Use for authorized security testing of desktop thick clients including local storage, update channels, IPC, traffic, and client-side trust boundaries.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
□ 进程树、子进程、驱动/服务
□ 监听端口与出站域名
□ 本地敏感路径：%APPDATA%、Keychain、注册表
□ 明文配置、硬编码密钥、调试开关
□ DLL 劫持/搜索顺序（Windows）
□ 数据库文件（SQLite）权限与加密
□ IPC：谁可连接？是否鉴权？
□ 系统代理 / 应用自定义 TLS
□ 证书钉扎 → 联合 mobile/js 方法学或 Frida
□ API 越权：客户端隐藏的管理接口
□ .NET → dotnet-reverse；原生 → ida/ghidra；Electron → asar + js-reverse
| 工具 | 用途 |
|---|---|
| Process Monitor / API Monitor | 行为 |
| Burp / mitmproxy | 流量 |
| dnSpy / IDA / Ghidra | 逆向 |
| Sysinternals | Windows 面 |
| asar / nexe 检测 | Electron |
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Train and optimize AI agents using Microsoft's Agent Lightning framework with reinforcement learning. Use when setting up agent training, instrumenting agents with tracing, configuring LightningStore, implementing reward functions, or optimizing prompts with RL/APO algorithms.
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Post-run self-evaluation system that scores agent output on correctness, clarity, actionability, and conciseness. Use after /team runs, skill executions, or when explicitly asked to evaluate output quality.
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Create AI marketing videos for ads, promos, product launches, and brand content. Models: Veo, Seedance, Wan, FLUX for visuals, Kokoro for voiceover. Types: product demos, testimonials, explainers, social ads, brand videos. Use for: Facebook ads, YouTube ads, product launches, brand awareness. Triggers: marketing video, ad video, promo video, commercial, brand video, product video, explainer video, ad creative, video ad, facebook ad video, youtube ad, instagram ad, tiktok ad, promotional video, launch video
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Use when building AI features into a product: LLM integration, RAG pipelines, guardrails, streaming, AI UX, prompt engineering, or AI cost control. Treats prompts as code and validates every model output.
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Your AI research and engineering brain trust. 59 named personas across 8 cells covering frontier labs, applied product, model architecture, reasoning/RL/agents, alignment and interpretability, theory and science of DL, multimodal and…
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Use when designing a new REST or GraphQL API, reviewing an API spec before implementation, setting team API standards, or migrating REST to GraphQL. Covers resources, HTTP semantics, pagination, error handling, and pitfalls.
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