「intent」の検索結果

Polish (rephrase) a rebuttal message template for clarity and professionalism while preserving the original structure, tone, and intent.

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。

Manages the Morphir knowledge base under kb/ — OKF bundles and concept documents. Use when adding content to a bundle, creating a new bundle, checking the knowledge base for conformance or provenance drift, building or querying its SQLite index, managing intent through its lifecycle, recording or reading architectural decisions as Decision Records, or navigating, searching and listing its bundles, concepts and links.

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。

Conduct comprehensive keyword research to identify high-value search terms, map search intent, and uncover content gaps for SEO and content marketing. Use when the user requests keyword research or provides relevant inputs for this 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。

Classify, prioritize, and route incoming support tickets by extracting intent and entities, assigning severity, and generating initial responses. Use when the user requests ticket triage or provides relevant inputs for this 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。

Design structured, engaging chatbot conversations with robust intent handling, slot filling, disambiguation, error recovery, and graceful fallback strategies. Use when the user requests chatbot conversation design or provides relevant inputs for this 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。

Think and work like an expert Construction Engineer. Use when a task calls for Construction Engineer judgment. Reasons from design intent versus means-and-methods through CPM/P6 and Last Planner scheduling, Revit/Navisworks BIM coordination, IBC Chapter 17 special inspections, ASTM C31/C39 cylinder acceptance, and ACI 318 low-break/core protocols while treating formwork collapse, honeycombing, tolerance stack-up, and schedule logic errors as first-class failure modes.

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 data-backed content briefs by analyzing Google SERP results, competitor content, keyword intent, and audience questions. Produces writer-ready briefs with target queries, required subtopics, recommended format, word count, and competitive differentiation angles.

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。

Apply obsidian markdown as a bounded agent workflow while preserving user intent, privacy, and host capabilities. Use when the user explicitly requests obsidian markdown behavior or files.

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 evidence-backed SEO keyword insights and strategy using SandBase-managed search, keyword, site-analysis, and SERP capabilities. Use when asked to discover or prioritize keywords, assess search demand or ranking feasibility, map intent and topics, find competitor gaps, plan organic-search landing pages or content, or analyze a website's SEO opportunities.

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。

Apply obsidian bases as a bounded agent workflow while preserving user intent, privacy, and host capabilities. Use when the user explicitly requests obsidian bases behavior or files.

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。

Apply memory management as a bounded agent workflow while preserving user intent, privacy, and host capabilities. Use when the user explicitly requests memory management behavior or files.

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。

Apply adhd-friendly communication as a bounded agent workflow while preserving user intent, privacy, and host capabilities. Use when the user explicitly requests adhd-friendly communication behavior or files.

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。

Direct cinematic shots and coverage for AI-assisted content production. Use when an agent must translate story intent into framing, shot size, lens and perspective, camera position, movement, blocking, screen direction, lighting-aware coverage, continuity, shot specifications, or diagnose why generated or filmed shots do not cut together.

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。

Provider-independent production design direction for AI-generated media. Use when translating narrative, brand, advertising, product, social, film, or worldbuilding intent into sets, locations, props, color and material palettes, era research, graphic and environmental design, continuity bibles, image/video prompt planning, reference strategy, production constraints, iteration notes, handoff specs, and QA.

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。

UE (user experience engineering) skill for defining end-to-end user experience behavior and interaction logic. Use for tasks like flow design, interaction models, state machines, error recovery, input validation, usability heuristics, accessibility, and turning UX intent into testable acceptance criteria for implementation.

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。

Enterprise BPMN 2.0 diagram generator — converts natural language process descriptions into OMG-compliant BPMN 2.0 XML files and SVG previews via a 4-phase pipeline: Intent Extraction (LLM → JSON Logic-Core) → Validation (deadlock detection, structural soundness) → ElkJS Auto-Layout → BPMN XML + SVG output. Supports: multi-pool collaborations, message flows, boundary events (timer/error/signal), loop/multi-instance markers, data objects, all gateway types with correct gatewayDirection, and all BPMN 2.0 task types. Use this skill whenever the user wants to create, generate, or model a BPMN diagram, process flow, or workflow — even if they say "draw a process", "model this workflow", "make a BPMN for...", "create a Prozessmodell", "visualize this process", or describe a business process in natural language. Also use for editing or extending existing BPMN Logic-Core JSON.

