所有 Skills
找到 8171 个 Skills
Skills 列表
react19-concurrent-patterns
Preserve React 18 concurrent patterns and adopt React 19 APIs (useTransition, useDeferredValue, Suspense, use(), useOptimistic, Actions) during migration.
github
ppt-master
基于 AI 驱动的多格式 SVG 内容生成系统。通过多角色协作，将源文档（PDF/DOCX/URL/Markdown）转换为高质量的 SVG 页面，并最终导出为 PPTX 演示文稿。当用户提出“做PPT”、“生成PPT”、“制作PPT”、“创建演示文稿”、“制作演示文稿”或提及“ppt-master”时触发使用。
hugohe3agent-supply-chain
Verify supply chain integrity for AI agent plugins, tools, and dependencies. Use this skill when: - Generating SHA-256 integrity manifests for agent plugins or tool packages - Verifying that installed plugins match their published manifests - Detecting tampered, modified, or untracked files in agent tool directories - Auditing dependency pinning and version policies for agent components - Building provenance chains for agent plugin promotion (dev → staging → production) - Any request like "verify plugin integrity", "generate manifest", "check supply chain", or "sign this plugin"
githubphoenix-tracing
OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.
githubphoenix-evals
Build and run evaluators for AI/LLM applications using Phoenix.
githubgithub-actions-hardening
Security hardening reviewer for GitHub Actions workflow files (.github/workflows/*.yml). Reasons about the Actions threat model that pattern matchers and general code linters miss — untrusted-input script injection, privileged triggers running fork code, mutable action references, and over-scoped tokens. Use this skill when asked to review, audit, harden, or secure a GitHub Actions workflow, when writing a new workflow, or for any request like "is this workflow safe?", "review my CI for security issues", "why is pull_request_target dangerous here?", "pin my actions", or "lock down GITHUB_TOKEN permissions". Covers script injection via ${{ }} interpolation, pull_request_target / workflow_run privilege escalation, SHA-pinning of third-party actions, least-privilege permissions, GITHUB_ENV/GITHUB_OUTPUT injection, secret exposure, OIDC over long-lived credentials, and self-hosted runner exposure on public repositories.
githubarize-trace
Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.
githublsp-setup
Enable code intelligence (go-to-definition, find-references, hover, type info) for any programming language by installing and configuring an LSP server for Copilot CLI. Detects the OS, installs the right server, and generates the JSON configuration (user-level or repo-level). Use when you need deeper code understanding and no LSP server is configured, or when the user asks to set up, install, or configure an LSP server.
githubarize-link
Generates deep links to the Arize UI for traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs. Produces clickable URLs for sharing Arize resources with team members. Use when the user wants to link to or open a trace, span, session, dataset, evaluator, or annotation config in the Arize UI.
githubgithub-actions-efficiency
Audit GitHub Actions workflow efficiency and recommend fixes to reduce CI minutes and costs.
githubarize-dataset
Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.
githubarize-annotation
Creates and manages annotation configs (categorical, continuous, freeform label schemas) and annotation queues (human review workflows) on Arize. Applies human annotations to project spans via the Python SDK. Use when the user mentions annotation config, annotation queue, label schema, human feedback, bulk annotate spans, update_annotations, labeling queue, annotate record, or human review.
githubarize-instrumentation
Adds Arize AX tracing to an LLM application for the first time. Follows a two-phase agent-assisted flow to analyze the codebase then implement instrumentation after user confirmation. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize tracing.
githubintegrate-context-matic
Discovers and integrates third-party APIs using the context-matic MCP server. Uses `fetch_api` to find available API SDKs, `ask` for integration guidance, `model_search` and `endpoint_search` for SDK details. Use when the user asks to integrate a third-party API, add an API client, implement features with an external API, or work with any third-party API or SDK.
githubarize-experiment
Creates, runs, and analyzes Arize experiments for evaluating and comparing model performance. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. Use when the user mentions create experiment, run experiment, compare models, model performance, evaluate AI, experiment results, benchmark, A/B test models, or measure accuracy.
githubfreecad-scripts
Expert skill for writing FreeCAD Python scripts, macros, and automation. Use when asked to create FreeCAD models, parametric objects, Part/Mesh/Sketcher scripts, workbench tools, GUI dialogs with PySide, Coin3D scenegraph manipulation, or any FreeCAD Python API task. Covers FreeCAD scripting basics, geometry creation, FeaturePython objects, interface tools, and macro development.
githubarize-evaluator
Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.
githubarize-ai-provider-integration
Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.
githubarize-prompt-optimization
Optimizes, improves, and debugs LLM prompts using production trace data, evaluations, and annotations. Extracts prompts from spans, gathers performance signal, and runs a data-driven optimization loop using the ax CLI. Use when the user mentions optimize prompt, improve prompt, make AI respond better, improve output quality, prompt engineering, prompt tuning, or system prompt improvement.
githubreact19-test-patterns
Provides before/after patterns for migrating test files to React 19 compatibility, including act() imports, Simulate removal, and StrictMode call count changes.
github
impeccable
当用户想要设计、重新设计、塑造、评审、审计、打磨、澄清、提炼、加固、优化、适配、添加动画、着色、提取或以其他方式改进前端界面时使用。涵盖网站、落地页、仪表盘、产品UI、应用外壳、组件、表单、设置、引导流程和空状态。处理UX评审、视觉层次、信息架构、认知负荷、可访问性、性能、响应式行为、主题化、反模式、排版、字体、间距、布局、对齐、颜色、动效、微交互、UX文案、错误状态、边界情况、国际化以及可复用的设计系统或令牌。也适用于需要更大胆或更令人愉悦的平淡设计、需要更安静的大声设计、对UI元素进行实时浏览器迭代，或追求技术上非凡的视觉效果。不适用于纯后端或非UI任务。
pbakausroundup-setup
Interactive onboarding that learns your communication style, audiences, and data sources to configure personalized status briefings. Paste in examples of updates you already write, answer a few questions, and roundup calibrates itself to your workflow.
githubemail-drafter
起草和审阅符合您个人写作风格的专业电子邮件。通过 WorkIQ 分析您已发送的电子邮件中的语气、问候语、结构和签名模式，然后为任何收件人生成上下文感知的草稿。用途：起草电子邮件、撰写电子邮件、编写电子邮件、回复电子邮件、跟进电子邮件、分析电子邮件语气、电子邮件风格。
githubthreat-model-analyst
对仓库和系统进行完整的STRIDE-A威胁模型分析和增量更新技能。支持两种模式：（1）单一分析——对仓库进行完整的STRIDE-A威胁模型分析，生成架构概览、DFD图、STRIDE-A分析、优先级发现结果和管理层评估。（2）增量分析——以之前的威胁模型报告为基线，比较最新（或指定提交）的代码库，并生成带有变更跟踪（新增、已解决、仍存在的威胁）、STRIDE热图、发现差异和嵌入式HTML比较的更新报告。仅在用户明确请求威胁模型分析、增量更新或直接调用/threat-model-analyst时激活。
github