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Found 1,622 Skills
Unified LLM torch-profiler triage skill for `sglang`, `vllm`, and `TensorRT-LLM`. Use it to inspect an existing `trace.json(.gz)` or profile directory, or to drive live profiling against a running server and return one three-table report with kernel, overlap-opportunity, and fuse-pattern tables.
Automates the Karpathy LLM Wiki workflow: turns web, GitHub, and YouTube URLs into well-structured, citable, wikilinked pages with automatic linting and sourcing — invoke with /pin-llm-wiki
Manage LLMem — structured memory system with SQLite-backed factual memory, semantic search, and background dreaming (decay, boost, promote, merge). Use when the user wants to: (1) add, search, update, or delete memories, (2) generate context for injection, (3) check memory stats, (4) run background consolidation/dream. Triggers on: "memory", "remember", "recall", "llmem", "memories", "forget", "consolidate memories", "dream".
Chinese public opinion analytics platform integrating 26 trending lists from 15 platforms with LLM-powered sentiment analysis, topic clustering, and multi-channel alert push
Build autonomous self-evolving AI agents with vision-grounded memory that operate computers through a perceive-reason-act cycle
Root cause analysis on production LLM traces. Diagnoses why an LLM application is failing — works from eval judge verdicts, runtime errors, or structural anomalies depending on what signals are present. Walks the span tree from symptom to root cause. Use when user says "what's wrong with my app", "why is my eval failing", "analyze errors", "root cause analysis", "diagnose failures", or wants to understand production failure patterns.
Calculate agreement between human ground truth and machine labels for a text LLM judge metric, then analyze transcripts and reviewer notes to propose an improved metric prompt. One metric at a time.
Fulfillment setup — Fulfilled by TikTok, self-fulfillment, shipping templates, return policies
Multi-platform public opinion analysis assistant with web scraping, LLM-powered analytics, topic clustering, sentiment analysis, and multi-channel alerts
Build LLM-powered chat apps with the right SDK — Anthropic SDK / Claude API (prompt caching, thinking, tool use, batch, files, citations, memory, model migrations) AND Vercel AI SDK (useChat, streamText, tool calls, UIMessage, ChatStatus, addToolOutput). Use when implementing chat interfaces, tuning Claude features, migrating between Claude model versions, or wiring up streaming with @ai-sdk/react.
Use when building an LLM-powered app that needs cost control via model routing, budget tracking, retry, and prompt caching.
Configure a Mac mini as a reliable local LLM server with remote access, observability, and power-safe operation.