Agent skill · software engineering · onewave-ai
agent-army
Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.
Why this skill is useful
Adds a framework for deploying parallel agent hierarchies with specific orchestration and safety checks that fundamentally extend the AI's capabilities.
What it needs
Requires git installed locally. About 10k tokens when loaded. Last updated 2026-07-15. 242 stars on the source repository.
What this skill does
Agent Army A 2-layer parallel execution framework. The Commander is the top-tier model — Fable by default, or Opus if that's the session model — and does the thinking: recon, composition, briefing, verification. It orchestrates swarms of subordinate models whose tiers the user picks at deploy time (see Power Level). Each Layer 1 agent has its own full context window (not a slice). Each spawns Layer 2 sub-agents under it. The result is many independent brains running at once — not one brain divided. Swarm vs. army: A swarm splits one context window across sub-agents — one brain, divided. An army gives each Layer 1 member its own window. That difference is the whole point of this skill. When to use Large refactors spanning many files Multi-file color / style / naming / API migrations Broad codebase audits (security, a11y, performance, dead code) Bulk content generation or transformation Any task with 6+ independent units of work that can run simultaneously When NOT to use Fewer than 6 independent units of work — just do it directly Heavy sequential dependencies where each step needs the last one's output Single-file changes Tasks needing one coherent authorial voice across all output (parallel agents drift) If the task doesn't clearly fit, say so and propose doing it inline instead of spinning up an army. <mandatory-rules> MANDATORY RULES 1. EVERY Layer 1 agent MUST spawn 2+ sub-agents. No exceptions. If you're about to deploy an L1 agent with no sub-agents, STOP and restructure. 2. NEVER silently shrink the army. Match the user's chosen tier. If you must deviate, say so out loud and why. 2b. NEVER silently downgrade models. Pass model: explicitly on every Agent call at the user's chosen power level. Omitting it inherits the session model — that's a silent Max Power bill. 3. Sub-agent deployment instructions go INSIDE the Layer 1 brief. If they're missing, the sub-agents will never be created. 4. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills onewave-ai/agent-army