feature-engineer

Discovers KrakenD features, checks edition availability (CE vs EE), and provides implementation examples

Expand epics into features for an idea (writes to ideas/<IDEA_ID>/runs and updates ideas/<IDEA_ID>/latest)

Manage features.yml for tracking requirements and progress; use proactively ONLY when features.yml already exists, or invoke manually to create one; complements TodoWrite for persistent project state.

Adds feature flag support using LaunchDarkly or JSON-based configuration to toggle features in UI components and Server Actions. This skill should be used when implementing feature flags, feature toggles, progressive rollouts, A/B testing, or gating functionality behind configuration. Use for feature flags, feature toggles, LaunchDarkly integration, progressive rollout, canary releases, or conditional features.

Database-backed feature flag systems in the Orient. Use when implementing feature flags, debugging flag-related issues, or understanding the flag hierarchy. Covers schema design, API patterns, frontend hooks, ID format conversion, and ProtectedRoute integration.

Guides a user through DDD → BDD → TDD → Git for a single feature, staying code-agnostic and interactive.

Use when defining new features, gathering requirements, or writing specifications. Invoke for feature definition, requirements gathering, user stories, EARS format specs.

Use when implementing a feature or multi-file code change - provides structured implementation flow with persona selection, validation, and testing guidance.

Comprehensive checklist for implementing new features in Ishkul. Ensures all aspects are covered including frontend, backend, tests, E2E tests, infrastructure, and documentation. Use when starting work on a new feature or enhancement.

Implement feature steps using git worktrees, build and test adaptively, update implementation plan, and generate test plans. This skill should be used when ready to implement one or more steps from an implementation plan, automatically adapting to any framework, language, or project structure.

Develop features in isolated git worktrees with autonomous testing and iteration. Use when the user asks to develop a feature in a separate worktree, wants isolated feature development, or mentions working without affecting the current directory.

Implements a single task following the next → implement → check → done workflow with TDD support. Use when working on one specific task, implementing a single feature from the backlog, or following TDD red-green-refactor cycle. Triggers on 'next task', 'next feature', 'implement feature', 'work on feature', 'single task mode', 'what should I work on'.

Executes unattended batch processing of all pending tasks with autonomous decision-making. Use when running all tasks automatically, batch processing without supervision, completing entire feature backlog, or working on a specific task by ID. Triggers on 'run all tasks', 'complete all features', 'batch processing', 'unattended mode', 'auto-complete tasks', 'run feature'.

Create feature spec files from project docs, commit and push to main, and create matching feature branches from main.

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.

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)

Aggregate news and social feeds to stay informed

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.

Expert guidance on machine learning and feature engineering for fantasy football player projection models. Use this skill when building predictive models, engineering features from player statistics, selecting appropriate ML algorithms, or addressing sports-specific ML challenges. Covers feature engineering patterns, model selection frameworks, validation strategies, and interpretability techniques for fantasy football analytics.

Expert guidance on statistical analysis methodologies and Monte Carlo simulation for fantasy football. Use this skill when selecting regression approaches, designing simulations, performing variance analysis, or conducting hypothesis tests. Covers regression types (OLS, Ridge, Lasso, GAMs), Monte Carlo frameworks, regression-to-mean analysis, and statistical best practices for player performance modeling.

Build or modify the Rust↔Python FFI using PyO3+maturin. Use for binding builds, smoke tests, and boundary validation workflow.

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 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 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.

Expert guidance for ffuf web fuzzing during penetration testing, including authenticated fuzzing with raw requests, auto-calibration, and result analysis

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.

Extract design assets and metadata from Figma using the Figma REST API.

Extract and analyze Figma designs to create structured design specifications. Use this skill when you need to analyze Figma nodes, extract design properties (layout, spacing, typography), classify components using Atomic Design principles, and generate design specification documents that can be used for implementation.

figma-design-extraction

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.

Analyzes Figma designs and generates implementation-ready PRDs with detailed visual specifications. Use when user provides Figma link or uploads design screenshots. Requires Figma MCP server connection.

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.

Standardize Figma-to-code workflow using Figma MCP - always get_design_context first, then screenshot, use project tokens not hardcoded values, validate 1:1 parity

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.

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.

File Organization Standards Skill

[PROJECT] file and directory structure conventions and enforcement

file-restructurer

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.

Organizes or restructures files and directories according to a specified hierarchy or categorization scheme. Analyzes existing structures, creates new directory trees, intelligently moves files based on content and naming patterns, and verifies the final organization.

Use when Codex needs to inspect or modify files via the local Python filesystem MCP server running at `servers/filesystem`.

Ingest SEC EDGAR filings (10-K, 10-Q, 8-K) via official API with source tracking and pgvector storage