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ACO swarm intelligence with modular Workflow composition and adversarial decision gates. Coordinator drives iteration loop; 4 composable Workflow scripts handle exploration, scoring, convergence, and synthesis — each with built-in adversarial patterns.
6 of 23 test cases passed with the skill.
Tokens, turns and time describe resource use, not a dollar price.
Lift withheld: 7 comparable cases; this report requires 8.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
Resume an existing session where team-session.json contains run_id 'run-3301'. When checking status with maestro, the run is marked as sealed.
| Checked | Without skill | With skill |
|---|---|---|
| Creates a new run via maestro run create and updates team-session.json with the new run details. | Missed | Passed |
The instructions your model reads when the skill loads.
<required_reading> @~/.maestro/workflows/run-mode-lite.md </required_reading>
ACO 蚁群优化 + 模块化 Workflow 编排 + 对抗决策。
继承 team-swarm 的蚁群算法核心（Python ACO 脚本），用 4 个可组合的 Workflow 脚本
替代 team-worker 架构，在每个决策节点注入对抗性 agent 模式。
SKILL.md (Coordinator — this file)
│
│ Phase 1: Config Generation (inline)
│ Phase 2: ACO Init (Bash: aco.py init)
│
│ Phase 3: Iteration Loop ×K
│ ┌──────────────────────────────────────────────────┐
│ │ 3a. Bash: aco.py select → assignments │
│ │ 3b. Workflow(wf-swarm-explore) ← 模块1 │
│ │ N ants parallel → ant_results │
│ │ 3c. Workflow(wf-swarm-score) ← 模块2 │
│ │ 3-vote adversarial scoring → verified_scores │
│ │ 3d. Write scores → Bash: aco.py update │
│ │ 3e. Workflow(wf-swarm-converge) ← 模块3 │
│ │ prosecutor/defender/judge → converged? │
│ │ 3f. if converged: break │
│ └──────────────────────────────────────────────────┘
│
│ Phase 4: Bash: aco.py report
│ Workflow(wf-swarm-synthesize) ← 模块4
│ 3-perspective analysis + arbitration → best-solution.md
| Module | Script | Args Interface | Adversarial Pattern | Returns |
test cases passed with the skill
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