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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 ga
Passed 19 of 24 test cases with the skill, and 6 of 24 without it.
and 22 more in the full report
15 fixed5 passed either way4 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 15 test cases the skill fixed. Same model, same prompt, with and without the skill.
All refactoring, auditing, and propagation waves are complete. The user opts in to generate PR descriptions and changelog updates. Which model tier should execute this summary work?
| Checked | Without skill | With skill |
|---|---|---|
| assigns Haiku model tier to Wave 4 Notify tasks | Missed | Passed |
The instructions your model reads when the skill loads.
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)
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.
If the task doesn't clearly fit, say so and propose doing it inline instead of spinning up an army.
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.test cases passed, vs 6 / 24 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.