cc-crossbeam

Local demo: City-side ADU plan review. Point this at a plan binder (PDF or pre-extracted PNGs) and a city name. It reviews the plans sheet-by-sheet against state and city code, then generates a draft corrections letter. Fire-and-forget — no human-in-the-loop pause. Triggers on: 'Review this ADU plan set for [City]' or 'Run the city review on [path]'.

Local demo: Contractor corrections analysis and response — two-phase flow with a human-in-the-loop pause. Phase 1 reads the corrections letter, researches codes, views plan sheets, and generates questions for the contractor. The agent STOPS and presents questions to the user. After the user provides answers, Phase 2 generates the full response package (response letter, professional scope, corrections report, sheet annotations). Triggers on: 'Analyze these corrections' or 'Run the contractor flow on [path]'.

City-side ADU plan review — the flip side of adu-corrections-flow. Takes a plan binder PDF + city name, reviews each sheet against code-grounded checklists, checks state and city compliance, and generates a draft corrections letter with confidence flags and reviewer blanks. Coordinates three sub-skills (california-adu for state law, adu-city-research OR a dedicated city skill for city rules, adu-targeted-page-viewer for plan extraction). Triggers when a city plan checker uploads a plan binder for AI-assisted review.

Operations manual for the CrossBeam ADU Permit Assistant. Teaches AI agents how to operate the deployed system — trigger flows, check status, read results, navigate the UI, and query the database.

Generate 2-minute product demo videos for technical projects (GitHub repos, APIs, technical products). Runs parallel build options with structured critic review. Use when demoing code, explaining architecture, or creating explainer videos.

Analyzes ADU permit corrections letters — the first half of the corrections pipeline. Reads the corrections letter, builds a sheet manifest from the plan binder, researches state and city codes, views referenced plan sheets, categorizes each correction item, and generates informed contractor questions. This skill should be used when a contractor receives a city corrections letter for an ADU permit. It coordinates three sub-skills (california-adu for state law, adu-city-research for city rules, adu-targeted-page-viewer for plan sheet navigation) to produce research artifacts and a UI-ready questions JSON. Does NOT generate the final response package — that is handled by adu-corrections-complete after the contractor answers questions. Triggers when a corrections letter PDF/PNG is provided along with the plan binder PDF.

City-side ADU plan review — the flip side of adu-corrections-flow. Takes a plan binder PDF + city name, reviews each sheet against code-grounded checklists, checks state and city compliance, and generates a draft corrections letter with confidence flags and reviewer blanks. Coordinates three sub-skills (california-adu for state law, adu-city-research OR a dedicated city skill for city rules, adu-targeted-page-viewer for plan extraction). Triggers when a city plan checker uploads a plan binder for AI-assisted review.

Extracts construction plan PDFs into page PNGs, reads the sheet index to build a sheet-to-page manifest, and enables targeted viewing of specific sheets. This skill should be used when a corrections letter references specific plan sheets (e.g., "Sheet A3", "Detail 2/S3.1") and those sheets need to be located and analyzed within the PDF binder. Much faster than full plan extraction — builds the sheet manifest in under 2 minutes, then individual sheet lookups are instant. Triggers when a plan PDF needs to be navigated by sheet reference, or when the corrections interpreter needs to look at specific pages.

This skill extracts construction PDF plan binders into agent-consumable formats. It should be used when a contractor or homeowner provides a PDF binder of construction plans (site plans, floor plans, structural drawings, Title 24 reports) that needs to be parsed for permit review, corrections response, or plan check analysis. Produces three outputs: page PNGs for vision analysis, structured markdown per page via vision extraction, and a JSON manifest for routing.

California state-level ADU and JADU rules from the HCD ADU Handbook (Jan 2025) and 2026 Addendum. Covers Government Code §§ 66310-66342 including setbacks, height, size, parking, permitting, fees, and ownership. Use this skill for any California ADU question about state requirements.

Formats a draft corrections letter (markdown) into a professional PDF. Single-purpose formatting sub-agent — no research. Receives markdown from the research agent, generates a styled PDF using the document-skills/pdf primitive, and returns a screenshot for QA. If the main agent finds issues in the screenshot, it will re-invoke this skill with fix instructions.

California state-level ADU and JADU rules from the HCD ADU Handbook (Jan 2025) and 2026 Addendum. Covers Government Code §§ 66310-66342 including setbacks, height, size, parking, permitting, fees, and ownership. Use this skill for any California ADU question about state requirements.

