Total 50,316 skills, AI & Machine Learning has 8453 skills
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Generate interactive AI transformation context-builder prompts for consulting clients. Use when creating structured discovery session prompts that guide a company through context gathering about their business, pain points, tech stack, and AI opportunities. Produces a resumable, multi-section prompt with Express/Deep Dive modes.
Constructive, evidence-based dialogue mode that avoids sycophancy. This skill should be used when the user wants balanced multi-perspective analysis, critical feedback, or rigorous challenge of their ideas. Triggers on "/balanced" or requests for honest/critical/balanced feedback. Supports passive, interactive, tldr, steelman, and decision modes.
Generate audio using the Runway API via runnable scripts. Supports TTS, sound effects, voice isolation, dubbing, and voice conversion.
Run an autonomous /loop iteration -- check progress, work on next task, schedule next wake
Query AgentDB with semantic routing, hierarchical recall, causal graphs, and context synthesis
Investigate LLM analytics evaluations of both types — `hog` (deterministic code-based) and `llm_judge` (LLM-prompt-based). Find existing evaluations, inspect their configuration, run them against specific generations, query individual pass/fail results, and generate AI-powered summaries of patterns across many runs. Use when the user asks to debug why an evaluation is failing, surface common failure modes, compare results across filters, dry-run a Hog evaluator, prototype a new LLM-judge prompt, or manage the evaluation lifecycle (create, update, enable/disable, delete).
Set up an LLM-judge evaluation that extracts canonical use cases for a PostHog feature at scale and streams the results to a Slack channel as a live feed. Use when someone wants to understand how users are actually using a specific AI/LLM-powered feature in production — what they're investigating, what questions they're trying to answer, and what patterns surface — without manually reading hundreds of traces. Assumes the feature emits `$ai_generation` and `$ai_evaluation` events with `$session_id` linkage to the trigger user's recording (the standard setup post the session-summary linkage PRs).
This is a properly formatted skill.
Format prompts for different LLM providers with chat templates and HNSW-powered context retrieval
Analyze a Karpathy-pattern LLM wiki knowledge base and generate an interactive knowledge graph with entity extraction, implicit relationships, and topic clustering.
Deep-dive Amazon review analysis. Extract sentiment patterns, recurring complaints, feature requests, and competitive insights from product reviews. Turn customer feedback into product improvement and marketing opportunities.
Neuroscience research and reasoning workflows using ToolUniverse tools. Covers computational neuroscience (rate models, integrate-and-fire neurons, synaptic plasticity, network dynamics), neuroanatomy (cortical regions, basal ganglia, cerebellum, brainstem, model organism connectomes), neurophysiology (ion channels, action potentials, synaptic transmission), neural circuits (E/I balance, oscillations, central pattern generators), synaptic dynamics (STDP, short-term plasticity, neuromodulation), neurodegenerative diseases (Alzheimer's, Parkinson's, ALS, Huntington's), and clinical neurology (cranial nerves, stroke localization, neuromuscular disorders). Use when researchers ask about brain regions, neural computation, firing rates, synaptic plasticity, connectomics, neurodegeneration, or clinical neurological questions.