「intent」の検索結果

Recover source-bound buyer jobs, struggling moments, desired progress, forces, workarounds, information acts, journey states, criteria, constraints, roles, locales, and authentic language. Use on approved ICP hypotheses plus customer, search, review, forum, procurement, support, or public-market evidence before designing an AI-visibility prompt architecture.

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。

Turn an approved measurement charter, ICPs, and buyer jobs into a budget-aware prompt coverage blueprint across proximity bands, aided status, information acts, journey states, roles, locales, evidence grades, partitions, and measurement lanes. Use before prompt wording to define required, optional, and prohibited canonical intent cells.

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。

Post-meeting debrief — analyzes what happened, compares outcomes to your prep intentions, tracks decision evolution. Use when the user says "debrief", "what just happened in that meeting", "what did we decide", "debrief that call", "post-meeting", "what changed", or right after stopping a recording.

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。

Consolidated accessibility skill entrypoint for WCAG 2.2, ARIA Authoring Practices, cognitive accessibility, Section 508, EN 301 549, design intent verification, and the Accessibility Planner workflow.

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。

Find and fix a bug in the octane monorepo. Use when given a failing test, a regression, or a report that behavior differs from expectation, including deciding whether a React mismatch is an intentional divergence.

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。

Plan an e-commerce category / collection page that ranks and merchandises well. Use when asked to design a category page, a PLP (product listing page), a collection page, or to improve category SEO and merchandising. Produces a brief — search intent & keywords, intro copy, merchandising/sort logic, filters & facets, internal links, and SEO/technical notes — so the page converts browsers and earns organic traffic.

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。

Help users navigate the path from junior product manager to executive leadership by focusing on ownership, cross-functional influence, and intentional career design.

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。

Help users master their personal output by shifting from reactive scheduling to intentional energy management, internal trigger mastery, and proactive boundary setting.

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。

Help users interact with probabilistic models by designing interfaces that manage fluidity, intent, and agency while maintaining trust and control.

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。

Intent-based search router with trust scoring. Routes queries to optimal channels (Context7 docs, native web search, gh/glab code search, Serena local) and attaches domain trust labels. Use for search, find, lookup, reference, docs, code search, and web research.

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。

Design-first ideation that explores user intent, constraints, and approaches before any planning or implementation. Use for brainstorming, ideation, exploring concepts, and evaluating approaches.

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。

Intent-based observability + traceability router across layers, boundaries, and signals. Routes to vendor-specific skills via category taxonomy; owns transport tuning, meta-observability, incident forensics. Use for observability, traceability, telemetry, APM, RUM, metrics, logs, traces, profiles, SLO, incident forensics, tracing architecture 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。

Live SEO data via DataForSEO MCP server. SERP analysis (Google, Bing, Yahoo, YouTube), keyword research (volume, difficulty, intent, trends), backlink profiles, on-page analysis (Lighthouse, content parsing), competitor analysis, content analysis, business listings, AI visibility (ChatGPT scraper, LLM mention tracking), and domain analytics. Requires DataForSEO extension installed. Use when user says "dataforseo", "live SERP", "keyword volume", "backlink data", "competitor data", "AI visibility check", "LLM mentions", or "real search data".

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 whenever the task involves inspecting, modifying, or building plugins for Bethesda games via the forked xEdit automation daemon. Loads first; routes to the right path (MCP intent tool, MCP atomic passthrough, or sub-agent delegation) and prevents the agent from bypassing the harness.

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。

Live SEO data via DataForSEO API credentials. SERP analysis (Google, Bing, Yahoo, YouTube, Google Images), keyword research (volume, difficulty, intent, trends), backlink profiles, on-page analysis (Lighthouse, content parsing), competitor analysis, content analysis, business listings, AI visibility (ChatGPT scraper, LLM mention tracking), and domain analytics. Uses DataForSEO credentials from the selected project `.env`; MCP tools are optional adapters when already available. Use when user says "dataforseo", "live SERP", "keyword volume", "backlink data", "competitor data", "AI visibility check", "LLM mentions", "image SERP", "google images", "image rankings", or "real search data".

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。

Scaffold a TanStack app with tanstack create using --framework, --template, --toolchain, --deployment, --add-ons, --blank, and --router-only. Covers flag compatibility, non-interactive defaults, and intent-preserving command construction.

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。

End-to-end outbound prospecting: detect intent signals, research companies, find decision-maker contacts, personalize messaging, launch campaign.

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 a prospect list of companies with decision makers, verified contact info, and hiring/intent signals. Use when asked to find leads by industry, build an account list with specific titles, prospect companies that are actively hiring, or create a targeted outreach list filtered by company size, location, and hiring activity.

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。

End-to-end Google Search Ads campaign builder. Performs deep keyword research (competitor SEO, review language mining, Reddit/HN community terminology, site audit), builds keyword architecture with funnel mapping and intent classification, creates ad group structure, generates headline/description variants, builds negative keyword lists, recommends bid strategy, and exports a campaign-ready CSV for Google Ads Editor import.

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。

Guidelines for making .NET libraries and applications trimming-safe and Native AOT compatible. Covers the trimming/AOT model, the MSBuild properties that enable analysis (IsTrimmable, IsAotCompatible, PublishTrimmed, PublishAot), the trimming attributes (RequiresUnreferencedCode, RequiresDynamicCode, DynamicallyAccessedMembers, UnconditionalSuppressMessage), IL2xxx/IL3xxx warning codes, and a pattern playbook: source generators and UnsafeAccessor, generated-interception diagnostic suppressors, intentional runtime scanning boundaries, trimming-safe islands and feature switches, migration analyzers, and temporary warning-approval baselines. Use when introducing trimming/AOT support, resolving IL2xxx/IL3xxx warnings, or making reflection-heavy code trimming-safe in C# / .NET codebases. For System.Text.Json AOT scenarios, see also the serialization skill.

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。

Implement, review, or improve WidgetKit widgets and controls. Use when building Home Screen, Lock Screen, StandBy, or CarPlay widgets with timeline providers; configurable widgets with AppIntentTimelineProvider; interactive widgets or Control Center controls with Button/Toggle wiring; WidgetKit push reloads, refresh budgets, deep links, Smart Stack relevance, Liquid Glass/accented rendering, widget extension setup, WidgetBundle, App Groups, and entitlements.

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。

Writes turn-level tests for a LiveKit agent in the user's normal test suite: pytest (Python) or Vitest (Node.js). Use when the user asks to "write tests for my agent", "add a test for this tool", "test the handoff", "pin this bug", "why does my agent test fail", or after building or changing agent behavior that needs regression coverage. Covers the SDK's test session harness, assertions on messages, tool calls and handoffs, LLM judging of a reply against an intent, mocking tools, multi-turn tests, and judging whole conversations with the built-in judges. For interactive poking use debugging-livekit-agents. For grading whole conversations at scale use running-livekit-simulations.

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。

Guides Stripe integration decisions across development and test environment planning (separate sandboxes vs the shared test mode sandbox), API selection (Checkout Sessions vs PaymentIntents), Connect platform setup (Accounts v2, controller properties), billing/subscriptions, tax and registrations (Stripe Tax, automatic_tax, product tax codes), Treasury financial accounts, integration options (Checkout, Payment Element), migrating from deprecated Stripe APIs, and security best practices (API key management, API key permissions, webhooks, OAuth). Use when planning, building, modifying, testing, or reviewing any Stripe integration, including choosing a development environment, accepting payments, building marketplaces, integrating Stripe, processing payments, setting up subscriptions, collecting sales tax, VAT, or GST, creating connected accounts, or implementing secure key handling.

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。

Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.

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。