「complex」の検索結果

Use CloudBase document database WeChat MiniProgram SDK to query, create, update, and delete data. Supports complex queries, pagination, aggregation, and geolocation queries.

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Create a workflow-intelligence report from CCAM orchestration, delegation, tool flow, concurrency, complexity, compaction, and fleet-run data. Use for architecture reviews, agent-fleet analysis, or workflow optimization reports.

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。

Compare two sessions side-by-side using Agent Monitor data — per-model token usage (input/output/cache_read/cache_write + compaction baselines), pricing engine cost breakdowns, workflow intelligence (complexity scores, tool flow transitions, subagent effectiveness), session metadata (thinking_blocks, turn_count, turn_duration_ms, usage_extras), and full event timelines with all 10+ event types.

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。

Identify anomalous sessions using Agent Monitor data — cost outliers from the pricing engine, token anomalies (cache miss spikes, compaction baseline surges), unusual event type ratios (PreToolUse/PostToolUse gaps, APIError clusters), behavioral deviations from workflow intelligence (complexity score outliers, error propagation anomalies), and sessions with abnormal metadata (extreme turn_count, high thinking_blocks, zero turn_duration).

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。

Calculate a productivity score using actual Agent Monitor metrics — session completion rates, cache efficiency (cache_read vs input), compaction pressure (baseline tokens), turn velocity (turn_count / total_turn_duration_ms), tool success ratio (PreToolUse vs PostToolUse), and the workflow intelligence API's complexity and effectiveness scores.

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。

Benchmark one session (or a small recent set) against the rolling average using Agent Monitor data — cost, total tokens, tool count, and workflow complexity score — and report where each metric lands as a percentile of the population. Tells you whether a session was normal, cheap, or an outlier. Use when judging whether a session was typical or out of band.

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。

Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage. Use when starting complex tasks, multi-step projects, research tasks, or when the user mentions planning, organizing work, tracking progress, or wants structured output.

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Generate a comprehensive marketing website for a web app — multi-page with real screenshots, animated GIF walkthroughs, feature deep-dives, and workflow demonstrations. Browses the running app, captures screens and sequences, and produces a deployable site that actually teaches people what the product does. Especially useful for complex or agentic apps that are hard to explain. Triggers: 'showcase site', 'product page', 'show off the app', 'marketing site', 'demo site', 'product showcase', 'explain the app', 'how do I market this'.

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。

Multi-agent orchestration for complex tasks. Use when tasks require parallel work, multiple agents, or sophisticated coordination. Triggers include requests for features, reviews, refactoring, testing, documentation, or any work that benefits from decomposition into parallel subtasks. This skill defines how to orchestrate work using cc-mirror tasks for persistent dependency tracking and TodoWrite for real-time session visibility.

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。

Simple scroll-triggered reveal animations using AOS (Animate On Scroll). Use this skill when building marketing pages, landing pages, or content-heavy sites requiring basic fade/slide effects without complex animation orchestration. Triggers on tasks involving scroll animations, scroll-triggered reveals, AOS, simple animations, or basic scroll effects. Alternative to GSAP ScrollTrigger and Locomotive Scroll for simpler use cases. Compare with motion-framer for React-specific animations.

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。

Modern animation library for React and JavaScript. Create smooth, production-ready animations with motion components, variants, gestures (hover/tap/drag), layout animations, AnimatePresence exit animations, spring physics, and scroll-based effects. Use when building interactive UI components, micro-interactions, page transitions, or complex animation sequences.

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Versatile JavaScript animation engine for DOM, CSS, SVG, and JavaScript objects. Use when creating timeline-based animations, stagger effects, SVG morphing, keyframe sequences, or complex choreographed animations. Triggers on tasks involving Anime.js, timeline animations, staggered sequences, SVG path animations, morphing, or multi-step animation choreography. Alternative to GSAP for SVG-heavy animations and React-independent 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。

Use when user requests diagrams, flowcharts, architecture charts, or visualizations. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Generates .excalidraw files and exports to PNG/SVG via Kroki API or locally using excalidraw-brute-export-cli.

