Browse skills

Use fff (Fast File Finder) — a blazing-fast file search tool built in Rust with Node.js bindings, optimized for AI agents and Neovim integration. Supports fuzzy matching, regex, gitignore-aware filtering, and sub-millisecond search across large codebases. Use when tasks involve fast file discovery, AI agent tooling, or Neovim file navigation.

Use Originality.ai API to detect AI-generated content and check for plagiarism simultaneously. Use when: SEO content audits, freelancer content verification, editorial review pipelines, originality checks.

You are an expert in Outlines, the Python library for reliable structured text generation with LLMs. You help developers generate guaranteed-valid JSON, regex-matching text, and grammar-constrained output from open-source models — using finite state machine guided generation that constrains the token sampling process to produce only valid output on the first try.

Assists with finding security vulnerabilities in web applications using OWASP ZAP. Use when configuring automated scans, writing scan policies, integrating security scanning into CI/CD pipelines, or analyzing results for OWASP Top 10 vulnerabilities like XSS, SQL injection, and CSRF. Trigger words: owasp zap, security scan, vulnerability scanner, penetration testing, zap-baseline, active scan, passive scan.

HashiCorp Packer for building automated machine images. Use when the user needs to create AMIs, Docker images, or GCP images using HCL templates with provisioners for consistent, reproducible infrastructure images.

Accept payments with Paddle as merchant of record. Use when a user asks to add subscription billing without handling tax compliance, accept international payments, implement a payment system where Paddle handles VAT/sales tax, or build a SaaS billing system.

PandasAI enables natural language queries on pandas DataFrames using LLMs. Learn to ask questions in plain English, generate charts, clean data, and integrate with OpenAI and local models for conversational data analysis.

Expert guidance for Pandera, the Python library for validating pandas and Polars DataFrames with expressive schemas. Helps developers define data contracts, validate data pipelines, and catch data quality issues before they corrupt downstream systems.

Build multiplayer and collaborative apps with PartyKit. Use when a user asks to build real-time collaboration features, create multiplayer experiences, add live cursors, build collaborative editing, create real-time voting or polls, sync state across clients, or build WebSocket servers on the edge. Covers PartyServer definition, client connections, state management, hibernation, and deployment to Cloudflare.

Build and extend 3D building editor apps using Pascal Editor's architecture (React Three Fiber + Zustand scene graph). Use when: building 3D architectural tools, creating BIM-like editors, extending Pascal Editor with custom features, building floor plan generators.

Comprehensive passive reconnaissance covering WHOIS, DNS history, reverse IP, SSL certificates, Google dorks, and Wayback Machine enumeration. Use when: initial target profiling without active scanning, stealth recon where no direct target contact is desired, or building a complete picture of a target's infrastructure from public data alone.

Add authentication to Express with Passport.js. Use when implementing login with Google/GitHub/email, OAuth, session auth, or social login.

Assists with building content management systems using Payload CMS with a code-first approach. Use when defining collections in TypeScript, configuring access control, customizing the admin panel, or integrating with Next.js. Trigger words: payload, payload cms, headless cms, collections, admin panel, content management, payload fields.

Achieve PCI DSS compliance for handling payment card data — scoping, controls, and SAQ selection. Use when storing, processing, or transmitting payment card data, building e-commerce security, or achieving payment processing compliance.

Extract text, tables, metadata, and structured data from PDF files. Use when a user asks to read a PDF, parse a PDF, extract data from a PDF, summarize a PDF document, pull tables from a PDF, or convert PDF content to structured formats like JSON or CSV. Handles single and multi-page documents, scanned PDFs, and PDFs with complex table layouts.

Combine multiple PDFs into one or split a PDF into separate files. Use when a user asks to merge PDFs, combine PDF files, join documents together, split a PDF into pages, extract pages from a PDF, or separate a PDF into parts. Supports page range selection and custom ordering.

Extract text from scanned PDFs using optical character recognition. Use when a user asks to OCR a PDF, read a scanned document, extract text from an image PDF, digitize a scanned file, convert a scanned PDF to text, or read text from a photograph of a document. Supports multiple languages and handles low-quality scans.

Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when a user asks to fine-tune a language model, train a custom LLM, adapt a model to their data, use LoRA or QLoRA, fine-tune Llama or Mistral, or train a model on consumer GPUs. Covers PEFT methods for 7B-70B parameter models.

When the user wants to perform visual testing with automated screenshot comparison using Percy by BrowserStack. Also use when the user mentions "percy," "visual testing," "screenshot comparison," "visual diff," "percy snapshot," or "BrowserStack visual." For Storybook-specific visual testing, see chromatic.

Perplexity API for real-time web-search-augmented LLM responses. Use when you need up-to-date information in AI responses, research assistants, fact-checking, current events coverage, or any task requiring knowledge beyond an LLM's training cutoff. Returns cited sources alongside answers.