# Dispatching Subagents > Decide whether to delegate work to subagents, set each one's isolation boundary, and verify their output with external evidence. Use when considering fanning work out to parallel agents, orchestrating multiple agents, or reviewing whether a multi-agent result can be trusted. - Skill: `jonhill90/dispatching-subagents` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add jonhill90/dispatching-subagents` - Raw SKILL.md: https://api.skillmd.com/api/skills/jonhill90/dispatching-subagents/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: jonhill90 (https://skillmd.com/u/jonhill90) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/jonhill90/dispatching-subagents --- # Dispatching Subagents Delegation is an orchestrator-workers decision, not a reflex. It costs roughly an order of magnitude more tokens than doing the work inline and it removes your ability to see what happened. Earn it. Portability: dispatch mechanisms differ per harness and change often. This skill is the decision procedure, not the API. Use whatever mechanism the current harness provides; where none exists, execute the same plan sequentially in this context. The boundaries and verification rules below are unchanged either way. ## Decide first Delegate only when at least one is true: - The work is **breadth-first**: several independent paths must be explored and their results do not depend on each other. - The material **exceeds one context window** and splitting it loses nothing. - A **verifier must be independent** of the maker to be worth anything. Do not delegate when: the subtasks are sequential and each needs the previous one's output; the task is small enough to read directly; you cannot state the success criterion for a worker in one paragraph; or you would be unable to check the result yourself. If none of the three conditions holds, do the work inline and say so. ## Set the isolation boundary Before dispatching, state for each worker what it knows about the others. Default to **nothing**: a self-contained task description, the required output format, and a fresh context. Shared state between workers is a cost — justify each piece of it. Write the boundary down in the plan. "Worker A does not see B's findings" is a design decision, not an omission. ## Tier the models Put reasoning-heavy planning, decomposition, and final review on the strongest model. Put well-specified execution on cheaper ones. A worker whose task cannot be specified tightly enough for a cheaper model is a sign the decomposition is not finished. ## Verify with external evidence Agreement between workers is not verification. Several agents on the same model reading the same flawed context will agree with each other and be wrong together. A result is verified only by evidence from outside the agents: - test or build output, pasted; - a command's actual return value; - a file or record that can be read back; - human review. The maker never grades its own work. If a verifier is itself an agent, it must be given the artifact and the criterion, not the maker's reasoning. **An author cannot audit its own bookkeeping.** This is narrower than "the maker never grades its own work" and it is the case people skip, because the bookkeeping does not feel like the work. A plan that assigns files to parallel workers, a manifest of what each one owns, a dependency order, a per-task validation block — the author wrote each of those while holding the intent in mind, and re-reads them the same way. Two tasks claiming the same file, a step whose stated dependency exists only in prose, a command named in the plan that is not a real command: none of these are visible from inside the head that wrote them. A separate context reading the *finished* artifact finds them in one pass, and finds them mechanically rather than by insight — intersect the file sets, resolve every named command, check that each declared dependency appears in something the scheduler can read. Where the audit is mechanical, prefer a script to a reviewer; a duplicate-path detector that runs before every dispatch beats an agent asked to be careful. Budget for this as its own dispatch, after the artifact is complete and before anything executes it. It is usually the cheapest reviewer in a fan-out and the one that finds the defects that would have collided. ## When independence is not available Sometimes no genuinely independent reviewer exists — only one reviewing agent is running, and it also contributed to the change under review. Three moves are possible and only one is right: 1. **Proceed silently**, saying nothing about the conflict — a hidden conflict is a defect. 2. **Stall the queue** until independence returns — this looks safer but is a failure too, just a quieter one, when the work is otherwise mergeable. 3. **Review anyway, and declare the conflict in the first line of the review**: what the reviewer contributed to the change, and why review is proceeding without independence regardless. A hidden conflict is a defect; a declared one is a tradeoff — the record can be judged either way later, but only if it says so. Two boundaries keep this from drifting into cover for bad practice: - **The strictly worse case stays refused.** A reviewer approving its own work with no second reader of any kind — no declaration, no evidence, no fixup-only pass — is not made acceptable by naming it. Declaring a conflict is not a licence for that case. - **The exception is scoped and expires.** State when independence is expected back, and stop taking the exception once it returns. An exception with no stated end silently becomes the norm. When you get to choose which agent reviews, prefer one that only touched a fixup over one that wrote the substantive change, and say in the review which it was. This traces back to a standing independent reviewer becoming unavailable for a bounded window: rather than stalling a queue of otherwise-mergeable work indefinitely, a contributing agent reviewed its own queue with the conflict named explicitly in each review, while still refusing the strictly-worse case above. The exception was scoped to expire once independence returned. ## Report honestly State how many workers ran, what each was asked, what came back, and which claims are backed by external evidence versus by an agent's assertion. Unverified worker output is reported as unverified. ## Stop conditions Stop and consolidate when: workers return contradictory results and no external evidence settles it; a worker fails twice on the same subtask; or the dispatch has cost more than doing the work inline would have. Contradiction is a finding to report, not noise to re-roll away.