Dispatching Parallel Agents

Dispatching Parallel Agents

Skill Usage Announcement

MANDATORY: When using this skill, announce it at the start with:

🔧 Using Skill: dispatching-parallel-agents | [brief purpose based on context]

Example:

🔧 Using Skill: dispatching-parallel-agents | [Provide context-specific example of what you're doing]

This creates an audit trail showing which skills were applied during the session.

Overview

When you have multiple unrelated failures (different test files, different subsystems, different bugs), investigating them sequentially wastes time. Each investigation is independent and can happen in parallel.

Core principle: Dispatch one agent per independent problem domain. Let them work concurrently.

When to Use

digraph when_to_use {
    "Multiple failures?" [shape=diamond];
    "Are they independent?" [shape=diamond];
    "Single agent investigates all" [shape=box];
    "One agent per problem domain" [shape=box];
    "Can they work in parallel?" [shape=diamond];
    "Sequential agents" [shape=box];
    "Parallel dispatch" [shape=box];

    "Multiple failures?" -> "Are they independent?" [label="yes"];
    "Are they independent?" -> "Single agent investigates all" [label="no - related"];
    "Are they independent?" -> "Can they work in parallel?" [label="yes"];
    "Can they work in parallel?" -> "Parallel dispatch" [label="yes"];
    "Can they work in parallel?" -> "Sequential agents" [label="no - shared state"];
}

Use when:

• 3+ test files failing with different root causes
• Multiple subsystems broken independently
• Each problem can be understood without context from others
• Either parallel-safe infrastructure OR sequential fix implementation

Don't use when:

• Failures are related (fix one might fix others)
• Need to understand full system state
• Agents would interfere AND fixes must be concurrent

Prerequisites

MUST be true before using parallel agents:

1. Failures Are Logically Independent

Each failure can be investigated without knowing about the others:

Independent failures:

• Auth failure (login with expired token)
• Payment failure (invalid card)
• Profile failure (missing required field)
• Different features, different root causes

NOT independent:

• Auth failure cascades to profile failure
• Payment fails because auth failed first
• Tests fail in sequence due to shared state corruption
• Root cause is shared, investigation must be sequential

2. Investigation Is Parallel-Safe

Subagents can work concurrently without interfering:

Parallel-safe investigation:

• Reading different source files
• Examining different test files
• Running tests in isolation mode (separate processes/databases)
• Reading git history for different features

NOT parallel-safe:

• Tests share database/filesystem (race conditions)
• Tests modify global state/environment variables
• Tests run in same process with shared setup
• Investigation requires modifying same files

If failures are independent BUT not parallel-safe: You can STILL use this pattern, with modifications:

1. Dispatch subagents for investigation (reading code, analyzing)
2. Implement fixes SEQUENTIALLY (not in parallel)
3. Or set up isolated test environments (Docker containers, separate DBs)

If failures are NOT independent: Do NOT use parallel agents. Use systematic-debugging to find root cause.

Decision Tree: When to Use Parallel Agents

Do you have 3+ failures?
├─ NO → Use systematic-debugging (single failure investigation)
└─ YES → Continue

Are failures logically independent?
(Can each be investigated without knowing about others?)
├─ NO → Use systematic-debugging (find common root cause)
└─ YES → Continue

Is investigation parallel-safe?
(Can subagents work concurrently without interfering?)
├─ YES → Dispatch parallel agents ✓
└─ NO → Two options:
        A) Dispatch for investigation only, fix sequentially
        B) Set up isolated test environments, then dispatch

The Pattern

1. Identify Independent Domains

Group failures by what's broken:

• File A tests: Tool approval flow
• File B tests: Batch completion behavior
• File C tests: Abort functionality

Each domain is independent - fixing tool approval doesn't affect abort tests.

2. Create Focused Agent Tasks

Each agent gets:

• Specific scope: One test file or subsystem
• Clear goal: Make these tests pass
• Constraints: Don't change other code
• Expected output: Summary of what you found and fixed

3. Dispatch in Parallel

// In Claude Code / AI environment
Task("Fix agent-tool-abort.test.ts failures")
Task("Fix batch-completion-behavior.test.ts failures")
Task("Fix tool-approval-race-conditions.test.ts failures")
// All three run concurrently

4. Review and Integrate

When agents return:

• Read each summary
• Verify fixes don't conflict
• Run full test suite
• Integrate all changes

Agent Prompt Structure

Good agent prompts are:

1. Focused - One clear problem domain
2. Self-contained - All context needed to understand the problem
3. Specific about output - What should the agent return?

