← ClaudeAtlas

delegatelisted

Fan out independent research, summary, extraction, or fact-finding subtasks to a cross-family delegate — the reviewer by default — for parallel execution alongside the active primary where dual-model coverage adds value. Use when the user says "delegate to the reviewer," "split this with the reviewer," "fan this out," "have the reviewer take half of these," "research these in parallel with the reviewer," "divide and conquer with the reviewer," or when the active primary would otherwise process many independent items serially and cross-family coverage would help.
sumitake/agent-collab · ★ 0 · AI & Automation · score 63
Install: claude install-skill sumitake/agent-collab
## Unified runtime invocation Resolve the **plugin root** from this loaded file: `SKILL.md` is at `<plugin-root>/skills/<skill-name>/SKILL.md`. Invoke only `python3 "<plugin-root>/coordinator.py"` and send one bounded JSON request on stdin. Before constructing it, read the **Coordinator request schema** in `<plugin-root>/README.md`; never invent fields or route/action pairs. The public coordinator re-observes the active host/model, captures artifact provenance, excludes same-family routes, and verifies the co-packaged native manifest. It runs standalone from the installed plugin. Never discover a provider executable or reconstruct a raw command. Frontmatter `tier` is a routing recommendation, never a coordinator request field. For a review, cross-check, tiebreaker, or fallback over an authored artifact, capture its exact UTF-8 content and observed author model in the optional `artifact` object even when governance is false; never paste it into the prompt as a provenance substitute. # Delegate — fan out independent subtasks for parallel cross-family coverage When the work is **the same operation across many independent items**, splitting the workload between the active primary and the reviewer cuts latency AND adds cross-family coverage value (the two families surface different sources, framings, defaults). This is **map-reduce with two readers**, not just parallel dispatch — the latter is what the active primary's native parallel tool (e.g., subagent fan-out) does without