| name | deepwork-dispatching-parallel-agents |
| description | Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies |
Dispatching Parallel Agents
Overview
You delegate tasks to specialized agents with isolated context. By precisely crafting their instructions and context, you ensure they stay focused and succeed at their task. They should never inherit your session's context or history — you construct exactly what they need. This also preserves your own context for coordination work.
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
- No shared state between investigations
Don't use when:
- Failures are related (fix one might fix others)
- Need to understand full system state
- Agents would interfere with each other
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
Emit all dispatch calls in a single response. Multiple dispatch calls in one response execute concurrently; one dispatch call per response executes sequentially.
Subagent (general-purpose): "Fix agent-tool-abort.test.ts failures — [scope, constraints, expected output]"
Subagent (general-purpose): "Fix batch-completion-behavior.test.ts failures — [scope, constraints, expected output]"
Subagent (general-purpose): "Fix tool-approval-race-conditions.test.ts failures — [scope, constraints, expected output]"
// All three dispatched in one response → run concurrently
4. Review and Integrate
When agents return:
- Read each summary and captured evidence
- Inspect touched files/diff for each agent's scope
- Verify fixes don't conflict
- Run targeted tests for each changed area when available, then run the full suite
- Integrate all changes
This step is a completion/integration check: confirm each agent finished its scope, detect conflicts, and verify the combined result. It is not a prompt to dispatch a full spec-reviewer or code-quality-reviewer for each agent. The final acceptance review over the whole change set happens after all tasks are integrated.
Agent Prompt Structure
Good agent prompts are:
- Focused - One clear problem domain
- Self-contained - All context needed to understand the problem
- 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"
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
- Parallelization - Multiple investigations happen simultaneously
- Focus - Each agent has narrow scope, less context to track
- Independence - Agents don't interfere with each other
- Speed - 3 problems solved in time of 1
Verification
After agents return:
- Read each summary and evidence - Understand what changed and what proof the agent captured
- Inspect touched files/diff - Confirm the changes match each agent's scope
- Check for conflicts - Did agents edit the same code or make incompatible assumptions?
- Run targeted checks, then full suite - Verify each changed area when possible, then verify all fixes work together
- Spot check - Agents can make systematic errors
Treat this as a completion/integration check across the parallel tasks, not as a per-agent full reviewer loop. The parent workflow (e.g., subagent-driven-development) performs the final acceptance review after all tasks are integrated.
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
Codex Compatibility
- When this skill mentions TodoWrite, use Codex
update_plan.
- When this skill mentions OpenCode
task(...), use the current callable Codex subagent-dispatch tool and preserve the task contract. Treat an agent_type, agent_path, or agent_nickname field as an exact profile selector only when its current schema or documentation explicitly guarantees that behavior; otherwise prefer complete direct composition, then generic/flat dispatch.
- A generic/flat child message must be self-contained and labeled
TASK, ROLE, DELIVERABLE, SCOPE, VERIFY, REQUIRED SKILLS, CONTEXT, and CONSTRAINTS; do not claim it loaded a dw-* profile.
- When this skill mentions OpenCode-specific tool names, choose the nearest Codex tool with the same intent and preserve the workflow contract.