Total 50,502 skills, AI & Machine Learning has 8478 skills
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Reference: review of an inbound vendor agreement against the team playbook in `~/.claude/plugins/config/claude-for-legal/commercial-legal/CLAUDE.md`. Flags deviations, assesses risk, generates specific redline language, and routes to the right approver. Loaded by /commercial-legal:review when a vendor MSA, services agreement, or similar is detected.
This skill should be used when the user asks to "create an agent", "make an agent", "write an agent", "build a subagent", "add an agent to a plugin", "design an autonomous agent", "generate an agent file", "write a system prompt for an agent", "what frontmatter does an agent need", "create a specialized agent". Not for skills or commands — use create-skill.
This skill should be used when the user says "interview me about", "help me clarify", "stress-test my idea", "let's explore this concept", "challenge my assumptions about", "grill me on", "drill into my plan", or needs structured questioning to refine and articulate their thinking.
Turn papers, technical articles, or knowledge content into highly realistic AIGC slides. First create a narrative structure and page-by-page visual direction, then call an image generation model to produce a 16:9 slide image for each page, and finally synthesize into PPTX/PDF. Suitable for paper presentations, group meetings, open courses, technical sharing, and commercial research presentations; use this skill when users mention "paper PPT", "AI-generated PPT", "PPT that doesn't look like AI", "high-quality slides", or "page-by-page AI-generated PPT".
Build an operator-level compute template for an LLM and estimate FLOPs/MFU for a serving shape. Use when you need tensor shapes, per-op FLOPs, kernel-to-op MFU mapping, or parallelism what-if analysis.
For use when students **have completed WG-12 to WG-21** (single-file consolidation blueprint) and are working on **WG-22 Code Splitting** (`agent_core.py` + `main.py`). **First message in a new session**: Display PEAS brand screen and confirm readiness first; after confirmation, **lay out the context** before proceeding to requirement clarification. If **`prompts/` or `templates/`** are missing, copy them from `references/project_assets/` to the project root. Process: Spec Alignment (2d′) → Six-column Contract → **In-session Handoff Implementation** → Acceptance. Starting point: starter_main_wg21.py; Standard reference: reference_agent_core.py + reference_main.py. Triggers: peas-workshop-advanced-coach, PEAS workshop advanced coach, WG-22, code splitting coach, Agent.chat.
Generate per-asset visual specifications and AI generation prompts from GDDs, level docs, or character profiles. Produces structured spec files and updates the master asset manifest. Run after art bible and GDD/level design are approved, before production begins.
Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/set via the SDK or REST API, tuning the similarity threshold, separating caches per task type, and filtering with custom attributes. Use when caching LLM completions or RAG answers to cut API cost and latency, building a cache-aside layer in front of OpenAI / Anthropic / etc., tuning hit rate vs precision, or splitting one app's LLM workloads into multiple LangCache caches.
Redis vector search guidance covering HNSW vs FLAT algorithm choice, vector index configuration (dims, distance metric, datatype), filtered hybrid search combining vector similarity with TAG or NUMERIC filters, and the RAG retrieval pattern with RedisVL. Use when defining a VECTOR field in FT.CREATE, integrating embeddings (OpenAI, Cohere, sentence-transformers), tuning HNSW parameters (M, EF_CONSTRUCTION, EF_RUNTIME), building a retrieval-augmented generation pipeline, or filtering vector results by attribute.
Automate content creation from research to video generation using Claude/OpenAI and Remotion
Manages Dify via bundled CLI: pull/export DSL, patch working.yml, deploy, cache remote files, upload to Dify, run/chat workflows. Use when the user mentions Dify, workflow DSL, pull, deploy, dify-manage, or Dify file inputs.
Deploy a 24/7 Claude Code agent with persistent Chromium browser on any Ubuntu VPS, controllable via Telegram