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Guide for optimizing MSBuild build parallelism and multi-project scheduling. Only activate in MSBuild/.NET build context. USE FOR: builds not utilizing all CPU cores, speeding up multi-project solutions, evaluating graph build mode (/graph), build time not improving with -m flag, understanding project dependency topology. Note: /maxcpucount default is 1 (sequential) — always use -m for parallel builds. Covers /maxcpucount, graph build for better scheduling and isolation, BuildInParallel on MSBuild task, reducing unnecessary ProjectReferences, solution filters (.slnf) for building subsets. DO NOT USE FOR: single-project builds, incremental build issues (use incremental-build), compilation slowness within a project (use build-perf-diagnostics), non-MSBuild build systems. INVOKES: binlog MCP server tools (expensive_projects, expensive_targets, project_target_times); falls back to dotnet build -m, dotnet build /graph, binlog replay + grep.

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Guide for modernizing and migrating MSBuild project files to SDK-style format. Only activate in MSBuild/.NET build context. USE FOR: converting legacy .csproj/.vbproj with verbose XML to SDK-style, migrating packages.config to PackageReference, removing Properties/AssemblyInfo.cs in favor of auto-generation, eliminating explicit <Compile Include> lists via implicit globbing, consolidating shared settings into Directory.Build.props. Indicators of legacy projects: ToolsVersion attribute, <Import Project="$(MSBuildToolsPath)">, .csproj files > 50 lines for simple projects. DO NOT USE FOR: projects already in SDK-style format, non-.NET build systems (npm, Maven, CMake), .NET Framework projects that cannot move to SDK-style. INVOKES: dotnet try-convert, upgrade-assistant tools.

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Diagnose MSBuild build performance bottlenecks using binary log analysis. Only activate in MSBuild/.NET build context. USE FOR: identifying why builds are slow by analyzing binlog performance summaries, detecting ResolveAssemblyReference (RAR) taking >5s, Roslyn analyzers consuming >30% of Csc time, single targets dominating >50% of build time, node utilization below 80%, excessive Copy tasks, NuGet restore running every build. Covers timeline analysis, Target/Task Performance Summary interpretation, and 7 common bottleneck categories. Use after build-perf-baseline has established measurements. DO NOT USE FOR: establishing initial baselines (use build-perf-baseline first), fixing incremental build issues (use incremental-build), parallelism tuning (use build-parallelism), non-MSBuild build systems. INVOKES: binlog MCP server tools (overview, errors, search, items, properties); falls back to dotnet msbuild binlog replay + grep/cat when the MCP is unavailable.

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Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.

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This guide covers essential PDF processing operations using Python libraries and command-line tools. For advanced features, JavaScript libraries, and detailed examples, see reference.md. If you need to fill out a PDF form, read forms.md and follow its instructions.

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Write and improve prompts for Qwen-Image-2.1, Alibaba's open-weight image generation and editing model. Use whenever the user wants to generate or edit images with Qwen-Image / Qwen-Image-2.1 / Qwen-Image-Edit, asks for help prompting any Qwen image model, needs readable text rendered inside an image (posters, signs, UI mockups, infographics), wants to combine several reference images into one, or asks about aspect ratios, styles, or camera settings for Qwen image generation — even when they are only choosing an image model for a text-heavy graphic and have not named the model yet.

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Rank multiple design solutions and explain why. Separate personal preference from quality judgment. Use when comparing design options, evaluating competing approaches, or making design decisions with clear reasoning.

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Draw from architecture, fashion, music, food, and industrial design to expand your design taste range. Use when seeking inspiration beyond digital, building diverse reference sets, or expanding creative vocabulary.

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Inspect native RGB, depth, confidence, calibration, and poses to make finite, source traceable reference points and surface measurements.

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How to migrate the tdmcp Codex Desktop bundle from legacy .dxt to .mcpb (MCP Bundle) and keep it building — covers the manifest schema (verify against the installed packer, never hardcode), the build-dxt.mjs packer/zip-fallback flow, the npm scripts, and the full .dxt→.mcpb reference sweep across docs and scripts. Use when packaging or migrating the tdmcp desktop bundle.

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Authoritative reference for submitting tdmcp to the Anthropic Connectors Directory as a Codex Desktop Extension (MCPB). Use whenever drafting, checking, or fixing the submission — it defines the two submission paths, why tdmcp is a Desktop Extension (never a remote connector), every form field, the rejection-causing gates, and the local-only compliance story. Read this before writing any submission deliverable.

