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概要と使いどころ
Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.
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Modern JavaScript (ES2022+) patterns for clean, maintainable code. Use when working with modern JavaScript features like optional chaining, nullish coalescing, or ESM.
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Go developer toolchain — gopls LSP diagnostics, linting, formatting, and vet. Use when setting up Go tooling, running linters, or integrating gopls with Claude Code.
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Closed-loop policy over the canonical Session/Run chain
日本語の概要は準備中です。原文の説明を表示しています。
Intent-to-chain planner over the canonical Session/Run lifecycle
日本語の概要は準備中です。原文の説明を表示しています。
Audit Hex deps for supply-chain security risk — bidi chars; Use after mix deps.update, when checking if a package…
日本語の概要は準備中です。原文の説明を表示しています。
Audit Hex deps for supply-chain security risk — bidi chars, compile-time exec, maintainer changes, typosquats, CVEs. Use after mix deps.update, when checking if a package upgrade is safe, or reviewing mix.lock PR diffs.
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OTP/BEAM patterns and Elixir idioms — GenServer, Supervisor, Task, Registry, pattern matching, with chains, pipes. Use when designing processes or debugging BEAM issues.
日本語の概要は準備中です。原文の説明を表示しています。
Audit Hex deps for supply-chain security risk — bidi chars, compile-time exec, maintainer changes, typosquats, CVEs. Use after mix deps.update, when checking if a package upgrade is safe, or reviewing mix.lock PR diffs.
日本語の概要は準備中です。原文の説明を表示しています。
马斯克的思维操作系统。基于传记、播客、推文、法庭证词、决策记录和外部批评的深度调研， 提炼5个核心心智模型、8条决策启发式和完整的表达DNA。 用途：作为思维顾问，用马斯克的视角分析问题、审视决策、拆解成本结构、挑战行业假设。 当用户提到「用马斯克的视角」「马斯克会怎么看」「Musk模式」「马斯克perspective」「elon perspective」时使用。 即使用户只是说「这个成本合理吗」「从第一性原理想想」「白痴指数是多少」「五步算法」「能不能垂直整合」也可触发。 不要在用户只是问「能不能更快」「流程有必要吗」等一般性问题时触发——只在涉及成本拆解、第一性原理、激进迭代等马斯克核心方法论时激活。
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Use this skill when the user wants to build tool/scripts or achieve a task where using data from the Hugging Face API would help. This is especially useful when chaining or combining API calls or the task will be repeated/automated. This Skill creates a reusable script to fetch, enrich or process data.
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Typosquatting detection, install script analysis, dependency confusion prevention, and phantom dependency detection for npm/pip.
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Prompt templates, few-shot examples, chain-of-thought, structured output, evals
日本語の概要は準備中です。原文の説明を表示しています。
Protobuf schema design, streaming patterns, interceptor chains, deadline propagation, and error handling for gRPC services.
日本語の概要は準備中です。原文の説明を表示しています。
Engineer effective LLM prompts using zero-shot, few-shot, chain-of-thought, and structured output techniques. Use when building LLM applications requiring reliable outputs, implementing RAG systems, creating AI agents, or optimizing prompt quality and cost. Covers OpenAI, Anthropic, and open-source models with multi-language examples (Python/TypeScript).
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Constructs secure, efficient CI/CD pipelines with supply chain security (SLSA), monorepo optimization, caching strategies, and parallelization patterns for GitHub Actions, GitLab CI, and Argo Workflows. Use when setting up automated testing, building, or deployment workflows.
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LLM and ML model deployment for inference. Use when serving models in production, building AI APIs, or optimizing inference. Covers vLLM (LLM serving), TensorRT-LLM (GPU optimization), Ollama (local), BentoML (ML deployment), Triton (multi-model), LangChain (orchestration), LlamaIndex (RAG), and streaming patterns.
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Assembles component outputs from AI Design Components skills into unified, production-ready component systems with validated token integration, proper import chains, and framework-specific scaffolding. Use as the capstone skill after running theming, layout, dashboard, data-viz, or feedback skills to wire components into working React/Next.js, Python, or Rust projects.
