Use for authorized reverse engineering of browser extensions (Chrome/Firefox) including manifest analysis, background workers, and extension-based credential or traffic logic recovery.
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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。
□ crx 解压 / 从 profile 取扩展目录
□ manifest.json：permissions、host_permissions、background、content_scripts
□ 评估过度权限（<all_urls>、webRequest、debugger）
□ service_worker / background 入口
□ content_script 注入点与世界（isolated）
□ chrome.storage / IndexedDB 密钥
□ 与 `js-reverse` 相同：Observe 网络与消息传递（runtime.sendMessage）
□ 开发者模式加载解压目录
□ chrome://extensions 检查错误
□ DevTools 附加 service worker
□ 必要时 Frida/浏览器 CDP（jshookmcp）
| 工具 | 用途 |
|---|---|
| 解压/jq | manifest |
| Chrome DevTools | worker 调试 |
| js-reverse 工具链 | 深度 JS |
| YARA | 恶意扩展规则 |
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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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