Results for “parallel-agents”

Concurrent investigation of independent failures. Use when multiple unrelated issues need parallel resolution.

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Use when legacy prompts or older framework flows reference `dispatching-parallel-agents` and you need the modern runtime to resolve that capability cleanly.

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Assign independent bugs or test failures to separate agents that work at the same time. Define each agent’s scope and expected report, then check for conflicting changes and run the full test suite before integrating fixes.

• Investigating test failures with unrelated causes
• Fixing independent problems in separate subsystems
• Defining focused tasks for multiple agents

Coordinate specialized agents in Claude Code to divide development and review tasks, pass findings between stages, and combine results into one report with prioritized recommendations and action items.

• Reviewing code from security, performance, and quality perspectives
• Coordinating frontend, backend, and database work
• Combining specialist findings into a prioritized report

Split independent debugging or repair tasks among multiple AI agents. Define a focused scope, constraints, and expected report for each agent, then review their changes, check for conflicts, and test the combined result.

• Investigating unrelated failures across test files
• Assigning separate subsystems to different agents
• Writing focused tasks with clear constraints

Investigate independent bugs or test failures concurrently by assigning each problem area to a separate agent. Define clear boundaries and expected reports, then review the fixes, check for conflicts, and run the full test suite before integration.

• Investigate unrelated test failures in parallel
• Split independent subsystem bugs among agents
• Write focused assignments with clear boundaries

Helps decide whether to handle a task directly, create a subagent, or route it to an agent already familiar with the work. The choice depends on required background knowledge and whether plausible but incorrect results can be checked.

• Choosing who should handle a task
• Delegating self-contained research with verifiable sources
• Routing context-heavy reviews to an informed agent

Decompose large tasks across parallel agents — use for migrations, multi-file refactors, or batch work

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Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

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Parallel Agent Orchestration

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Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

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Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies.

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Use when executing a written implementation plan with independent tasks in the current session where delegation beats inline coordination cost; otherwise inline. Ad-hoc 2+ tasks without a plan use dispatching-parallel-agents.

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Use when facing 2+ independent tasks without a written plan, with no conflicting shared mutable state or sequential dependencies, where parallel delegation beats inline cost; otherwise inline. Planned tasks use subagent-driven-development.

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Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

The English summary is being prepared. Showing the original description.

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

The English summary is being prepared. Showing the original description.

Parallel Agent Orchestration

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Spawns multiple AI coding agents to work on related GitHub issues concurrently using git worktrees. Use when breaking down a large feature into multiple issues, running parallel agents with --print flag, or managing wave-based execution of related tasks.

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Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

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Stack Honey onto Superpowers-style workflows (subagent-driven-development, dispatching-parallel-agents, executing-plans) and any orchestration that dispatches fresh subagents. Dispatched subagents run in isolated context and do NOT inherit the session's Honey hook, so they emit full-fat code and verbose reports. Use when you are about to dispatch implementer/reviewer/fixer/parallel subagents: it gives the exact Honey directive to paste into each dispatch prompt, with a worker variant and a reviewer variant, so the levers apply inside the subagents too — where the multiplied cost actually is.

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Plan, implement, or review dispatching parallel agents work in an existing codebase with compatibility, security, and verification controls. Use when the user explicitly requests dispatching parallel agents work.

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The parallel fan-out primitive. Routed to by any skill or command that splits work across independent units and dispatches an agent per unit — subagent-driven-development, /sprint, parallel /review. It owns the dispatch/collect/funnel discipline: bound concurrency, isolate units, collect every result, dedupe overlap, and funnel through finding-triage then the read-only verdict-aggregator. Raw agent output is never consumed before the funnel runs; an agent that errors records its unit as incomplete without corrupting the batch.

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OPTIONAL per-task isolation for autonomous parallel work. Routed to only on explicit opt-in by subagent-driven-development or dispatching-parallel-agents, so parallel units mutate files without colliding. Stands up one worktree per unit, works it in isolation, then integrates each unit back onto the caller's working branch for the caller's single commit-gate + finishing-a-development-branch exit. Never on the default path; it does not bypass a gate or finish per unit.

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Splits a coding task into independent parallel agent workstreams with disjoint write sets, explicit inputs and outputs, dependency ordering, and a merge/review plan. Use when several subtasks can proceed without shared mutable state. Not for tightly coupled edits, one failing root cause, or parallel changes to the same files.

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