Skills（SKILL.md）は、AIエージェント（Claude Code、Cursor、Codexなど）に特定の能力を追加するための設定ファイルです。
詳しく見る →Creates phase-based feature plans with quality gates and incremental delivery structure. Use when planning features, organizing work, breaking down tasks, creating roadmaps, or structuring development strategy. Keywords: plan, planning, phases, breakdown, strategy, roadmap, organize, structure, outline.
Break down feature requests into detailed, implementable plans with clear tasks. Use when user requests a new feature, enhancement, or complex change.
Feature-Sliced Design (FSD) is an architectural methodology for organizing frontend applications into a standardized, scalable structure. It provides clear separation of concerns through a layered hie
feature-slicing
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Reviews feature specifications for completeness, testability, and implementation readiness. Validates acceptance criteria, edge cases, and technical constraints. Use when reviewing feature specs before implementation or during sprint planning.
Creates focused feature specifications with user stories, acceptance criteria, and edge cases. Lighter than PRD, focuses on single feature implementation. Use when specifying individual features after PRD approval or for standalone feature work.
Feature specification and planning guidelines for software engineers. This skill should be used when writing PRDs, defining requirements, managing scope, prioritizing features, or handling change requests. Triggers on tasks involving feature planning, specification writing, stakeholder alignment, or scope management.
Guide iterative specification and CDC (Cahier Des Charges) creation through deep questioning, context analysis, and proactive proposals. Use this skill BEFORE feature-research to clarify requirements, identify prerequisites, define scope, and document complete specifications. Triggers when starting a new feature, task, bug fix, or refactoring and requirements need clarification.
Validate features_backlog.md for an idea against concept_summary.md and epics_backlog.md (writes report to ideas/<IDEA_ID>/runs and updates ideas/<IDEA_ID>/latest; optional patch if allowed)
Guide for building and maintaining ActivityPub/fediverse applications using Fedify. This skill should be used when users want to create federated social applications, implement ActivityPub protocols, build new features, test and debug federation, deploy to production, look up FEPs, or maintain existing Fedify applications.
Capture and analyze product feedback with full metadata
Systematically gather, organize, and act on user feedback
Navigate difficult conversations and deliver constructive feedback using structured frameworks. Covers the Preparation-Delivery-Follow-up model and Situation-Behavior-Impact (SBI) feedback technique. Use when preparing for difficult conversations, giving feedback, or managing conflicts.
Use when receiving UAT feedback, bug reports, user testing results, stakeholder feedback, QA findings, or any batch of issues to investigate. Investigates each item BEFORE creating issues, classifies by type and priority, creates well-formed GitHub issues with proper project board integration.
feishu-messaging
Gordon Ramsay-style festival operations expertise - passionate, no-nonsense guidance for running winter festivals with STANDARDS
Use when user mentions a Jira issue key (e.g., PLAT-123) or needs context from Jira. Retrieves and formats issue details for PRISM agent workflows.
Fetches official documentation for external libraries and frameworks (React, Next.js, Prisma, FastAPI, Express, Tailwind, MongoDB, etc.) with 60-90% token savings via content-type filtering. Use this skill when implementing features using library APIs, debugging library-specific errors, troubleshooting configuration issues, installing or setting up frameworks, integrating third-party packages, upgrading between library versions, or looking up correct API patterns and best practices. Triggers automatically during coding work - fetch docs before writing library code to get correct patterns, not after guessing wrong.
Fetch reference implementations from core-supabase repository. Use when (1) implementing Repository layer with Supabase, (2) need RPC function usage patterns, (3) checking correct parameter structures and type assertions, (4) verifying Supabase integration patterns.
fetching-library-docs
Complete CI/CD video processing system. PROACTIVELY activate for: (1) GitHub Actions FFmpeg setup, (2) GitLab CI video pipelines, (3) Jenkins declarative pipelines, (4) FFmpeg caching strategies, (5) Windows runner workarounds, (6) GPU-enabled self-hosted runners, (7) Matrix builds for multi-format, (8) Artifact upload/download, (9) Video validation workflows, (10) BtbN/FFmpeg-Builds integration. Provides: YAML workflow examples, Docker container patterns, caching configuration, platform-specific solutions, debugging guides. Ensures: Fast, reliable video processing in CI/CD pipelines.
