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Found 1,665 Skills
Guides development with SAP AI Core and SAP AI Launchpad for enterprise AI/ML workloads on SAP BTP. Use when: deploying generative AI models (GPT, Claude, Gemini, Llama), building orchestration workflows with templating/filtering/grounding, implementing RAG with vector databases, managing ML training pipelines with Argo Workflows, configuring content filtering and data masking for PII protection, using the Generative AI Hub for prompt experimentation, or integrating AI capabilities into SAP applications. Covers service plans (Free/Standard/Extended), model providers (Azure OpenAI, AWS Bedrock, GCP Vertex AI, Mistral, IBM), orchestration modules, embeddings, tool calling, and structured outputs.
Use when syncing skills from local folders, GitHub URLs, or skillsmp.com pages to multiple AI coding tool directories
Use when the user wants to manage Valet agents, channels, connectors, organizations, or secrets via the valet CLI. Handles creation, deployment, linking, teardown, and all multi-step workflows. Also use when asked to "create an agent", "deploy an agent", "design an agent", "build me an agent that...", "create a connector", "set up a webhook", or anything involving the Valet platform or any request to create and deploy AI agents. Also use when asked to "learn from this session", "capture this workflow", "save this as an agent", "make this repeatable", or when writing SOUL.md files.
Create a comprehensive specification from a brief description. Manages specification workflow including directory creation, README tracking, and phase transitions.
This skill should be used when performing AI-powered mutation testing to evaluate and improve unit test quality. It generates targeted code mutants, runs tests to identify surviving mutants, and strengthens or creates tests to kill them. Accepts a file path, directory, or defaults to git diff changed files.
Use this skill for ANY question about creating test or evaluation datasets for LangChain agents. Covers generating datasets from traces (final_response, single_step, trajectory, RAG types), uploading to LangSmith, and managing evaluation data.
Use when user asks to setup endorctl, install endorctl, run endorctl scan, scan for vulnerabilities, run endor scan or run Endor Labs scan or when any endorctl command fails with 'command not found', 'no such file or directory', authentication errors, 'unauthorized', '403', 'tenant not found', EOF error, or namespace/access errors.
Automatic generation system for A-share daily briefings. It crawls real-time data from East Money and generates daily reports covering complete information such as market indices, popular sectors, and capital trends.
Use ONLY when creating NEW registrable components in ML projects that require Factory/Registry patterns. ✅ USE when: - Creating a new Dataset class (needs @register_dataset) - Creating a new Model class (needs @register_model) - Creating a new module directory with __init__.py factory - Initializing a new ML project structure from scratch - Adding new component types (Augmentation, CollateFunction, Metrics) ❌ DO NOT USE when: - Modifying existing functions or methods - Fixing bugs in existing code - Adding helper functions or utilities - Refactoring without adding new registrable components - Simple code changes to a single file - Modifying configuration files - Reading or understanding existing code Key indicator: Does the task require @register_* decorator or Factory pattern? If no, skip this skill.
Use this skill any time the user wants in-depth research or comprehensive analysis on any topic. This includes: industry analysis, competitive landscape mapping, market sizing, trend analysis, technology reviews, investment research, sector overviews, due diligence, benchmark studies, patent landscape analysis, regulatory analysis, and academic surveys. Also trigger when: user says 帮我调研一下, 深度分析, 行业研究, 市场规模分析, 竞争格局, 技术趋势, 做个研究报告. If deep research or comprehensive analysis is needed, use this skill.
This skill should be used when the user requests to "save team", "team save", "save team configuration", or "export team". It reads the configuration from a running team and saves it as a snapshot file to the .team-profiles/ directory for reuse with /team-load.
Run a comprehensive security audit combining automated SAST scanning, STRIDE threat modeling, and attack tree analysis. Use before major releases, after security-sensitive changes, or on a regular cadence. Can audit the full codebase or specific directories.