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Translate and dub a video into another language with voice cloning and lip-sync, powered by HeyGen Video Translation. The presenter keeps their face, their voice is cloned into the target language, and lips re-sync to the new audio — viewers see the same person speaking natively. Use when: (1) localizing an existing video into one or more languages ("translate this video to Spanish", "make this in French and German", "dub this into Japanese", "I need this in 10 languages for a launch"), (2) the user has a finished video and wants the SAME presenter speaking another language (not a new presenter — that's heygen-video), (3) podcast / audio-only translation ("translate this podcast", "dub the audio but keep my video"), (4) high-stakes translations where the user wants to review/edit subtitles before final render (the proofreads workflow), (5) "translate my video", "dub this", "localize this clip", "make a multilingual version", "subtitle and dub". Returns the translated video URL (or audio file for audio-only mode), one per target language. Chain signal: if the user wants to CREATE a new video in another language (no source video exists yet), route to heygen-video and write the script in the target language — do not use heygen-translate. Use heygen-translate only when there is an existing source video to localize. NOT for: creating new videos from scratch (use heygen-video), avatar creation (use heygen-avatar), TTS-only synthesis (use heygen-video with audio-only output), or text-only translation.
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Create a persistent HeyGen avatar — a reusable face + voice identity for the agent, the user, or any named character — powered by HeyGen Avatar V technology. Prompt-based creation by default (description → HeyGen builds it); photo upload is optional for real-person digital twins. Use when: (1) giving the agent a face + voice so it can present videos ("bring yourself to life", "create your avatar", "give yourself an avatar", "design a presenter", "set up an avatar", "let's make an avatar"), (2) the user wants to appear in videos as themselves ("create my avatar", "I want my face in a video", "digital twin of me", "build me an avatar"), (3) building a named character presenter ("create an avatar called Cleo", "design a character named X"), (4) establishing HeyGen identity before making videos — the correct FIRST step when no avatar exists yet. Chain signal: when the user says both an identity/avatar action AND a video action in the same request ("create an avatar AND make a video", "set up identity THEN create a video", "design a presenter AND immediately record"), run heygen-avatar first, then heygen-video. Returns avatar_id + voice_id — pass directly to heygen-video to create HeyGen videos. NOT for: generating videos (use heygen-video), translating videos, or TTS-only tasks.
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Use the open-source free `coverlet` toolchain for .NET code coverage. Use when a repo needs line and branch coverage, collector versus MSBuild driver selection, or CI-safe coverage commands. USE FOR: coverlet setup; CI line or branch coverage; choosing between collector and MSBuild drivers. DO NOT USE FOR: coverage report rendering by itself; repos that intentionally use a different coverage engine. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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Diagnoses and fixes .NET MAUI development environment issues. Validates .NET SDK, workloads, Java JDK, Android SDK, Xcode, and Windows SDK. All version requirements discovered dynamically from NuGet WorkloadDependencies.json — never hardcoded. Use when: setting up MAUI development, build errors mentioning SDK/workload/JDK/Android, "Android SDK not found", "Java version" errors, "Xcode not found", environment verification after updates, or any MAUI toolchain issues. Do not use for: non-MAUI .NET projects, Xamarin.Forms apps, runtime app crashes unrelated to environment setup, or app store publishing issues. Works on macOS, Windows, and Linux.
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LLM and AI application security testing — prompt injection, jailbreak resistance, OWASP LLM Top 10 (2025), RAG and agent/tool-use security, model supply chain, and AI red teaming for authorized assessments
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Cyber threat intelligence production — the intelligence cycle, IOC extraction/normalization/enrichment, STIX/TAXII and MISP, structured analytic models (Diamond, Kill Chain, ATT&CK), source scoring, actor/campaign tracking, and finished intelligence reporting
日本語の概要は準備中です。原文の説明を表示しています。