Fix the 3 failing tests in src/agents/agent-tool-abort.test.ts:

1. "should abort tool with partial output capture" - expects 'interrupted at' in message
2. "should handle mixed completed and aborted tools" - fast tool aborted instead of completed
3. "should properly track pendingToolCount" - expects 3 results but gets 0

These are timing/race condition issues. Your task:

1. Read the test file and understand what each test verifies
2. Identify root cause - timing issues or actual bugs?
3. Fix by:
   - Replacing arbitrary timeouts with event-based waiting
   - Fixing bugs in abort implementation if found
   - Adjusting test expectations if testing changed behavior

Do NOT just increase timeouts - find the real issue.

Return: Summary of what you found and what you fixed.

Common Mistakes

❌ Too broad: "Fix all the tests" - agent gets lost ✅ Specific: "Fix agent-tool-abort.test.ts" - focused scope

❌ No context: "Fix the race condition" - agent doesn't know where ✅ Context: Paste the error messages and test names

❌ No constraints: Agent might refactor everything ✅ Constraints: "Do NOT change production code" or "Fix tests only"

❌ Vague output: "Fix it" - you don't know what changed ✅ Specific: "Return summary of root cause and changes"

Examples

Example 1: Independent + Parallel-Safe → Use Skill

Failures:

• Auth test fails (expired token handling)
• Payment test fails (card validation)
• Profile test fails (field validation)

Check independence:

• Different features
• Different root causes
• Can investigate without knowing about others

Check parallel safety:

• Tests in different files
• Each uses isolated test database (Docker containers)
• No shared mocks or global state
• Running tests won't interfere

Decision: Dispatch parallel agents

Example 2: Independent but NOT Parallel-Safe → Modified Approach

Failures:

• Auth test fails (expired token handling)
• Payment test fails (card validation)
• Profile test fails (field validation)

Check independence:

• Different features
• Different root causes
• Can investigate without knowing about others

Check parallel safety:

• All tests use same test database (shared state)
• Tests have beforeEach(() => resetDatabase()) (race condition)
• Running tests in parallel causes interference

Decision: Use modified approach:

1. Dispatch 3 subagents to investigate (read code, analyze logic)
2. Implement fixes SEQUENTIALLY (one at a time, avoiding interference)
3. OR set up isolated test environments first, then dispatch

Example 3: NOT Independent → Don't Use Skill

Failures:

• Auth test fails (session creation)
• Profile test fails (requires session)
• Settings test fails (requires session)

Check independence:

• Profile and Settings failures caused by Auth failure
• Root cause is shared (session creation broken)
• Cannot investigate Profile/Settings without understanding Auth failure

Decision: Do NOT dispatch parallel agents. Use systematic-debugging to find root cause in auth system first.

When NOT to Use

Related failures: Fixing one might fix others - investigate together first Need full context: Understanding requires seeing entire system Exploratory debugging: You don't know what's broken yet Shared state: Agents would interfere (editing same files, using same resources)

Real Example from Session

Scenario: 6 test failures across 3 files after major refactoring

Failures:

• agent-tool-abort.test.ts: 3 failures (timing issues)
• batch-completion-behavior.test.ts: 2 failures (tools not executing)
• tool-approval-race-conditions.test.ts: 1 failure (execution count = 0)

Decision: Independent domains - abort logic separate from batch completion separate from race conditions

Dispatch:

Agent 1 → Fix agent-tool-abort.test.ts
Agent 2 → Fix batch-completion-behavior.test.ts
Agent 3 → Fix tool-approval-race-conditions.test.ts

Results:

• Agent 1: Replaced timeouts with event-based waiting
• Agent 2: Fixed event structure bug (threadId in wrong place)
• Agent 3: Added wait for async tool execution to complete

Integration: All fixes independent, no conflicts, full suite green

Time saved: 3 problems solved in parallel vs sequentially

Key Benefits

1. Parallelization - Multiple investigations happen simultaneously
2. Focus - Each agent has narrow scope, less context to track
3. Independence - Agents don't interfere with each other
4. Speed - 3 problems solved in time of 1

Verification

After agents return:

1. Review each summary - Understand what changed
2. Check for conflicts - Did agents edit same code?
3. Run full suite - Verify all fixes work together
4. Spot check - Agents can make systematic errors

Real-World Impact

From debugging session (2025-10-03):

• 6 failures across 3 files
• 3 agents dispatched in parallel
• All investigations completed concurrently
• All fixes integrated successfully
• Zero conflicts between agent changes