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From ultraship
Dispatches isolated sub-agents to investigate independent problems in parallel, preserving context. Use when 3+ test files fail with distinct root causes or multiple subsystems break independently.
How this skill is triggered — by the user, by Claude, or both
Slash command
/ultraship:dispatching-parallel-agentsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
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.
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.
Nesting and scale: Subagents can spawn their own subagents up to 5 levels deep, so a dispatched agent owning a large domain can fan out helpers for its sub-steps rather than doing everything serially. When the work-list is large, repetitive, or unknown in size (every route, every package in a monorepo, every finding to verify), stop hand-dispatching and escalate to a dynamic Workflow — describe the task and include the word "workflow" so an orchestration script pipelines the items across background subagents with a verification stage built in. Rule of thumb: a few independent tasks → dispatch agents here; dozens of items or fan-out-then-verify → a Workflow.
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:
Don't use when:
Group failures by what's broken:
Each domain is independent - fixing tool approval doesn't affect abort tests.
Each agent gets:
// 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
When agents return:
Good agent prompts are:
The #1 reason subagents fail is context starvation. The controller thinks it provided enough context but didn't. When in doubt, include more:
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. The abort implementation is in
src/agents/agent-tool-handler.ts (the abortTool method around line 150).
Tests use a helper createMockToolStream() from test-utils.ts.
Your task:
1. Read the test file and the implementation file
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
4. You may read other files if needed to understand the system
Do NOT just increase timeouts - find the real issue.
Return: Summary of what you found and what you fixed.
❌ 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, test names, AND relevant source code inline
❌ 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"
❌ "Don't explore": Agent can't read files → guesses → fails → you redo the work ✅ Permission: "Read any files you need to understand the system"
❌ Tight tool budget (15 calls): Agent rushes → BLOCKED → you redo the work ✅ Reasonable budget: Let agents work until done, cap at 25-30 for safety
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)
Scenario: 6 test failures across 3 files after major refactoring
Failures:
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:
Integration: All fixes independent, no conflicts, full suite green
Time saved: 3 problems solved in parallel vs sequentially
After agents return:
From debugging session (2025-10-03):
npx claudepluginhub houseofmvps/ultraship --plugin ultrashipDelegates independent tasks to parallel subagents, each with isolated context. Use when 3+ test failures or subsystems have unrelated root causes.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
Dispatches isolated agents to investigate or fix multiple independent problems in parallel (e.g., separate failing test files, unrelated subsystems). Saves time by avoiding sequential debugging when problems don't share state or dependencies.