context: All info agent needs
• Clear deliverable: What success looks like
• Boundary constraints: What NOT to touch

Must Avoid

• Overly broad scope: "Fix all the tests"
• Missing context: Assuming agent knows background
• Vague deliverable: "Make it work"
• No boundaries: Free rein to change anything

Example: Multiple Test Failures

Situation: 6 failures across 3 test files

Analysis:
- tests/auth.test.js: 2 failures (login, logout)
- tests/api.test.js: 3 failures (GET, POST, DELETE)
- tests/db.test.js: 1 failure (connection timeout)

Independence check:
- Auth tests: Isolated authentication logic
- API tests: Isolated route handling
- DB tests: Isolated database operations

Decision: Parallelize - no shared dependencies

Agent dispatch:

Agent 1: "Fix auth.test.js failures. Login should [spec].
         Logout should [spec]. Error: [message]."

Agent 2: "Fix api.test.js failures. GET should [spec].
         POST should [spec]. DELETE should [spec]. Error: [message]."

Agent 3: "Fix db.test.js failure. Connection should [spec].
         Current timeout at [duration]. Error: [message]."

Results:

Agent 1: Fixed login validation, logout token cleanup
Agent 2: Fixed route registration order
Agent 3: Increased pool size and added retry logic

Conflict check: No overlapping files
Integration: All changes accepted
Final tests: All passing

Integration with Implement Phase

Use during implementation when:

• Multiple plan steps are independent
• Test failures span unrelated subsystems
• Bulk changes across independent files

Plan step identifies parallelizable work
→ Verify independence
→ Create focused agent prompts
→ Dispatch concurrently
→ Review and integrate
→ Continue with next plan step

Conflict Resolution

When agents modify overlapping code:

1. Identify the conflict
   - Same file?
   - Same function?
   - Incompatible changes?

2. Determine precedence
   - Which change is more correct?
   - Which aligns with requirements?
   - Which has fewer side effects?

3. Merge carefully
   - Take best of both if compatible
   - Choose one if mutually exclusive
   - Test merged result

4. Verify resolution
   - Run affected tests
   - Check for regressions
   - Document the resolution

Anti-Patterns

Parallelizing Related Problems

Wrong: Dispatch agents for potentially related failures Right: Verify independence before parallelizing

Overly Broad Agent Prompts

Wrong: "Fix all failing tests in this area" Right: "Fix specific failure X with context Y"

Ignoring Conflicts

Wrong: Accept all agent outputs without checking Right: Review for conflicts before integrating

Too Many Parallel Agents

Wrong: Dispatch 10+ agents simultaneously Right: Keep to 3-5 agents for manageability

No Boundary Constraints

Wrong: Let agents modify any file Right: Constrain each agent to relevant files

Checklist Before Dispatching

• Problems verified as independent
• No shared state between tasks
• Changes won't conflict
• Each agent prompt is focused
• Each agent prompt is self-contained
• Boundaries specified for each agent
• Expected output is clear

Checklist After Completion

• All agent results reviewed
• Conflicts identified and resolved
• Full test suite passes
• No regressions introduced
• Changes integrated cleanly

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