Complete Docker FFmpeg deployment system. PROACTIVELY activate for: (1) Docker FFmpeg image selection (jrottenberg, linuxserver), (2) GPU passthrough (NVIDIA, Intel, AMD), (3) Volume mounting and permissions, (4) Docker Compose video processing, (5) Kubernetes FFmpeg jobs, (6) Custom Dockerfile builds, (7) Windows/Linux/macOS Docker usage, (8) Resource limits and optimization, (9) Watch folder automation, (10) Production container patterns. Provides: Image comparison tables, GPU Docker commands, Compose examples, K8s manifests, troubleshooting guides. Ensures: Consistent, isolated FFmpeg environments across platforms.
Complete GPU-accelerated encoding/decoding system for FFmpeg 7.1 LTS and 8.0.1 (latest stable, released 2025-11-20). PROACTIVELY activate for: (1) NVIDIA NVENC/NVDEC encoding, (2) Intel Quick Sync Video (QSV), (3) AMD AMF encoding, (4) Apple VideoToolbox, (5) Linux VAAPI setup, (6) Vulkan Video 8.0 (FFv1, AV1, VP9, ProRes RAW), (7) VVC/H.266 hardware decoding (VAAPI/QSV), (8) GPU pipeline optimization with pad_cuda, (9) Docker GPU containers, (10) Performance benchmarking. Provides: Platform-specific commands, preset comparisons, quality tuning, full GPU pipeline examples, Vulkan compute codecs, VVC decoding, troubleshooting guides. Ensures: Maximum encoding speed with optimal quality using GPU acceleration.
Complete karaoke subtitle system and advanced animated text effects. PROACTIVELY activate for: (1) Karaoke-style highlighted lyrics, (2) ASS/SSA advanced subtitle styling, (3) Scrolling credits (horizontal/vertical), (4) Typewriter text animation, (5) Bouncing/moving text, (6) Text fade in/out effects, (7) Word-by-word text reveal, (8) Kinetic typography, (9) Lower thirds animation, (10) Countdown timers and dynamic text. Provides: ASS karaoke timing format, drawtext with time expressions, scrolling text patterns, text animation formulas, kinetic typography techniques, subtitle styling reference, multi-line animated text.
Complete Modal.com FFmpeg deployment system for serverless video processing. PROACTIVELY activate for: (1) Modal.com FFmpeg container setup, (2) GPU-accelerated video encoding on Modal (NVIDIA, NVENC), (3) Parallel video processing with Modal map/starmap, (4) Volume mounting for large video files, (5) CPU vs GPU container cost optimization, (6) apt_install/pip_install for FFmpeg, (7) Python subprocess FFmpeg patterns, (8) Batch video transcoding at scale, (9) Modal pricing for video workloads, (10) Audio/video processing with Whisper. Provides: Image configuration examples, GPU container patterns, parallel processing code, volume usage, cost comparisons, production-ready FFmpeg deployments. Ensures: Efficient, scalable video processing on Modal serverless infrastructure.
Complete FFmpeg + OpenCV + Python integration guide for video processing pipelines. PROACTIVELY activate for: (1) FFmpeg to OpenCV frame handoff, (2) cv2.VideoCapture vs ffmpeg subprocess, (3) BGR/RGB color format conversion gotchas, (4) Frame dimension order img[y,x] vs img[x,y], (5) ffmpegcv GPU-accelerated video I/O, (6) VidGear multi-threaded streaming, (7) Decord batch video loading for ML, (8) PyAV frame-level processing, (9) Audio stream preservation with video filters, (10) Memory-efficient frame generators, (11) OpenCV + FFmpeg + Modal parallel processing, (12) Pipe frames between FFmpeg and OpenCV. Provides: Color format conversion patterns, coordinate system gotchas, library selection guide, memory management, subprocess pipe patterns, GPU-accelerated alternatives to cv2.VideoCapture. Ensures: Correct integration between FFmpeg and OpenCV without color/coordinate bugs. See also: ffmpeg-python-integration-reference for type-safe parameter mappings.
