「capa」の検索結果

Search, scrape, and interact with the web via the Firecrawl CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, scrape a webpage, grab content from a URL, get data from a website, crawl documentation, download a site, or interact with pages that need clicks or logins. Also use when they say "fetch this page", "pull the content from", "get the page at https://", or reference external websites. This provides real-time web search with full page content and interact capabilities — beyond what Claude can do natively with built-in tools. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.

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Survey the whole tdmcp project and produce a prioritized list of NEW features it could implement — across artist controls, CLI/DX, AI/LLM integration, and TouchDesigner depth. Use whenever the user wants to brainstorm, discover, survey, list, or audit what features/tools/effects/controls/commands/prompts/capabilities tdmcp *could* add, asks 'what could we build / what's missing / what are the opportunities / ideas for the project', or wants a feature backlog or gap analysis. Also for follow-ups: re-run, refresh, update, re-survey, deepen, or re-prioritize the backlog, or survey just one surface (e.g. 'CLI ideas only'). This is the IDEATION harness — it produces a list to decide from; it does NOT build. When the user has already chosen a feature and wants it implemented/shipped/added, use tdmcp-pipeline instead.

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Expert capability for robust, stealthy, and efficient browser automation using Playwright Go.

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Use when checking capabilities or instructing the user on how to interact with specialized MCP servers like Unreal, Rhino, DaVinci, or TouchDesigner.

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The Gemini API provides access to Google's most advanced AI models. Key capabilities include:

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Set up bundle IDs, capabilities, signing certificates, provisioning profiles, and encrypted signing sync with the asc cli. Use when onboarding a new app, rotating signing assets, or sharing them across a team.

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Integrate Apple Pay payments and Wallet passes using PassKit. Use when adding Apple Pay buttons, creating payment requests, handling payment authorization, adding passes to Wallet, configuring merchant capabilities, managing shipping and contact fields, or working with PKPaymentRequest, PKPaymentAuthorizationController, PKPaymentButton, PKPass, PKAddPassesViewController, PKPassLibrary, or Apple Pay checkout flows.

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Build iOS App Clips with invocation URLs, NFC, QR codes, App Clip Codes, Safari banners, Maps, Messages, and shared App Group data handoff to the full app. Covers target setup, experience configuration, size limits, NSUserActivity handling, SKOverlay promotion, location confirmation, and capability limits. Use when creating App Clips or wiring App Clip invocation and full-app migration.

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Support audio accessory features like automatic switching using AudioAccessoryKit. Use when implementing automatic audio routing for connected accessories, managing audio accessory sessions, registering device capabilities and placement, providing connected audio source identifiers, or configuring audio accessories connected to iOS devices.

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Provide universal memory capabilities for different AI agents and development frameworks, unifying the capture, retrieval, and management of user, project, and task context.

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Use when: 'intake this repo/skill', 'evaluate external skill', 'should we adopt X', a candidate repo URL plus an adoption question, or any external skill/workflow/tool surfaces as a possible fit for Agistra. Structured front-door evaluation of external skills, workflows, and similar capability artifacts before any install, promotion, or adaptation decision. Ends in exactly one classification: Install candidate, Adapt concept, or Reject. Never install first — intake first.

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Use when: the agent captures a correction from the team lead, hits an unexpected error, discovers a capability gap, or finds a better practice. Logs to .learnings/ and promotes durable patterns to permanent project memory.

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Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.

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Guide for creating effective 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, or tool integrations.

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Web search, content extraction, crawling, and research capabilities using Tavily API

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Guide for creating effective 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, or tool integrations.

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Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

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Use when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models ("blockrun", "use grok", "use gpt", "dall-e", "deepseek")

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Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b

日本語の概要は準備中です。原文の説明を表示しています。

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

日本語の概要は準備中です。原文の説明を表示しています。

Build search applications with vector, hybrid, and semantic search capabilities.

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Azure Fabric Management SDK for Python. Use for managing Microsoft Fabric capacities and resources.

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Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.

日本語の概要は準備中です。原文の説明を表示しています。

tespit etme (s) container escape attempts by analyzing namespace configurations, privileged container checks, dangerous capability assignments, and host path mounts using the kubernetes Python client. Identifies CVE-2022-0492 style escapes via cgroup abuse. Use auditing yaparken container security posture or investigating escape attempts.

日本語の概要は準備中です。原文の説明を表示しています。