「planning」の検索結果

Expert en véhicules autonomes (perception, planning, ROS, simulation, safety)

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 planning or building a SaaS MVP from scratch. Provides a structured roadmap covering tech stack, architecture, auth, payments, and launch checklist.

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。

Estimate AI-assisted and hybrid human+agent development work with research-backed PERT statistics and calibration feedback loops

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。

Expert startup business analyst specializing in market sizing, financial modeling, competitive analysis, and strategic planning for early-stage companies.

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 comprehensive 3-5 year financial models with revenue projections, cost structures, cash flow analysis, and scenario planning for early-stage startups.

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。

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.

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。

6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

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。

Develops an implementation plan ready for wave-orchestration to execute. Takes the user's goal or rough plan as input, mines the codebase for facts, grills the user one question at a time for the decisions, drafts the planning/ artifacts (task DAG, wave table, worker prompt template, state file), then reviews its own plan on two axes before seeking approval. Use when the user wants to turn a feature idea, master plan, or backlog into a wave-orchestration execution plan.

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。

Structured planning workflow for any coding task. Use at the start of every new feature, bug fix, refactor, or implementation request. Analyzes the project, asks up to 5 clarifying questions, creates a TODO.md, gets user approval, then executes task by task. Never writes code before a plan is approved.

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。

Work like Manus: Use persistent markdown files as your "working memory on disk."

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 just says "plan", "planen" or "roadmap": offer a template via aos-plan-canvas templates. Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page. Use for planning, whenever a user says "plan", "roadmap", "visualize the plan", "review the plan" or /plan-canvas, right after a brainstorm or grill interview has produced a plan, and whenever any skill's artifact (plan, design, comparison, report, diagram) can be reviewed visually instead of with typed feedback.

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 a user asks for a plan for a coding task, to generate a clear, actionable, and atomic checklist.

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。

BDB Shipping Godmode, the final gatekeeper for production releases. Use when running pre-launch checks, feature-flag rollouts, or rollback planning under Spec-Driven Development before a release ships.

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 brainstorming or planning live event technology, show control, and real-time media systems (TouchDesigner, Resolume, grandMA3).

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 for event agency operations: client intake, project scoping, vendor management, crew coordination, production planning, pre-show logistics, and post-show wrap. Delegates technical execution to godmode-eventtech and bdbmediastorm.

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 data persistence using SwiftData. Use when defining @Model classes with @Attribute, @Relationship, @Transient, @Unique, or @Index; when querying with @Query, #Predicate, FetchDescriptor, or SortDescriptor; when configuring ModelContainer and ModelContext for SwiftUI or background work with @ModelActor; when planning schema migrations with VersionedSchema and SchemaMigrationPlan; when setting up CloudKit sync with ModelConfiguration; or when coexisting with or migrating from Core 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。

Translate Figma designs into production-ready SwiftUI code with 1:1 visual fidelity using the Figma MCP workflow. Trigger when the user provides Figma URLs or node IDs and wants iOS/SwiftUI implementation, asks to implement a design or component from Figma for an iOS app, or references Figma selections in the context of an Xcode/SwiftUI project. Also trigger when user asks to inspect Figma designs for iOS planning, fetch design tokens for SwiftUI, or convert Figma assets for Xcode. Requires a working Figma MCP server connection. Do NOT trigger for web/React implementations.

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 reactive, type-safe, production-grade backends. ALWAYS use this skill when the user asks to build, plan, design, or implement backend features, APIs, data models, server logic, database schemas, web apps, full stack apps, or mobile apps. This includes planning and architecture discussions.

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。

Structured task planning with clear breakdowns, dependencies, and verification criteria. Use when implementing features, refactoring, or any multi-step 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。

Use when a user asks for a plan for a coding task, to generate a clear, actionable, and atomic checklist.

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 SEO-optimized marketing content with consistent brand voice. Includes brand voice analyzer, SEO optimizer, content frameworks, and social media templates. Use when writing blog posts, creating social media content, analyzing brand voice, optimizing SEO, planning content calendars, or when user mentions content creation, brand voice, SEO optimization, social media marketing, or content strategy.

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。

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool use, function calling.

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。

Planning workflow - OBSERVE → ORIENT → PLAN → APPROVE → EXECUTE → DOCUMENT

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。

6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

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。