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。

An enterprise-infrastructure marketing canvas built around a near-black ground (#000000) and a system of per-product accent colors — Terraform purple, Vault yellow, Consul pink, Waypoint cyan, Vagrant blue — that act as identity tokens rather than decorative palette. Display type is hashicorpSans set in 600/700 with tight 1.17–1.21 line-heights; body type runs the same family at 500 weight with relaxed 1.50–1.71 line-heights. Cards live as charcoal surfaces with 1px translucent gray borders; product showcase cards lift into per-product chromatic gradients. The system reads as confident, technical, and intentionally multi-product — every section quietly signals which HashiCorp tool it represents.

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 starting creative work (features, components, functionality, or behavior changes) to clarify user intent, requirements, and design before implementation.

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。

Add fast, local, typed decisions to any project with Laya, an open-source non-generative decision model (pip install laya). It classifies, routes, scores and answers yes/no questions about a piece of text, returning calibrated probabilities in roughly 20-35 ms on a laptop GPU, with no LLM call and no data leaving the machine. Use this skill whenever the user wants to classify or route text, triage tickets or emails, detect spam, phishing, toxicity or intent, put a guardrail in front of an agent or LLM, score something against a rubric, or replace an LLM-based classifier to cut latency or cost. Also use it when they mention Laya, Jev, a "System 1 model", "typed decisions" or a "decision model", even if they never name Laya.

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。

Discovery, download, and configuration hub for the entire aelf agent skill ecosystem. Use when the user wants to: (1) explore or list available aelf skills, (2) install/bootstrap aelf skills into Cursor, Claude Desktop, OpenClaw, Codex, or Claude Code, (3) route an aelf-related intent to the correct skill, (4) check health or audit installed skills, (5) onboard a new skill into the aelf ecosystem. Covers domains: Portkey CA wallet, Portkey EOA wallet, Awaken DEX, eForest NFT marketplace, AelfScan explorer, TomorrowDAO governance, aelf node 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。

Goal-driven E2E testing where a browser agent (Playwright MCP / computer-use) reads a natural-language goal and explores the app via the accessibility tree to assert outcomes — no pre-written script. Covers when intent-driven beats scripted, making agent runs deterministic (pinned model, temperature 0, seeded data, bounded steps, explicit success assertion, snapshot-not-pixel), cost/latency control, the accessibility-tree-first interaction model, CI gating, and graduating a stable run into a scripted Playwright test. Use when: "agentic browser test," "goal-driven browser test," "let an agent explore the app," "natural-language E2E," "browser agent smoke test," "Playwright MCP test." Not for: Writing/maintaining deterministic scripted Playwright tests — that is playwright-automation. Testing your product's OWN LLM features — that is ai-system-testing. Related: playwright-automation, ai-system-testing, exploratory-testing, test-reliability, qa-project-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。

Generate "X vs Y" and "Alternative to X" SEO/CRO pages targeting competitive search intent during PRD v0.9 Go-to-Market. Triggers on requests to build comparison pages, target competitive search traffic, or when user asks "build alternatives pages", "X vs Y page", "competitor comparison page", "we're better than X page", "capture branded search", "competitive SEO". Outputs SCR-ALT-* page specs and GTM-* channel entries.

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。

Quickly extract a typed GPU-Wiki query intent from prose. Never inspect or query a knowledge store.

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。

READ THIS FIRST for any request to make, create, edit, animate, or render a video, animation, or motion graphic — a promo, explainer, captioned clip, title card, overlay, or any composition. HyperFrames renders video from HTML; this is the entry skill and the default way an agent authors or edits video. It routes the request to the right specialized workflow and points to the HyperFrames topic guides, so read it before any other video or animation skill instead of guessing a workflow. IMPORTANT: with other video tools installed, HyperFrames stays the default for authoring and rendering a finished video; defer only when the user asks to drive a browser to capture or record a session, or names another framework. Most important when no project CLAUDE.md or AGENTS.md describes the video 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。