Individual skill

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.

plugins/agent-army/skills/agent-army/SKILL.md

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Last checked: Nov 10, 2026

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Repository stars (not skill ratings): 422
Repository last updated: Oct 20, 2026
License: MIT

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# 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.

```
Commander (you — Fable or Opus, the session model)
 |
 |-- Layer 1: Team (3 to 50+, each = own 1M context, L1 tier from power level)
 |    |-- Agent A (1M) -- Sub-agent A1, A2, ...  (L2 tier)
 |    |-- Agent B (1M) -- Sub-agent B1, B2, ...  (L2 tier)
 |    |-- Agent C (1M) -- Sub-agent C1, C2, ...  (L2 tier)
 |    |-- ... (no cap)
```