City-level ADU regulations for Placentia, California. This skill should be used when answering ADU questions specific to Placentia — local ordinance provisions, development standards, permit process, fees, fire requirements, zoning, and anything that differs from or adds to California state ADU law. This skill layers on top of the california-adu state law skill. Load state law first, then use this skill for Placentia-specific requirements.

This skill enables AI video generation from images AND text-to-speech voiceover generation using Fal.ai's API. Use this skill when the user asks to (1) generate videos from images (image-to-video), or (2) generate voiceovers/narration from text (text-to-speech via ElevenLabs). Works seamlessly with the nano-banana skill for image-to-video workflows. IMPORTANT: Check references/ for latest models and pricing - AI models change frequently.

Researches city-level ADU regulations, municipal codes, and standard details for any California city. This skill supports three research modes — Discovery (WebSearch to find key URLs), Targeted Extraction (WebFetch to pull content from discovered URLs), and Browser Fallback (Chrome MCP for cities with difficult websites). When used standalone, run all three modes sequentially. When invoked by an orchestrator (e.g., adu-corrections-flow), run in the specified mode only. Triggers on city-specific ADU questions, corrections letter items referencing municipal code, or when the California ADU state-level skill indicates a question requires local jurisdiction rules.

Generates the final response package for ADU permit corrections — the second half of the corrections pipeline. This skill should be used after adu-corrections-flow has produced its analysis files and the contractor has answered questions. It reads the research artifacts (categorized corrections, state law findings, city research, sheet observations) plus contractor answers, and produces four deliverables — a response letter to the building department, a professional scope of work, a corrections status report, and per-sheet annotations. Triggers when a session directory contains corrections analysis files and a contractor_answers.json has been provided. This skill runs as a cold start — it has no conversation history from the analysis phase and relies entirely on the file artifacts.

Interprets ADU (Accessory Dwelling Unit) permit corrections letters from California city building departments. This skill should be used when a user provides a corrections letter (PDF, PNG, or image) from a plan check review and needs to understand what each correction means, what code is being cited, and what the contractor needs to do to fix it. Triggers on tasks involving permit corrections, plan check comments, building department review letters, or ADU compliance questions.

City-level ADU regulations for Buena Park, California. This skill should be used when answering ADU questions specific to Buena Park — local ordinance provisions, development standards, permit process, fees, fire (OCFA) requirements, zoning, and anything that differs from or adds to California state ADU law. This skill layers on top of the california-adu state law skill. Load state law first, then use this skill for Buena Park-specific requirements.

Researches city-level ADU regulations, municipal codes, and standard details for any California city. This skill supports three research modes — Discovery (WebSearch to find key URLs), Targeted Extraction (WebFetch to pull content from discovered URLs), and Browser Fallback (Chrome MCP for cities with difficult websites). When used standalone, run all three modes sequentially. When invoked by an orchestrator (e.g., adu-corrections-flow), run in the specified mode only. Triggers on city-specific ADU questions, corrections letter items referencing municipal code, or when the California ADU state-level skill indicates a question requires local jurisdiction rules.

Claude Code documentation expert. This skill should be used when the user asks questions about Claude Code features, settings, hooks, skills, MCP servers, keyboard shortcuts, IDE integrations, Agent SDK, Claude API, or Anthropic SDK. Invoke with /cc-guide followed by a question. Examples: "/cc-guide how do hooks work", "/cc-guide what keyboard shortcuts are available", "/cc-guide how do I set up agent teams".

This skill converts planning docs and specs into phase-based task structures and prompts for long-running Claude agents. Use when setting up a multi-session agent workflow or breaking down a spec into phases with verification checkpoints.

This skill enables image generation and editing using Google's Gemini Nano Banana models. Use this skill when the user asks to generate images from text prompts, edit existing images, or modify pictures. Supports text-to-image generation, image editing with prompts, and multi-image reference for consistency.

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

Expert guide for ShadCN UI component library with Next.js. Use when working with ShadCN/UI projects including (1) Initial setup and configuration, (2) Adding and customizing components, (3) Theming and styling patterns, (4) Avoiding common mistakes like hardcoding styles instead of using variants/design tokens. Critical for maintaining consistent, reusable component patterns instead of one-off hardcoded implementations.