Total 51,037 skills, AI & Machine Learning has 8547 skills
Showing 12 of 8547 skills
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.
Use when challenging ideas, plans, decisions, or proposals using structured critical reasoning. Invoke to play devil's advocate, run a pre-mortem, red team, or audit evidence and assumptions.
Triages GitHub issues by routing to oncall teams, applying labels, and closing questions. Use when processing new PyTorch issues or when asked to triage an issue.
Use this skill to analyze competitors, find competitive gaps, and develop competitive strategy. Triggers: "competitor analysis", "competitive analysis", "analyze competitor", "competitive intel", "competitive intelligence", "competitive landscape", "competitor comparison", "beat competitor", "competitor weakness", "competitive advantage", "competitor research" Outputs: Competitive matrix, gap analysis, differentiation strategy, battlecards.
AI content generation with OpenAI and Claude, callAIWithPrompt usage, prompt storage in app_settings, structured outputs, response format validation, multi-criteria scoring, rate limiting, JSON schema, and AI API best practices. Use when generating content, creating prompts, scoring articles, or working with OpenAI/Claude APIs.
Evaluate, score (ASQM strict), tag, and normalize all Skills; writes agent.yaml and README per skill, detects overlaps, produces ASQM_AUDIT.md or chat summary. Use when auditing skills, after adding/changing skills, or when generating repo-level skill summaries.
Persistent shared memory for AI agents backed by PostgreSQL (fts + pg_trgm, optional pgvector). Includes compaction logging and maintenance scripts.
Integrate PICA into an application using the OpenAI Agents SDK. Use when adding PICA tools to an OpenAI agent via @openai/agents, setting up PICA MCP with the OpenAI Agents SDK, or when the user mentions PICA with OpenAI Agents.
Write comprehensive literature reviews for medical imaging AI research. Use when writing survey papers, systematic reviews, or literature analyses on topics like segmentation, detection, classification in CT, MRI, X-ray, ultrasound, or pathology imaging. Triggers on requests for "review paper", "survey", "literature review", "综述", "systematic review", or mentions of writing academic reviews on deep learning for medical imaging.
Creates and reviews CLAUDE.md configuration files for Claude Code. Applies HumanLayer guidelines including instruction budgets (~50 user-level, ~100 project-level), WHAT/WHY/HOW framework, and progressive disclosure. Identifies anti-patterns like using Claude as a linter for style rules.
Generate videos using TensorsLab's AI video generation models. Supports text-to-video and image-to-video generation with automatic prompt enhancement, progress tracking, and local file saving. Use for generating videos from text descriptions, animating static images, creating cinematic content, and various aspect ratios. Requires TENSORSLAB_API_KEY environment variable. Video generation takes several minutes.
Creates or updates professional-grade agent skills (SKILL.md + optional scripts/references/assets) with strict validation and an iterative generator↔critic workflow. Use when: you want a new skill, want to refactor an existing skill for clarity/token-efficiency, or want to reach an A-grade rubric score.