Total 50,817 skills, AI & Machine Learning has 8500 skills
Showing 12 of 8500 skills
A validation framework that ensures Claude's responses are current, accurate, complete, and clear. Use this skill whenever the user asks a factual or research question, requests analysis or recommendations (e.g., "What's the best framework for X?", "Compare options for Y"), or any prompt where recency and accuracy matter. Also trigger when the user explicitly asks for validated, verified, or fact-checked answers. This skill should activate broadly — if the answer depends on facts that could have changed in the last few months, use it. Even questions that seem straightforward ("Is X still the recommended approach?") benefit from this skill's validation pipeline. Do NOT trigger for purely creative writing, casual chat, or tasks that are entirely opinion-based with no factual claims.
Parent skill. Focuses on researching personal judgment, methodology, system capability and brand equity building in the AI era. Responsible for overall positioning control and task distribution.
Guide la création d'un nouveau skill d'agent IA pour le dépôt foundation-skills. Génère le squelette du SKILL.md et du fichier docs, applique les conventions du dépôt (frontmatter, versionnage, structure). À utiliser quand l'utilisateur demande de créer un nouveau skill, écrire un skill, ajouter un skill ou générer le squelette d'un skill.
STUB — installed at ~/openclaw/skills/coding-agent/SKILL.md
Analyze videos, screen recordings, and screenshots to generate structured, actionable notes for coding agents. Supports Loom, YouTube, and local files. Extracts visual context, on-screen text, and audio narration. Use when someone shares a video and you need to understand what it shows.
Overview The VC Attention Agent allows users to extract followings of top crypto VCs, including lists from Dragonfly, Paradigm, a16z, and more, to bypass manual mapping and identify where institutiona
Cross-chain token swap agent powered by LayerZero's Value Transfer API. Supports swapping tokens across EVM chains including Ethereum, Arbitrum, Optimism, Base, Polygon, Avalanche, and more. Handles m
Automatic Speech Recognition (ASR). Uses Volcano Engine BigModel ASR for speech recognition, with two available modes: Express Edition (≤2h/100MB, synchronous fast response) and Standard Edition (≤5h, asynchronous recognition). It supports Feishu voice messages, local audio files and audio URLs. Use this skill when you receive voice messages or audio attachments (.ogg/.mp3/.wav).
Use when an approved current phase has 3 or more independent ready tasks and parallel execution will materially reduce cycle time. Orchestrates bounded workers, monitors blockers and file conflicts, coordinates rescues, and hands off to planning or reviewing when the current execution scope is complete. Use for prompts about swarming, parallel workers, launching multiple agents, coordinating a worker pool, or running approved current-phase work at scale.
Generates a Jupyter notebook that evaluates a fine-tuned SageMaker model using LLM-as-a-Judge. Use when the user says "evaluate my model", "how did my model perform", "compare models", or after a training job completes. Supports built-in and custom evaluation metrics, evaluation dataset setup, and judge model selection.
Use when the system needs to track its own effectiveness, learn from errors, adapt workflows, and continuously improve performance - activates automatically every session to collect metrics, classify errors, recognize patterns, and implement evidence-based workflow improvements
Use when the user needs prompt design, optimization, few-shot examples, chain-of-thought patterns, structured output, evaluation metrics, or prompt versioning. Triggers: new prompt creation, prompt optimization, few-shot example design, structured output specification, A/B testing prompts, evaluation framework setup.