Parallel dispatch — one user turn, N parallel workers

The default failure mode of the primary Claude is executing multi-task user turns sequentially. That is measurably slower on I/O-bound work (gh, WebFetch, git, log polling) and burns cache repeatedly. This skill enforces a different pattern: read the whole turn, split into independent units, dispatch all units in one assistant response.

Phase 1 — Split the request

Read the user's message and enumerate INDEPENDENT actionable items. Two items are independent if:

• Neither reads the other's output.
• The user's phrasing lists them as parallel (A, B, C, X and also Y, all of these).
• Order does not matter for correctness.

Items are NOT independent if:

• Item B needs a value / decision from item A.
• User uses sequencing words (first A, then B, once A finishes, B).
• Item B is a follow-up (check A, and if there's an issue, B).

If in doubt: sequential. Do NOT force parallelism when it introduces ordering risk.

If only ONE item is present, this skill does not apply. Return control immediately without emitting anything.

Phase 2 — Route each unit

For every independent unit, pick exactly one worker:

If a unit needs live user approval mid-flight (e.g. anything that will post to a shared surface — external comment, PR create, etc.), do NOT parallelise it — hand it back to the parent as sequential.

Phase 3 — Emit all workers in ONE response

Critical: emit every Agent(...) call in the same assistant response. Claude Code executes tool calls in the same response concurrently; splitting across responses is sequential.

Concrete example. User says: "grep for PaymentIntent in packages/api, list all TS files that import date-fns, and find where MAX_RETRIES is defined."

Correct emission (one response, three tool calls):

Agent(subagent_type="Explore", description="grep PaymentIntent", prompt="grep for symbol 'PaymentIntent' under packages/api and return file:line hits.")
Agent(subagent_type="Explore", description="date-fns importers", prompt="Find every TS file that imports from 'date-fns'.")
Agent(subagent_type="Explore", description="MAX_RETRIES definition", prompt="Find where MAX_RETRIES is defined and return the file:line and the value.")

Incorrect — three separate responses:

Response 1: Agent(Explore, PaymentIntent)
Response 2: Agent(Explore, date-fns)
Response 3: Agent(Explore, MAX_RETRIES)

Phase 4 — Aggregate

When all subagents return, produce ONE aggregated response for the user. Never regurgitate each subagent's raw output — group by outcome (found / not-found / errored) and put the most actionable bucket first.

If any subagent errored, surface the error inline with the unit's label; do not retry silently.

Concurrency budget

• Hard cap: 12 subagents per response. Beyond that Claude Code starts serializing.
• If the user's turn has > 12 independent units, split into two responses of ≤ 12 each. Announce the split briefly (Fanning out in two batches (12 + N)…).
• Do NOT chain the second batch behind the first if the units are truly independent — emit the second batch as soon as the first returns.

Anti-patterns

• Fake parallelism (sequential in disguise). Emitting one Agent per response and pretending it is parallel. It is not.
• Fake independence. Splitting a workflow that has dependencies (fix bug → run tests → commit) into parallel workers. That will corrupt state.
• Over-parallelising trivial work. Do not spawn a subagent for a single gh pr view when the parent can just call Bash directly in one turn.
• Skipping the aggregation. Returning raw subagent transcripts to the user is noise. Always aggregate.
• Racing writes. If two units both edit the same file / repo / branch, they are NOT independent. Sequential.

When NOT to invoke

• Single-task user turns.
• Any user turn where ordering matters (all then, after, if X).
• Tasks that require the user's live approval mid-flight (posting to any shared / external surface).
• One-shot lookups where a fast Bash call in parent is cheaper than spawning a subagent.