Automate web scraping and data extraction with Apify -- run Actors, manage datasets, create reusable tasks, and retrieve crawl results through the Composio Apify 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。
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概要と使いどころ
Automate web scraping and data extraction with Apify -- run Actors, manage datasets, create reusable tasks, and retrieve crawl results through the Composio Apify 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。
Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.
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 designing, reviewing, refactoring, or enforcing Angular application architecture with isolated lazy features, eager core/layout, reusable ui/pattern architecture building blocks, one-way dependency graphs, eslint-plugin-boundaries rules, or folder placement decisions. This skill takes precedence over angular-developer when architecture rules conflict with general Angular advice.
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。
Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications. Use when implementing complex type logic, creating reusable type utilities, or ensuring compile-time type safety in TypeScript projects.
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。
Learns a user's personal writing and speaking style through interactive writing prompts, then generates a reusable voice profile. Use when the user says "learn my writing style," "write like me," "capture my voice," "voice calibration," "mimic my tone," "my writing style," or wants AI to match their personal communication style. Also activates when a .voice-profile.md file exists and the user asks you to write something in their voice.
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Save durable decisions, findings, plans, and implementation knowledge from the visible Codex conversation into a new or existing NeatContext context. Use only when the user explicitly invokes this skill or asks to preserve the current conversation as reusable context.
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Save durable decisions, findings, plans, and implementation knowledge from the visible pi conversation into a new or existing NeatContext context. Use only when the user explicitly asks to preserve the current conversation as reusable context, or runs /neatcontext-save.
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。
Save durable decisions, findings, plans, and implementation knowledge from the visible Kimi Code conversation into a new or existing NeatContext context. Use only when the user explicitly invokes this skill or asks to preserve the current conversation as reusable context.
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 or maintain a source-grounded kpopper knowledge model as a versioned plugin. Use when a reusable domain model should ship independently of any one project.
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Frontend UI design, critique, audit, polish. Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
Extract and consolidate reusable components, design tokens, and patterns into your design system. Identifies opportunities for systematic reuse and enriches your component library. Use when the user asks to create components, refactor repeated UI patterns, build a design system, or extract tokens.
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。
React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.
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Sync reusable frontend decisions into persistent project documentation after UI work. Use when frontend changes introduce or modify component APIs, variants, design-system tokens, styling conventions, layout behavior, accessibility rules, interaction patterns, responsive behavior, or agent operating instructions; when the user asks to reflect decisions in components.md, design system docs, AGENTS.md, CLAUDE.md, GEMINI.md, or similar project memory files; or before finalizing frontend work where future consistency depends on decisions made during implementation.
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Use when creating or rewriting a README for a reusable package or library. Focus on installability, minimal usage example, compatibility, and developer onboarding.
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When working with GitHub Actions — workflow YAML, quality gates, test matrices, deployment triggers, reusable workflows — even when the user just says 'my CI is failing' or 'add a check'.
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Use BEFORE writing or editing any non-trivial UI — inventories components, design tokens, shadcn primitives, and reusable patterns into state.ui_audit. Hard gate for fe-design.
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[Architecture] Use when scaffolding reusable OOP/SOLID project foundations before feature implementation.
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[Utilities] Use when the user invokes, lists, saves, updates, or deletes a PROJECT-SPECIFIC saved prompt — a named, reusable procedure stored with the project rather than in the portable framework. `/custom-prompt list` prints every defined prompt with its description; `/custom-prompt <free-text request>` matches the request to the closest saved prompt and executes it only after a confirmation gate; `/custom-prompt save|update|delete ...` maintains the registry — save never stores raw wording, it drafts the best version of the prompt and confirms the name, description, inferred goal, and steps with the user first. Triggers: custom prompt, custom prompts, list custom prompts, save this prompt, save this prompt task, update this prompt, my saved prompt, project prompt, playbook, recipe, runbook.
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Creates a repeatable process for researching and comparing companies. Use when the user wants a structured, reusable company-research workflow with objectives, sources, fields, and validation.
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 wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
Generate reusable multi-step agent workflow blueprints. Use for trigger/action orchestration, deterministic workflow definitions, and automation handoff artifacts.
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 and evolve production-ready skills with reusable scripts, references, and validation. Use for new skill creation, skill upgrades, and enforcing consistent metadata and structure.
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Audit and optimize a skill system with evidence. Use for skill architecture, token or context waste, role and prompt boundaries, routing hits or misfires, plugin packaging, registry/docs/source drift, duplicate workflows, or deciding whether a reusable change belongs in a skill. Runs deterministic checks first and applies only authorized, minimal fixes.
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GStack learn method for capturing reusable lessons, triggers, and future retrieval cues after debugging, implementation, or release work.
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。