Complete live streaming and protocol system for FFmpeg 7.1 LTS and 8.0.1 (latest stable, released 2025-11-20). PROACTIVELY activate for: (1) RTMP streaming to Twitch/YouTube/Facebook, (2) HLS output and adaptive bitrate (ABR), (3) DASH streaming setup, (4) Low-latency streaming (LL-HLS, LL-DASH), (5) SRT protocol configuration, (6) WebRTC/WHIP sub-second latency (FFmpeg 8.0+), (7) Protocol conversion (RTMP to HLS), (8) Multi-destination streaming, (9) nginx-rtmp integration, (10) Docker streaming services. Provides: Platform-specific stream commands, ABR ladder examples, encryption setup, latency optimization, WHIP authentication, production patterns. Ensures: Reliable live streaming with optimal quality and latency.
Complete browser-based FFmpeg system. PROACTIVELY activate for: (1) ffmpeg.wasm setup and loading, (2) Browser video transcoding, (3) React/Vue/Next.js integration, (4) SharedArrayBuffer and COOP/COEP headers, (5) Multi-threaded ffmpeg-core-mt, (6) Cloudflare Workers limitations, (7) Custom ffmpeg.wasm builds, (8) Memory management and cleanup, (9) Progress tracking and UI, (10) IndexedDB core caching. Provides: Framework-specific examples, header configuration, common operation recipes, performance optimization, troubleshooting guides. Ensures: Client-side video processing without server dependencies.
Review code changes for FFP project standards including multi-tenant security, British English, architecture patterns, and SOLID principles. Use when reviewing PRs, checking branch changes, or auditing code quality.
Testing toolkit for the FHIR Writing Clinical Notes specification at connectathons. Use when the user needs to test FHIR DocumentReference write operations, validate conformance with the Writing Clinical Notes spec, or participate in a FHIR connectathon for clinical notes. Includes templates, OAuth helpers, and automated test scenarios for both provider-authored and patient-asserted notes.
Comprehensive FHIR (Fast Healthcare Interoperability Resources) software development assistant. Use when working with FHIR APIs, implementations, or healthcare data exchange. Supports FHIR R4, R4B, R5, Implementation Guides (IGs), validation, terminology, and SMART on FHIR. Ideal for building FHIR servers, clients, validators, or healthcare applications that need to process FHIR resources.
Use when writing or editing novels, short stories, or any fiction manuscript. Trigger on: 'write fiction', 'edit my novel', 'developmental edit', 'line edit', 'character voice', 'plot hole', 'brainstorm', or fiction writing tasks.
A complete system for writing fiction—from initial concept through final draft.
Clerk for Crown fiduciary breaches, fund mismanagement, conflicts of interest, and failure to protect reserve lands; use for Fiduciary_Duty_Negligence queue.
Extract structured fields from unstructured log data using OPAL parsing functions. Covers extract_regex() for pattern matching with type casting, split() for delimited data, parse_json() for JSON logs, and JSONPath for navigating parsed structures. Use when you need to convert raw log text into queryable fields for analysis, filtering, or aggregation.
Validate field completeness, format correctness, and data quality for vehicle insurance CSV/Excel files.
fiftyone
FigJam plugin development workflow. Use when modifying code.ts (canvas rendering), ui.ts (WebSocket/UI), fixing plugin build errors, or adding new rendering features.
This skill processes files containing figlet tags and replaces them with ASCII art representations. It detects and preserves comment styles (forward slash forward slash, hash, double-dash, forward slash asterisk), automatically manages Node.js dependencies, and supports 400+ fonts (defaulting to the standard font). The skill should be used when a user requests converting marked text in a file to ASCII art using figlet tag syntax, or when they want to list available fonts.
figma-design-extraction
Extracts design tokens from Figma files and generates production-ready CSS, SCSS, JSON, TypeScript, and W3C DTCG format files using the Figma MCP server
Generate Figma mockups from wrangler specifications with hierarchical file structure and approval tracking
Extract design specifications from Figma designs using the Figma MCP server. Used during planning workflows to gather detailed design context for implementation.
Extract design specifications from Figma files using MCP integration.
Pixel-perfect implementation of Figma designs. When Claude needs to translate Figma designs into code with precise attention to autolayout, variables, and styles.
Figma design-to-code, design system extraction ve component generation rehberi.
Convert Figma designs into Flutter code through an automated workflow that extracts design metadata, generates reference code, exports assets, implements the UI, and iteratively tests until the implem
Create FilamentPHP v4 forms with fields, validation, sections, tabs, and relationships
Reusable logic for categorizing files as Command, Agent, Skill, or Documentation based on structure and content analysis