Total 54,366 skills, AI & Machine Learning has 9029 skills
Showing 12 of 9029 skills
Extract and document someone's authentic writing voice from samples. Use when someone needs a "voice guide," wants to capture their writing DNA, or needs to train AI to write in their style. Also useful for ghostwriting, brand voice documentation, or onboarding writers.
Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.
Audit installed skills across project, global, and plugin levels. Lists skills with line counts, identifies improvement opportunities (conciseness, clarity, overlap, token waste). Use when reviewing skill quality, finding bloated skills, or optimizing token budgets.
Working memory management, context prioritization, and knowledge retention patterns for AI agents. Use when you need to maintain relevant context and avoid information loss during long tasks.
Expert guidance for working with Hugging Face Transformers library for NLP, computer vision, and multimodal AI tasks.
This skill should be used when the user asks to "track issues", "create beads issue", "show blockers", "what's ready to work on", "beads routing", "prefix routing", "cross-rig beads", "BEADS_DIR", "two-level beads", "town vs rig beads", "slingable beads", or needs guidance on git-based issue tracking with the bd CLI.
Create, deploy, and interact with agents on TerminalUse. Use when user mentions "tu", "terminaluse", "deploy agent", "create agent", "agent task", "filesystem", or wants to build/test/run an agent.
Automated reproduction of comprehensive model evaluation benchmarks following the Benchmark Suite V3. Auto-activates for model benchmarking, comparison evaluation, or performance testing between AI models.
Use when compressing agent context, implementing conversation summarization, reducing token usage in long sessions, or asking about "context compression", "conversation history", "token optimization", "context limits", "summarization strategies"
Use when "SHAP", "Shapley values", "feature importance", "model explainability", or asking about "explain predictions", "interpretable ML", "feature attribution", "waterfall plot", "beeswarm plot", "model debugging"
LLM의 본질(확률적 토큰 예측), hallucination의 구조적 원인, temperature의 의미를 학습시키는 모듈.
Guide for creating effective skills, adding skill references, skill scripts or optimizing existing skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, frameworks, libraries or plugins usage, or API and tool integrations.