「cap」の検索結果

Use when legacy prompts or older framework flows reference `code-review-expert` and you need the modern runtime to resolve that capability cleanly.

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。

Use when legacy prompts or older framework flows reference `code-reviewer` and you need the modern runtime to resolve that capability cleanly.

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。

Use when legacy prompts or older framework flows reference `architect` and you need the modern runtime to resolve that capability cleanly.

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。

Executes comprehensive red team exercises that simulate real-world adversary operations against an organization's people, processes, and technology. The red team operates with stealth as a primary objective, employing the full attack lifecycle from initial reconnaissance through objective completion while testing the organization's detection and response capabilities. This differs from penetration testing by focusing on adversary emulation rather than vulnerability identification. Activates for requests involving red team exercise, adversary simulation, adversary emulation, or full-scope offensive security assessment.

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。

Use when legacy prompts or older framework flows reference `cyber-intel` and you need the modern runtime to resolve that capability cleanly.

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。

Use when important product, technical, or founder decisions need to be captured as durable context with rationale, tradeoffs, and follow-up implications.

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。

Use when legacy prompts or older framework flows reference `devops-engineer` and you need the modern runtime to resolve that capability cleanly.

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。

Use when legacy prompts or older framework flows reference `dispatching-parallel-agents` and you need the modern runtime to resolve that capability cleanly.

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。

Use when legacy prompts or older framework flows reference `e2e-runner` and you need the modern runtime to resolve that capability cleanly.

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。

Builds a personal voice profile so Cowork writes the way you write — not like a generic AI. Use when personalizing your writing style, for capturing your communication patterns and tone, during setup after getting generic-sounding output, when training Cowork to match your voice, or when the user says "teach claude my voice", "my writing style", "output doesn't sound like me", "brand voice", "personalize output", "make it sound like me", "it sounds too formal", "it sounds too robotic", "can cowork match my tone", or "how do I get cowork to write like me".

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。

See the difference between Chat and Cowork with a live side-by-side comparison for understanding why Cowork is built differently. Use when evaluating AI tools, for comparing chat versus agent capabilities, during an AI tool decision, when switching from ChatGPT or Claude Chat, or when the user says "what is different about cowork", "cowork vs chat", "why not just use chatgpt", "show me the difference", "compare chat and cowork", or "why should I use cowork instead of chat".

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。

Architect escalation approval — extend iteration limit for a phase that has hit its cap. Records the approval decision in state and allows the blocked transition to proceed.

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。

Run an end-to-end GEO visibility measurement through a real AI interface, persist the captures, and return a portable JSON run artifact plus optional PDF/dashboard outputs. Use automatically on an explicit request to measure a brand's AI-search visibility, and as a composable data-collection step inside another agent workflow; the user should not have to launch the pipeline or dashboard manually.

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。

Use when the user asks to write a threat / risk / vulnerability assessment, or wants the appropriate template for each type. Distinct structures and section ordering per assessment kind. Prefers graded evidence items from /quality-of-information-check and runs that skill first when handed raw URLs or text. Confidence is capped by the weakest load-bearing claim, and at Moderate when the evidence is ungraded.

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。

Peer review checklist and quality standards for intelligence products, plus schema validation for graded evidence items and claim tables from /quality-of-information-check and /claim-extraction. Rejects outputs that break the evidence schema or the grading caps. Loaded by the quality-reviewer 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。

Analysis of Competing Hypotheses — structured technique for evaluating multiple explanations against evidence. Use when facing ambiguous attribution or multiple plausible scenarios. Prefers graded evidence items from /quality-of-information-check and runs that skill first when handed raw URLs or text. Runs on ungraded evidence when asked, labelled as such, unweighted, and capped at Moderate confidence.

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。

Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background 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 Shopify applications, extensions, and themes using GraphQL/REST APIs, Shopify CLI, Polaris UI components, and Liquid templating. Capabilities include app development with OAuth authentication, checkout UI extensions for customizing checkout flow, admin UI extensions for dashboard integration, POS extensions for retail, theme development with Liquid, webhook management, billing API integration, product/order/customer management. Use when building Shopify apps, implementing checkout customizations, creating admin interfaces, developing themes, integrating payment processing, managing store data via APIs, or extending Shopify functionality.

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。

Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.

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。

Create aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.

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。

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。

Comprehensive framework for effective gptme agent onboarding that builds user trust, communicates capabilities clearly, and establishes productive working relationships from the first interaction.

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。

Implementation guidance for creating individual agents in the Arcanea system with proper structure, capabilities, and integration.

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。

This skill should be used when the user asks to "create an agent", "write a subagent", "generate agent definition", "add agent to plugin", "write agent frontmatter", "create autonomous agent", "build subagent", needs agent structure guidance, YAML frontmatter configuration, invocation criteria with examples, or wants to add specialized subagents to Claude Code plugins with proper capabilities lists and tool access definitions.

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。