Skill UI

This expert simulates an experienced design system author for Ant Design, specializing in structured, enterprise-focused, data-dense web applications. It generates comprehensive, implementation-ready guidelines covering design tokens, component anatomy, interaction states, accessibility requirements (WCAG 2.2 AA), and content standards, ensuring maximal clarity and consistency for development and design teams.

This comprehensive guide provides expert knowledge on implementing structured data and schema markup using schema.org standards. Learn how to correctly use JSON-LD to help search engines understand your content, enabling rich results like star ratings, FAQs, and product details. It covers best practices, common schema types (Article, Product, FAQPage), and essential validation methods for maximizing search visibility.

A detailed technical workflow for inspecting complex 3D animation, rigging, and motion states within Blender. This skill moves beyond visual inspection by extracting structured data—such as bone transformations, world-space bounding boxes, ground contacts, and axis conventions—to accurately diagnose issues like foot sliding, rotation errors, or retargeting mismatches in professional animation pipelines.

This skill generates comprehensive Entity Relationship Diagrams (ERDs) and database schemas as D2 source code from an existing Entity Framework Core codebase. It analyzes DbContexts, DbSet declarations, Fluent API mappings, and migrations to accurately visualize tables, columns, primary/foreign keys, relationships (including many-to-many joins), owned types, and constraints. The output is a structured .d2 file, suitable for rendering into SVG or PNG, helping developers document the persistence model.

A comprehensive guide on embedding before-and-after screenshots directly into pull request descriptions. This skill helps reviewers visualize UI changes, layout adjustments, and data visualizations instantly, without needing to check out the branch. Includes best practices for image sizing, structured Markdown patterns, and specific API/upload guidance for Azure DevOps and GitHub.

This skill generates robust JSON-LD structured data markup for various web components, including blogs, FAQs, tools, and SaaS pages. By implementing standard Schema.org types (WebSite, Article, FAQPage, etc.), you can significantly improve your SEO, boost click-through rates (CTR), and provide clear context to both search engines and AI systems. Includes implementation guidance for modern frameworks like Next.js.

This skill captures and persists critical user decisions, project constraints, and architectural choices across multiple sessions and agents. It saves this context into a structured memory database (`mdbase`), ensuring that future development steps or agents can retrieve the original intent without re-deriving it from scratch. Ideal for documenting project rules, tech stacks, and design rationale.

This tool empowers users to query, filter, and aggregate logs from Datadog directly from the command line using the Composio CLI. It bypasses the graphical UI, providing structured JSON output for complex analysis, cross-service correlation, and automated reporting. Ideal for deep dive investigations, tracking latency regressions, or building scheduled operational digests.

This toolkit provides deterministic, programmatic capabilities for working with PDF documents. Users can extract structured data like text and tables, merge multiple PDFs, split documents by page ranges, fill out PDF form fields using JSON data, or generate entirely new PDFs from scratch using libraries like ReportLab. It is designed for explicit, byte-level operations, making it ideal for automation workflows that require precise document manipulation.

This skill reads the contents of a UTF-8 text file and outputs the raw bytes verbatim to stdout. It is designed for meta-skills that require round-tripping an artifact through disk for user inspection or manual editing between steps. Unlike standard file readers that prepend line numbers, this tool preserves the original structure, making it ideal for structured data formats like YAML, scripts, or SRT files that need to be accurately parsed downstream.

Pi Agent is a highly extensible, minimal terminal coding harness designed for building sophisticated AI applications and complex workflows. It enables developers to integrate custom AI providers, local models (via llama.cpp router), skills, and TUI components. Use it for everything from basic command execution and data parsing to advanced orchestration, web search, and structured interaction via SDK, RPC, or JSON event streams.

This advanced tool surfaces critical, often unrecorded, evidence of human-AI collaboration during development sessions. It analyzes git diffs and conversational context across multiple layers to classify the signal level (HIGH/MEDIUM/LOW), measure technical complexity, detect decision forks, and quantify the specific contribution of the AI model, providing structured data for post-session retrospectives and accountability.