Agent Skills: Parallel Launch

Parallel Launch

Decompose the given task into independent agent groups and execute them in broad parallel.

Process

1. Analyze the task and identify independent concerns that can run concurrently.

   • Each concern must be self-contained: no shared mutable state, no ordering dependency.
   • If concerns have dependencies, sequence the dependent batch after the independent batch completes.
   • Consult delegation scenarios for parallelism decisions.

2. Design agent groups for each independent concern:

   • Assign a clear, scoped objective (one concern per agent).
   • Select the appropriate tailored agent type (Explore, Plan, or a domain specialist) — prefer a task-specific agent over a general one.
   • Define expected output format so results can be composed.

3. Launch all independent agents in a single tool call.

4. Compose results once all agents complete:

   • Merge non-conflicting outputs directly.
   • For conflicting or overlapping results, reconcile and present trade-offs to the user.
   • If any agent failed or returned incomplete results, report the gap and propose a targeted follow-up.

5. Review composed output by dispatching a review agent to verify:

   • Completeness: All original concerns addressed, no gaps.
   • Consistency: No contradictions between agent outputs.
   • Accuracy: Claims are substantiated, sources checked, no hallucinated findings.
   • Scope: Nothing extra built beyond what was asked.
   • For implementation work, additionally verify spec compliance and code quality.

6. Report to user only after review passes.

Constraints

• Agents per batch: match the number of truly independent concerns (avoid artificial splitting).
• Each agent prompt must include full context; agents do not share memory.
• If the task has fewer than 2 independent concerns, execute directly instead of launching agents.