「features」の検索結果

Takes a Python repository and natural language feature description as input, implements the feature with proper code placement, generates comprehensive tests, and ensures all tests pass. Use when Claude needs to: (1) Add new features to existing Python projects, (2) Implement functions, classes, or modules based on requirements, (3) Modify existing code to add functionality, (4) Generate unit and integration tests for new code, (5) Fix failing tests after implementation, (6) Ensure code follows existing patterns and conventions.

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Incrementally implement new features in Java repositories from natural language descriptions. Use when adding functionality to existing Java codebases (Maven or Gradle projects). Takes a feature description as input and outputs modified repository with implementation code, corresponding JUnit tests, and verification that all tests pass. Supports method additions, new class creation, and method modifications with proper Java conventions.

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Automatically generates change logs from git commits, patches, and pull requests. Use when preparing software releases, creating version summaries, or maintaining CHANGELOG.md files. Analyzes commit messages (including conventional commits), diff/patch files, and PR data to produce categorized Markdown change logs organized by type (Features, Bug Fixes, Breaking Changes, etc.). Ideal for release notes, version updates, and automated changelog maintenance.

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Suggest and apply code refactorings to improve readability, maintainability, and code quality. Use this skill when improving existing code structure, eliminating code smells, applying design patterns, simplifying complex logic, extracting duplicated code, renaming for clarity, or preparing code for new features. Provides specific before/after examples, explains benefits, identifies risks, and ensures behavior preservation through tests.

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You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

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Add strategic color to features that are too monochromatic or lack visual interest. Makes interfaces more engaging and expressive.

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Audit and enable security-oriented Xcode build settings, compiler warnings, static analysis, and Enhanced Security features.

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New SwiftUI features and patterns for iOS 27 and macOS 27: @State macro, reorderable containers, AsyncImage caching, and new swipe actions.

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Modernize test suites to use modern Swift Testing features or migrate from XCTest.

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Streams change data capture from PostgreSQL into Redpanda or Kafka using Redpanda Connect's postgres_cdc input, which reads the WAL through logical replication (pgoutput). Use when configuring postgres_cdc (formerly pg_stream), setting up wal_level=logical, replication slots, and publications, enabling an initial snapshot before streaming, or troubleshooting slot growth and WAL accumulation. Also covers Redpanda Enterprise destination features such as Iceberg Topics, Tiered Storage, and server-side Schema ID Validation, since postgres_cdc itself requires a Redpanda Enterprise license.

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Generate high-quality Product Requirements Documents (PRDs) for software systems and AI-powered features. Includes executive summaries, user stories, technical specifications, and risk analysis.

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Build production-ready LLM applications, RAG systems, and intelligent agents. Use when implementing AI features, chatbots, vector search, or agent orchestration.

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Competitive intelligence and market positioning analysis. Researches competitors, compares features, pricing, and tech stacks, then produces a prioritized gap analysis with actionable roadmap. Trigger on: competitors, competitive analysis, gap analysis, feature comparison, market research, what are we missing, who are our competitors, pricing comparison, market positioning.

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Kelvin Garr's personal AICA brand identity and implementation framework. Use ONLY when building Kelvin's personal sites, portfolio, or AICA-branded projects. Features fixed visual identity (black glass + gold circuits + Space Grotesk) and Next.js 14 implementation guide. For client work with AICA methodology but their branding, use design-guide-updated instead.

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TanStack Table v8 headless data tables with server-side features for Cloudflare Workers + D1. Use for pagination, filtering, sorting, virtualization, or encountering state management, TanStack Query coordination, URL sync errors.

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Creates detailed technical specifications for software projects covering requirements, architecture, APIs, and testing strategies. Use when planning features, documenting system design, or creating architecture decision records.

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Automate 7-phase feature development with specialized agents (code-explorer, code-architect, code-reviewer). Use for multi-file features, architectural decisions, or encountering ambiguous requirements, integration patterns, design approach errors.

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Skill for integrating Better Auth - comprehensive TypeScript authentication framework for Cloudflare D1, Next.js, Nuxt, and 15+ frameworks. Use when adding auth, encountering D1 adapter errors, or implementing OAuth/2FA/RBAC features.

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Use when building APIs with Hono framework on Bun, including routing, middleware, REST APIs, context handling, or web framework features.

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Use when ranking a list of requirements, features, or backlog items using RICE / ICE / MoSCoW / Kano. Built-in decision tree picks the right framework based on data availability and decision context. Output is a transparent matrix, 2×2 Impact/Effort quadrant, and a Sprint allocation proposal. User-invoked only — do NOT auto-trigger. Triggers on "/pm-prioritize", "/prioritize", "приоритизация", "ранжируй бэклог", "RICE-анализ", "prioritize requirements", "RICE", "ICE", "MoSCoW", "Kano", "rank backlog".

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End-to-end, phase-gated SDLC for AI coding agents: relentless design interview → reviewed spec → dependency-graphed task board → safe-wave TDD execution → verification → converge. Handles features, bugs, refactors, greenfield projects, planning breakdowns, and migrations. Triggers on "absolute work", "build this end-to-end", "plan and build", "break this into tasks", "grill me on this plan", "pick up this ticket", "run this migration".

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Test-driven development with red-green-refactor loop. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, or asks for test-first development.

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Use when user asks to translate videos, dub video content, or localize videos into other languages. Translate videos with AI-powered dubbing using iFlytek (Xfei) Video Translation API. Supports video language translation, voice dubbing, multilingual video localization, 视频翻译, 视频配音, 视频本地化. Features task creation, task list, task details retrieval. Ideal for content creators and localization teams.

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Institutional-grade equity research skills for AI agents. 80 Claude-type skills across 14 verticals (equity-research-core, models-and-pitches, bio-pharm, scenarios, quantitative-analysis, idea-generation, options-derivatives, business-intelligence, industry-analysis, macro-strategy, portfolio-strategy, technical-analysis, risk-and-psychology, trading-as-business) powered by agentii.ai's agent-use-ready SEC filing data plane — SEC filings and 15K+ earnings call transcripts, 15.99M XBRL facts, and company profiles for 1,146+ US-public-equity tickers. Features the three-layer retrieval protocol (Document Discovery → Page Map → Deep Read, with deep-outline escalation) — measured, not asserted: 97.5% saved against a sequential read, and the page map itself is 10.0% of one (spec 062 T030, 2026-09-23) — server-side parallel multi-period search via search_cross_period, a full Excel/PPT generation pipeline with 3-tier office backend support, and the spec-046 governance layer (constitution, thesis and single-skill modes, mechanical gates, and a template-owned disclaimer on generated reports).

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