Total 31,175 skills, AI & Machine Learning has 5045 skills
Showing 12 of 5045 skills
Task management for session continuity. Use when coordinating multi-step work, managing subagent assignments, or preserving intent across compaction. Triggers on "track tasks", "manage work", "coordinate agents", or when complex work requires sequencing.
Use when discussing or working with DeepEval (the python AI evaluation framework)
Guide for creating custom skills in SaaS Factory. Use when you need to create a new skill to extend Claude's capabilities with specialized knowledge, workflows, or tools.
This skill generates interactive multiple-choice quizzes for each chapter of an intelligent textbook, with questions aligned to specific concepts from the learning graph and distributed across Bloom's Taxonomy cognitive levels to assess student understanding effectively. Use this skill after chapter content has been written and the learning graph exists.
Edits an existing image using a text prompt. Use when you need to modify, enhance, or transform an image based on text instructions.
Use when implementing on-device AI with Apple's Foundation Models framework (iOS 26+), building summarization/extraction/classification features, or using @Generable for type-safe structured output.
Use this skill to implement hybrid search combining BM25 keyword search with semantic vector search using Reciprocal Rank Fusion (RRF). **Trigger when user asks to:** - Combine keyword and semantic search - Implement hybrid search or multi-modal retrieval - Use BM25/pg_textsearch with pgvector together - Implement RRF (Reciprocal Rank Fusion) for search - Build search that handles both exact terms and meaning **Keywords:** hybrid search, BM25, pg_textsearch, RRF, reciprocal rank fusion, keyword search, full-text search, reranking, cross-encoder Covers: pg_textsearch BM25 index setup, parallel query patterns, client-side RRF fusion (Python/TypeScript), weighting strategies, and optional ML reranking.
Validates agent skill definitions against agentskills.io and AGENTS.md rules. Use when creating or modifying skills to ensure they are machine-readable and documentation-complete.
All-atom protein design using BoltzGen diffusion model. Use this skill when: (1) Need side-chain aware design from the start, (2) Designing around small molecules or ligands, (3) Want all-atom diffusion (not just backbone), (4) Require precise binding geometries, (5) Using YAML-based configuration. For backbone-only generation, use rfdiffusion. For sequence-only design, use proteinmpnn. For structure validation, use boltz.
Structure prediction using Boltz-1/Boltz-2, an open biomolecular structure predictor. Use this skill when: (1) Predicting protein complex structures, (2) Validating designed binders, (3) Need open-source alternative to AF2, (4) Predicting protein-ligand complexes, (5) Using local GPU resources. For QC thresholds, use protein-qc. For AlphaFold2 prediction, use alphafold. For Chai prediction, use chai.
Expert in designing and implementing intelligent game AI systems including behavior trees, finite state machines, GOAP, utility AI, pathfinding, steering behaviors, and perception systems. Specializes in creating believable, performant NPC behaviors that enhance player experience. Use when "game AI, NPC behavior, behavior tree, state machine for game, enemy AI, pathfinding, A* algorithm, navmesh, steering behavior, GOAP, utility AI, AI perception, combat AI, companion AI, boss AI, crowd simulation, flocking, game-ai, behavior-trees, pathfinding, npc, state-machines, goap, utility-ai, steering, perception" mentioned.
Ligand-aware protein sequence design using LigandMPNN. Use this skill when: (1) Designing sequences around small molecules, (2) Enzyme active site design, (3) Ligand binding pocket optimization, (4) Metal coordination site design, (5) Cofactor binding proteins. For standard protein design, use proteinmpnn. For solubility optimization, use solublempnn.