orchestrating-subagents

Defines tiering, fan-out, and prompt contracts for delegating work to subagents.

Updated Sep 14, 2026
One-click install
npx skills add https://github.com/pandejesal/drone-nav-sar --skill orchestrating-subagents-pandejesal
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: orchestrating-subagents
Source: https://github.com/pandejesal/drone-nav-sar/tree/main/.swarm/bundled-skills/orchestrating-subagents
Command: npx skills add https://github.com/pandejesal/drone-nav-sar --skill orchestrating-subagents-pandejesal

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Delegating work to subagents without clear rules wastes tokens on overlapping explorers, weakens validation gates, and pollutes the main context with raw transcripts. This Skill defines how to assign agent types, models, and effort levels per role so delegation stays cheap where it can be and rigorous where it must be. ## Core Features & Use Cases - Role-to-tier mapping: Assigns explorers to cheaper tiers while mandating the strongest model and high effort for reviewers and critics. - Fan-out discipline: Launches 2-4 parallel agents only for disjoint scopes, in a single message, scaling waves rather than width. - Subagent prompt contract: Requires every delegation prompt to state scope, deliverable structure, evidence bar with file:line references, status labels, and output bounds. - Use Case: When running a swarm-mode PR review, launch parallel explorers over disjoint directories, then hand the consolidated findings to a fresh-context reviewer that independently re-derives each claim before approval. ## Quick Start Ask the agent to orchestrate a swarm-mode task by launching parallel explorer subagents with scoped prompts and a fresh independent reviewer for validation.

Frequently Asked Questions about orchestrating-subagents

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I orchestrate subagents for parallel code exploration?

Launch 2-4 explorer agents in a single message, each with a disjoint scope stated in one line before launching. Give each a scoped prompt defining deliverable structure, evidence bar with file:line references, and a compact output bound.

What model and effort should subagent reviewers use?

Reviewers and critics must use the session's strongest model at high effort with a fresh context. Only explorers may be tiered down to cheaper or faster models, since recall misses are caught by the reviewer gate.

When should I not delegate a task to a subagent?

Skip delegation for single-fact lookups resolvable with one or two targeted Grep or Read calls, or when you already know the file and symbol. Delegation should buy breadth, isolation, or independence.

Can a subagent spawn its own subagents?

Nesting depends on the harness and agent type, so check whether a subagent tool is available before assuming. If unavailable, perform a clearly labeled fallback self-review and disclose that independent review was not possible.

Why must reviewers be fresh agents instead of continued conversations?

A reviewer must re-derive findings independently rather than confirm the author's reasoning. Give reviewers the claims and locations without the author's justification, and set an adversarial default of DISPROVED or UNVERIFIED unless code evidence supports the finding.