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概要と使いどころ
Living project knowledge for OpenFoodJournal — an iOS 26 food journaling app with AI-powered nutrition scanning. Consult this skill FIRST when starting any work on this project. Contains architecture decisions, data models, service contracts, current state, known issues, and conventions. Update this skill whenever requirements, architecture, or project state changes so it stays accurate across sessions.
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。
TypeScript and JavaScript expert with deep knowledge of type-level programming, performance optimization, monorepo management, migration strategies, and modern tooling. Use PROACTIVELY for any TypeScript/JavaScript issues including complex type gymnastics, build performance, debugging, and architectural decisions.
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。
Python development principles and decision-making. Framework selection, async patterns, type hints, project structure. Teaches thinking, not copying.
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。
When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' or 'monetization.' This skill covers pricing research, tier structure, and packaging 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。
When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' or 'consumer behavior.' This skill provides 70+ mental models organized for marketing application.
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。
Nest.js framework expert specializing in module architecture, dependency injection, middleware, guards, interceptors, testing with Jest/Supertest, TypeORM/Mongoose integration, and Passport.js authentication. Use PROACTIVELY for any Nest.js application issues including architecture decisions, testing strategies, performance optimization, or debugging complex dependency injection problems. If a specialized expert is a better fit, I will recommend switching and stop.
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。
Node.js development principles and decision-making. Framework selection, async patterns, security, and architecture. Teaches thinking, not copying.
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。
Mobile-first design thinking and decision-making for iOS and Android apps. Touch interaction, performance patterns, platform conventions. Teaches principles, not fixed values. Use when building React Native, Flutter, or native mobile apps.
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。
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation 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。
Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.
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。
Email has the highest ROI of any marketing channel. $36 for every $1 spent. Yet most startups treat it as an afterthought - bulk blasts, no personalization, landing in spam folders. This skill covers transactional email that works, marketing automation that converts, deliverability that reaches inboxes, and the infrastructure decisions that scale. Use when: keywords, file_patterns, code_patterns.
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。
Production deployment principles and decision-making. Safe deployment workflows, rollback strategies, and verification. Teaches thinking, not scripts.
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。
API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.
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。
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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。
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b
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, audit, and improve analytics tracking systems that produce reliable, decision-ready 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。
API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.
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。
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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 train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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。
ALWAYS use this skill whenever you would otherwise ask the user a question in free-form chat -- for clarifications, confirmations (especially destructive actions), missing parameters, multiple-choice decisions, or structured form input. Elicitations are routed through the Unique AI Platform UI via `unique-cli elicit create` + `elicit wait` (the default polling pattern) or a single supervised `unique-cli elicit ask` call (only when your agent instructions say your environment supervises the wait) so the user gets a proper structured prompt and you get a structured answer back. Do NOT ask the user in plain chat when you can use this skill instead.
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 the infrastructure implementation phase after the backend follows the model — turning documents/infra-design decisions into infra/ (local container stack, production IaC), wiring cradle.json infra.up / infra.containers, adding IaC validate and image build steps to CI, and, once E2E passes, applying production once in a sandbox and recording it in the deployment table. Not for designing infrastructure (infra-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。
Print Peephole's security audit report for this project — current mode, binary integrity, the CWE-mapped decision tally, sec-debt items needing approval, and tamper-evident log-chain status. Use when the user says /sec-audit or asks what Peephole has blocked or flagged.
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。
Busabase-backed App-in-Skill control-panel/workspace for a deal analyst to model revenue-based-financing (RBF) deals for SME businesses (retail/F&B chain stores). Use when the user invokes $kelly-revshare-simulator or /kelly-revshare-simulator, wants to model a revenue-share or merchant-cash-advance deal, project cash flow and repayment, compute a Cash-Flow Payout Multiple, effective annualized merchant cost, or compare/underwrite multiple financing scenarios. Pure deterministic math, no external calls, no real trading/payment side effects. Scenario create/edit/delete and the underwriting decision are direct writes made by the analyst, not a review/approval queue.
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。
E-commerce product-management desk (Busabase App-in-Skill) for catalog master data, SKUs, pricing, inventory, channel status, content assets, compliance notes, lifecycle state, and approval-gated product operations. Use when the user invokes $kelly-products or /kelly-products, asks for 电商商品管理, 商品库, SKU 管理, inventory/reorder, product status across Amazon/Shopify/TikTok Shop/eBay, channel publishing approvals, price-change review, quality holds, product lifecycle/archive decisions, or a Busabase-backed product management desk.
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。