Sync and integrate Fever Partners API for plans, reviews, attendees, and venues. Use when implementing Fever data sync, debugging API issues, or building review/analytics features.

Example-based prompting techniques for in-context learning

Complete audio encoding and normalization system. PROACTIVELY activate for: (1) Audio codec selection (AAC, MP3, Opus, FLAC), (2) Loudness normalization (EBU R128, loudnorm), (3) Audio extraction from video, (4) Format conversion, (5) Volume adjustment and dynamics, (6) Noise reduction and EQ, (7) Channel operations (stereo/mono/surround), (8) Sample rate and bit depth conversion, (9) Audio fade in/out and crossfades, (10) Podcast and broadcast processing chains. Provides: Codec comparison tables, loudness standards reference, two-pass normalization scripts, professional mastering chains. Ensures: Broadcast-compliant audio with proper loudness and quality.

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.

Authoritative Python-FFmpeg parameter integration reference ensuring type safety, accurate parameter mappings, and proper unit conversions. PROACTIVELY activate for: (1) ffmpeg-python library usage, (2) Python subprocess FFmpeg calls, (3) Caption/subtitle parameter mapping (drawtext, ASS), (4) Color format conversions (BGR, RGB, ABGR, ASS &HAABBGGRR), (5) Time unit conversions (seconds, centiseconds, milliseconds), (6) Type safety validation (int, float, string), (7) Coordinate systems, (8) Parameter range enforcement, (9) Frame pipe handling, (10) Error detection for type mismatches. Provides: Complete parameter type reference, color format conversion tables, time unit conversion formulas, validation patterns, working Python examples with proper typing.

Complete FFmpeg video stabilization and 360/VR video processing. PROACTIVELY activate for: (1) Video stabilization (deshake, vidstab), (2) Hardware-accelerated stabilization (deshake_opencl), (3) 360/VR video transforms (v360), (4) Perspective correction (perspective), (5) Ken Burns/zoom-pan effects (zoompan), (6) Lens distortion correction (lenscorrection, lensfun), (7) Action camera footage, (8) Drone video processing, (9) VR headset formats. Provides: Stabilization workflows, 360 projection conversions, motion effects, lens correction.

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.

Analyze Field Labs coaching transcription data, calculate session metrics, and generate daily summaries. Use for processing Fieldy voice transcriptions and creating coaching reports.

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

Parse Figma design files into structured screen hierarchies. Use when working with Figma API, extracting text/labels from design nodes, traversing node trees, detecting cover frames, or parsing screen IDs (AUTO_0001, PSET_0002, etc.).

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.

Generate Android Jetpack Compose UI from Figma using Figma Desktop MCP (get_metadata, get_variable_defs, create_design_system_rules, get_design_context, get_screenshot). Automatically detect icon/vector nodes in Figma, obtain SVG/path data when available, and convert icons to Android VectorDrawable XML using Android MCP Toolkit (convert-svg-to-android-drawable). Use when the user shares a Figma link/node-id and asks to implement UI in Compose from Figma.

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

Generates React code for a full page based on pasted Figma 'Inspect' details. Uses the page scaffolder.

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

Session-based file cleanup for privacy compliance. Use to delete temporary files, uploaded clinical notes, generated outputs, and expired logs to maintain HIPAA-friendly operations.

How to use the file-factory CLI to create new React components, hooks, context providers, Next.js pages along with associated tests and storybook stories. ALWAYS use this tool instead of manually creating new components/hooks/contexts/pages to ensure consistent file structure and conventions.

Draft GitHub issues for i-am-bee/agentstack. Use when the user wants to report a bug, request a feature, or draft a general GitHub issue.

Audit all filename and naming conventions in the codebase against CLAUDE.md standards and common patterns. Use when user asks to check naming conventions, audit filenames, find naming inconsistencies, or validate file naming patterns.

Analyze files and get detailed metadata including size, line counts, modification times, and content statistics. Use when users request file information, statistics, or analysis without modifying files.

Imported skill file_ops from langchain

File Organization Standards Skill

File Organization AI Assistant

[PROJECT] file and directory structure conventions and enforcement

This skill provides guidance for implementing file-based communication protocols that enable multiple agents to coordinate through structured file reads and writes. This approach is particularly valua

Search for files and content in a codebase. Use when investigating a codebase, finding patterns, or locating specific files. Not for reading file content or simple directory listing.

Regex file search via gh-grep extension. TRIGGERS - search code files, grep repository, file content search.

This skill should be used when managing the file-based todo tracking system in the todos/ directory. It provides workflows for creating todos, managing status and dependencies, conducting triage, and integrating with slash commands and code review processes.