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Verification methodology and gate checklist for the tdmcp Connectors Directory submission — run the docs build, build and inspect the .mcpb bundle, sweep for stale .dxt references, and cross-check the form-answer draft against the real requirements. Use to validate the submission package before a human submits, by executing commands and quoting evidence, not by trusting that work was done.

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Search, scrape, and interact with the web via the Firecrawl CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, scrape a webpage, grab content from a URL, get data from a website, crawl documentation, download a site, or interact with pages that need clicks or logins. Also use when they say "fetch this page", "pull the content from", "get the page at https://", or reference external websites. This provides real-time web search with full page content and interact capabilities — beyond what Claude can do natively with built-in tools. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.

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Turn one reference image into a cleaned, scaled 3D asset: your own image-to-3D ComfyUI workflow makes the mesh, Blender decimates it to a poly budget, fixes scale, origin and material, and exports a .glb. Use for "image to 3D", "make a 3D model from this picture", "photo to glb".

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Prepare a project for open sourcing: a sanitized fork with secrets and internal references stripped, a sanitizer verdict, README and LICENSE, then a new PRIVATE GitHub repo created and pushed only after GO. The playbook never makes the repo public. Use for "open source this project", "make a sanitized fork", "prepare a public release".

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BDB local-first long-term memory engine (memB). Use when querying, remembering, or adapting preferences, code architectures, and developer patterns across tasks.

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Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.

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Turn a real document (PDF, PPTX, DOCX, Keynote export, slide deck, proposal, whitepaper, report) into a finished AI-generated video using the Ozor MCP. Use this skill whenever the user attaches, uploads, references, or points to a document file and wants a video from it — e.g. 'make a video from this pitch deck', 'turn this PDF into a video', 'video from my proposal.docx', 'generate a video from this PowerPoint', 'create a video from this report', 'this whitepaper → video'. This skill runs the document-to-video pipeline: analyze_document → present the plan to the user → update_plan if needed → generate_from_plan → export_video → wait_for_export → get_embed_code. It always uses the plan-based flow so slide visuals are preserved. Do NOT use this skill for plain-text creative briefs (use ozor-generate) or for URLs/landing pages (use ozor-url-to-video).

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Implement, review, or improve accessibility in iOS/macOS apps with SwiftUI and UIKit. Use when adding VoiceOver support with accessibility labels, hints, values, and traits; when grouping or reordering accessibility elements; when managing focus with @AccessibilityFocusState; when supporting Dynamic Type with @ScaledMetric; when building custom rotors or accessibility actions; when auditing a11y compliance; or when adapting UI for assistive technologies and system accessibility preferences.

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Translate Figma designs into production-ready SwiftUI code with 1:1 visual fidelity using the Figma MCP workflow. Trigger when the user provides Figma URLs or node IDs and wants iOS/SwiftUI implementation, asks to implement a design or component from Figma for an iOS app, or references Figma selections in the context of an Xcode/SwiftUI project. Also trigger when user asks to inspect Figma designs for iOS planning, fetch design tokens for SwiftUI, or convert Figma assets for Xcode. Requires a working Figma MCP server connection. Do NOT trigger for web/React implementations.

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Generate a polished frontend reference screenshot through a configurable GPT-image-2-compatible generations endpoint, save and show versioned previews inside the project, revise selected previews through a configurable /images/edits endpoint, and reproduce only the user-approved design as functional frontend code with high visual fidelity. Use when Codex is asked to design, build, restyle, or recreate a web page, application screen, dashboard, landing page, or UI component through an image-first workflow, design approval loop, screenshot-driven implementation, pixel matching, or a 1:1 frontend recreation.

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Generates IEEE-format LaTeX technical reports from project requirements and codebase evidence, using academic prose, pseudocode-only explanations, BibTeX references, and IEEEtran formatting.

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Set up and run the full RLHF pipeline (SFT, reward model training, RL from reward model) using the Tinker API. Use when the user wants to do RLHF, train a reward model, or run the full preference-based RL pipeline.

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Reference for Tinker SDK types — Datum, ModelInput, TensorData, SamplingParams, response types, error types, and helper functions. Use when the user needs to build training data, construct model inputs, understand response objects, or handle errors.

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