Estimates implementation time for web development tasks (frontend and/or backend) by analyzing the existing codebase and calibrating for an AI coding agent as executor — not a human developer. Use when the user asks about effort, sizing, or feasibility: 'how long', 'how much work', 'estimate this', 'what is the effort', 'breakdown this task', 'can we do this in X days', 'is this a big task', 'how complex is', 'what's involved in', 'fits in the sprint', 'rough sizing', 't-shirt size', 'story points'. Also use when the user describes a feature and implicitly wants to know scope — e.g. 'we need to add X to the app', 'thinking about building Y', 'is this feasible by Friday'. Supports batch estimation from any structured source (BMAD output, spec folders, PRDs, backlogs, task lists) — use when the user mentions 'estimate the stories', 'estimate the epic', 'scan the backlog', 'estimate all tasks', 'estimate the specs', or points to a folder of task/story/spec files.

Port the visual theme and styling from a live website to a React/Tailwind CSS project. Extracts colours, typography, spacing, and component styles — via agent-browser automation, manual inspection, curl/wget, or direct source reading — writes structured documentation and all artifacts under .context/artifacts/{website}/ with timestamps, applies findings as Tailwind v4 CSS tokens, then verifies by visually diffing the original site against the local or deployed version. Use when cloning a brand, replicating a design system, matching a reference site, migrating visual identity, copying a style guide, or porting a theme from any live URL into a React codebase.

Use this skill to refactor, design, or review application architecture. Trigger it when discussing clean architecture, separating business logic from UI, or cross-platform/WASM development. This skill enforces the 'Headless Core & Passive View' pattern, it proactively refactors logic out of the UI, creates platform-agnostic Core interfaces, and ensures the View is a 'Humble Object' that only reflects state.

Build real-time voting and polling systems with PubNub

Deliver real-time sports scores, play-by-play, and scoreboards with PubNub

Angular patterns — standalone components, signals, services, dependency injection, reactive forms, and HTTP client. Use when building or reviewing Angular apps, when migrating to standalone components or signals, or when setting up a new Angular project.

Use this skill when the user asks to search or browse a Calibre ebook library. It helps find books by title/author/topic, locate file paths, and search inside EPUB/AZW3 text for quotes or passages. Do not use this skill for conversion, metadata editing, downloads, recommendations, or non-Calibre sources.

Generate music using ElevenLabs Music API. Use when creating instrumental tracks, songs with lyrics, background music, jingles, or any AI-generated music composition. Supports prompt-based generation, composition plans for granular control, and detailed output with metadata.

Generate, review, and curate eval scenarios for Tessl skills. Handles scenario generation, bleeding/leaking detection, criteria quality checks, coverage gap analysis, and score-driven iteration. Use when creating test cases or test scenarios for a skill, evaluating or assessing skill quality, running evals or evaluations, reviewing existing evals, expanding eval coverage, or skill testing.

Scaffold the `jbaruch/coding-policy` gh-aw PR review workflows into a consumer repository: copies the packaged paired workflow templates (OpenAI + Anthropic reviewers), compiles them with `gh aw`, and opens a PR. After merge, every pull request in the repo is reviewed against the latest published `jbaruch/coding-policy` rules by the reviewer whose family differs from the PR's declared author model — avoiding self-review bias per `rules/author-model-declaration.md`. Use when the user wants to add, install, enable, scaffold, set up, or wire up an automated policy review / PR reviewer / coding-policy CI reviewer in a consumer repo. Also use to upgrade, update, refresh, or pull the latest reviewer templates into a consumer repo that already has the scaffold installed — the skill switches to override mode in that case.

Structured workflow for shipping code via GitHub pull requests: PR creation, dual-lens automated review (gh-aw for `rules/*.md` compliance + Copilot for doc accuracy and cross-step consistency), merge, and branch cleanup. Covers readiness checks, version reasoning, review polling, feedback handling, and post-merge verification. Use when the user wants to open a pull request, ship code, merge a branch, or handle post-merge cleanup on GitHub.