你的人工智能已经有手了。ATO是你驾驶它们的座位。 制定规则。监控每一个工具调用。杀掉逃跑的。把每个工具实际做了什么对比你的代码。多运行时。本地优先。麻省理工。

三个人工智能都可能*走过代码。你看是哪个走了，哪个刚回复了。 那是驾驶舱。

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30秒后

下载→（Tauri 2.x ·麻省理工学院）

demo-war-room 运行时不带 API 密钥——选择你配置的运行时，然后退回到 Ollama。30 秒内收到第一个接收。

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研究（开放多模型编码基准）

发现：更高的底线，更高的天花板。我们在49个污染审计的LiveCodeBench编码任务（执行分级、计量收据）上运行了九个单模型和九个协调配方。多模型协调没有击败最佳单一模型。它提升了弱模型（~+9个问题）和上限高峰（战情室可能会输给自己最优秀的成员）。级联的限制是验证门，而非强力收尾者。完整文章、草稿及重演路径：

ATO — The cockpit where every AI follows your rules

Your AIs already have hands. ATO is the seat you fly them from. Set the rules. Watch every tool call. Kill the runaway. Compare what each one actually did to your code. Multi-runtime. Local-first. MIT.

$ ato review --reviewer claude --reviewer codex --reviewer gemini --against main
# illustrative output — your numbers (cost, duration, tool calls) will vary by runtime, model, and diff size

review session 7F3A1B6E · 3 reviewers · your rules: read-only, repo-scoped, killable

  CLAUDE     🔧 verified via 4 tool calls
             flagged 2 issues — XSS in src/render.ts:142, auth bypass in api/login.ts:87
             read_file ×3 · grep ×1 · 6.4s · $0.024 · 0 files written (read-only mode)

  CODEX      🔧 verified via 6 tool calls
             flagged 3 issues incl. SQL injection in db/queries.ts:64
             ← caught one claude missed by grep'ing for raw string concatenation
             read_file ×4 · grep ×2 · 7.1s · $0.004 · 0 files written

  GEMINI     ⚠️ prompt-only — didn't open the code
             flagged 2 issues from the diff alone (XSS×2, CSRF)
             5.9s · $0.001 · 0 tool calls · downweight in synthesis

  closer:    4 unique findings, 1 disputed.
             tags: security, sql-injection. cost: $0.029 total.
             every tool call, every byte read, archived to ~/.ato/local.db
             paste-ready transcript at .ato/reviews/7F3A1B6E.md

Three AIs all could have walked the code. You see which ones did, and which one just replied. That’s the cockpit.

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In 30 seconds

# macOS
brew install willnigri/ato/ato && ato demo-war-room

# Linux
curl -fsSL https://agentictool.ai/install.sh | sh && ato demo-war-room

# Desktop app (macOS · Windows · Linux)

Download → (Tauri 2.x · MIT)

demo-war-room runs without API keys — picks your configured runtimes, falls back to Ollama. First receipt in 30 seconds.

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Research (open multi-model coding benchmark)

Finding: higher floor, lower ceiling. We ran nine single models and nine coordination recipes on 49 contamination-audited LiveCodeBench coding tasks (execution-graded, metered receipts). Multi-model coordination did not beat the best single model. It lifted weak models (~+9 problems) and capped peaks (war rooms can lose to their own best member). Cascades were limited by the verifier gate, not the strong closer. Full write-up, draft paper, and re-run path: