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All Skills

Total 56,829 skills, AI & Machine Learning has 9448 skills

Categories

Showing 12 of 9448 skills

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AI & Machine Learningyouaifuou/karl-marx-skill

karl-marx

Karl Marx's thinking framework and critical methodology. Epistemological principles, decision heuristics, rhetorical devices and polemic engines are extracted from 17 core works, to analyze social phenomena, economic issues and political events from Marx's perspective. Trigger WHEN: "from Marx's perspective", "what would Marx think", "Marx mode", "historical materialism analysis", "help me analyze from Marx's angle", "switch to Marx".

🇨🇳|ChineseTranslated
17
AI & Machine Learninggyanesh-m/skills

galileo-typescript-sdk

Complete reference for the Galileo AI platform TypeScript/JS SDK for evaluating, observing, and protecting GenAI applications. Use when building Node.js or TypeScript applications that need LLM evaluation, production observability, tracing, or runtime guardrails with Galileo.

🇺🇸|EnglishTranslated
17
AI & Machine Learninggyanesh-m/skills

galileo-python-sdk

Complete reference for the Galileo AI platform Python SDK for evaluating, observing, and protecting GenAI applications. Use when building Python applications that need LLM evaluation, production observability, tracing, or runtime guardrails with Galileo.

🇺🇸|EnglishTranslated
17
AI & Machine Learningbobmatnyc/claude-mpm-skil...

vector-search-workflows

Vector search indexing and querying workflows using MCP Vector Search, including setup, reindexing, auto-index strategies, and MCP integration.

🇺🇸|EnglishTranslated
17
AI & Machine Learningnanzhipro/karpathy-llm-wi...

llm-wiki-bootstrap

Scaffolds a personal LLM Wiki from scratch — the Karpathy pattern of incrementally building a persistent, interlinked markdown knowledge base maintained by LLMs. Generates directory structure, schema file, index, log, and workflow conventions. Use when user says "create wiki", "new wiki", "bootstrap wiki", "llm wiki", "knowledge base", "start a wiki", "build a wiki", or wants to set up a structured markdown knowledge base for any domain.

🇺🇸|EnglishTranslated
17
AI & Machine Learningpippit-dev/pippit-skills

xyq-nest-skill

Comprehensive creation via Xiaoyunque's AI capabilities, supporting generation and editing of images/videos. Covered scenarios include: Generation (text-to-image, text-to-video, image-to-video, animation creation, draw xxx, create xxx clip), Editing & Revision (replace xxx with yyy, remove xxx, add xxx, change to xxx, adjust xxx, local modification, lens adjustment), Style Transfer (style migration, repainting, style change), video continuation, video/TVC/promotional video replication, short drama/short comic drama generation, music MV creation, product advertisement/demo video production, storyboard design, educational video/short video production. This skill should also be triggered when users mention Xiaoyunque, xyq, uploading reference images/videos, or checking generation progress. Key Judgment: This skill must be triggered whenever the user's request involves AI video creation, generation, editing, or revision, regardless of the wording (e.g., "draw a cat", "make a poster", "create a video", "help me revise this video", "help me replicate this video", "make an MV with this song", "generate a short drama with one sentence")

🇨🇳|ChineseTranslated
17
5 scripts/Checked
AI & Machine Learninggear-foundation/vara-skil...

vara-skills

Standard Gear/Vara Sails builder pack for AI agents. Use when building or extending a Sails app on Vara or Gear. NOT for Vara.eth, ethexe, non-Sails programs, or generic protocol research.

🇺🇸|EnglishTranslated
17
AI & Machine Learningflora131/atomic

memory-systems

Guides implementation of agent memory systems, compares production frameworks (Mem0, Zep/Graphiti, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention. Use when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph for agents", "track entities over time", "add long-term memory", "choose a memory framework", or mentions temporal knowledge graphs, vector stores, entity memory, adaptive memory, dynamic memory, or memory benchmarks (LoCoMo, LongMemEval). A core context engineering skill — also activates when the user mentions "context engineering" or "context-engineering" in the context of durable agent knowledge and cross-session persistence.

🇺🇸|EnglishTranslated
17
1 scripts/Checked
AI & Machine Learningasgard-ai-platform/skills

algo-ad-ctr

Build CTR prediction models for estimating ad click-through rates from features. Use this skill when the user needs to predict click probability, build an ad ranking model, or evaluate ad creative performance — even if they say 'predict click rate', 'ad relevance scoring', or 'which ad will get more clicks'.

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17
AI & Machine Learningascend/agent-skills

npu-smi

Huawei Ascend NPU npu-smi command reference. Use for device queries (health, temperature, power, memory, processes, ECC), configuration (thresholds, modes, fan), firmware upgrades (MCU, bootloader, VRD), virtualization (vNPU), and certificate management.

🇺🇸|EnglishTranslated
17
1 scripts/Attention
AI & Machine Learningascend/agent-skills

cann-operator-env-config

Provides installation guidance for CANN on Ascend NPU. Call this skill when users need to install CANN, configure the Ascend environment, or resolve installation issues.

🇨🇳|ChineseTranslated
17
AI & Machine Learningascend/agent-skills

ascend-profiling-anomaly

Analyze Huawei Ascend NPU profiling data to discover hidden performance anomalies and produce a detailed model architecture report reverse-engineered from profiling. Trigger on Ascend profiling traces, NPU bottlenecks, device idle gaps, host-device issues, kernel_details.csv / trace_view.json / op_summary / communication.json. Also trigger on "profiling", "step time", "device bubble", "underfeed", "host bound", "device bound", "AICPU", "wait anchor", "kernel gap", "Ascend performance", "model architecture", "layer structure", "forward pass", "model structure". Runs anomaly discovery (bubble detection, wait-anchor, AICPU exposure) alongside model architecture analysis (layer classification, per-layer sub-structure, communication pipeline). Outputs a separate Markdown architecture report alongside anomaly analysis.

🇺🇸|EnglishTranslated
17
1 scripts/Checked
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