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Iterative measurement-driven improvement loop. Measure, profile, mutate, re-measure, commit. Works for performance, bundle size, complexity, test coverage — anything quantifiable. Use when the user wants to systematically improve a metric through repeated cycles of profiling and targeted changes.

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Designing forms with multiple steps, progress indicators, conditional logic, and save-and-resume mechanics. The discipline of breaking complex data collection into stages that respect cognitive load while maintaining completion intent. Honest about kitchen-sink-single-page (overwhelms before the user starts), progress-theater (steps without genuine staging), and genuinely-staged (each step earns its own page) patterns. Triggers on multi-step form, multi-page form, form wizard, signup wizard, lead form, application form, intake form, configurator, onboarding form. Also triggers when a long form is converting poorly, when an audience is dropping off mid-form, or when a multi-step form is being scoped for the first time.

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。

Multi-perspective deliberation framework for complex scientific questions

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Analyze codebase health metrics including complexity and dependencies

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Cross-functional what-if modeling for compound adversity -- shows how one problem cascades into the next. Use when facing complex risk scenarios, strategic decisions with major downside, or multi-variable threats.

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。

Code review automation for TypeScript, JavaScript, Python, Go, Swift, and Kotlin. Analyzes PRs for complexity, risk, SOLID violations, and code smells. Use when reviewing PRs, analyzing code quality, or generating review checklists.

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Discover and recommend **combinations** of agent skills to complete complex, multi-faceted tasks. Provides two recommendation strategies — **Maximum Quality** (best skill per subtask) and **Minimum Dependencies** (fewest installs). Use this skill whenever the user wants to find skills, asks "how do I do X", "find a skill for X", or describes a task that likely requires multiple capabilities working together. Also use when the user mentions composing workflows, building pipelines, or needs help across several domains at once — even if they only say "find me a skill". This skill supersedes simple single-skill search by decomposing the task into subtasks and assembling an optimal skill portfolio.

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Generates standalone interactive HTML "deal cards" that translate complex regulations into negotiation-ready reference tools, systematically distinguishing mandatory obligations from negotiable implementation choices. Use when the user needs an interactive regulatory guide for (1) contract negotiation support, (2) client education or internal training, (3) regulatory briefings for commercial stakeholders, or (4) structured comparison between required and flexible compliance paths. Primary focus on EU digital regulation (Data Act, AI Act, CRA, DORA, NIS2, GDPR) but the structural pattern transfers to any regulation where separating hard obligations from implementation choice is the point. Supports bilingual output where the jurisdiction calls for it.

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。

Audits legal AI outputs and workflows for honest compression: unnecessary complexity, false simplicity, excessive caveats, hidden uncertainty and poor cost per legally acceptable 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。

Firm-matter matching, matter instruction drafting, firm onboarding checklist, and instruction audit for in-house legal ops teams. Match a new matter to the right panel firm by practice area, jurisdiction, complexity, and cost tier. Produce a structured matter instruction with scope, timeline, budget, staffing, and reporting requirements. Generate an onboarding checklist covering conflict clearance, engagement letter, OCG acknowledgment, e-billing setup, and platform access. Audit an existing instruction for completeness and produce a remediation note. Trigger on: 'which firm should handle this', 'instruct the firm', 'write the instruction', 'matter instruction template', 'onboard the firm', 'set up the matter', 'conflict check', 'e-billing setup', 'is our instruction complete', 'review our instruction', 'instruction gap', 'allocate this matter'.

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。

Framework for demonstrating AI capabilities in legal contexts. Provides detailed personas across tenant law, business contracts, startup disputes, employment claims, and consumer protection with progressive complexity scenarios. Use when: (1) Demonstrating AI-powered legal triage or intake systems, (2) Showcasing responsible AI-assisted client interactions, (3) Training staff on appropriate AI use in legal contexts, (4) Creating realistic scenarios for legal tech presentations, (5) Developing educational materials about AI in legal services, or (6) Testing AI-powered legal information systems in controlled environments.

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。