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Found 13 Skills
AI-powered autonomous data extraction that navigates complex sites and returns structured JSON. Use this skill when the user wants structured data from websites, needs to extract pricing tiers, product listings, directory entries, or any data as JSON with a schema. Triggers on "extract structured data", "get all the products", "pull pricing info", "extract as JSON", or when the user provides a JSON schema for website data. More powerful than simple scraping for multi-page structured extraction.
Collect real financial data for any US publicly traded company from free public sources (yfinance). Output structured JSON consumable by downstream financial skills (DCF modeling, comps analysis, earnings review). Handles market data (price, shares, beta), historical financials (income statement, cash flow, balance sheet), WACC inputs, and analyst estimates. Use when users request collect data for ticker, get financials for company, pull market data, gather DCF inputs, or any task requiring structured financial data before analysis. Also triggers on financial data, company data, stock data.
Extract and parse local git commit history into structured JSON format with custom tags ([Why], [What], [Impact]). Use when generating changelogs, creating PR summaries, updating CHANGELOG.md files, or analyzing recent code changes. Parses conventional commits, extracts technical details and business impact, and returns flat JSON to save context tokens and reduce hallucinations during documentation generation.
Instructions for using the ModelMix Node.js library to interact with multiple AI LLM providers through a unified interface. Use when integrating AI models (OpenAI, Anthropic, Google, Groq, Perplexity, Grok, etc.), chaining models with fallback, getting structured JSON from LLMs, adding MCP tools, streaming responses, or managing multi-provider AI workflows in Node.js.
Autonomous multi-page extraction into structured JSON. Use when the user wants website data matching a schema — pricing tiers, product listings — beyond a single-page scrape.
Analyze local or downloaded social video files with the official Gemini API, especially for TikTok/Reels benchmark breakdowns, script decomposition, and structured JSON outputs. Use this when you need video-level analysis beyond metadata, including uploading video files, prompting Gemini 3.1 Pro Preview, and linking results back to source metadata.
Write structured VGL (Visual Generation Language) JSON prompts for Bria's FIBO image generation models. Use this skill when creating detailed image descriptions in JSON format for text-to-image generation, image editing, inpainting, outpainting, background generation, or captioning. Triggers include requests to write structured prompts, create VGL JSON, describe images for AI generation, or work with Bria/FIBO's structured_prompt format. Also use when converting natural language image requests into the deterministic JSON schema required by FIBO models.
Benchmark Jetson LLM/VLM serving performance across vLLM, llama.cpp, and Ollama with structured JSON output.
Production-grade web scraping with automatic anti-bot bypass, structured JSON parsing for 40+ targets, and geo-targeting. Use when the user needs to scrape web pages, extract product data, get search results, or collect structured data from supported e-commerce and search platforms without worrying about getting blocked and when geo targeting is required.
Parse a local or remote FILE (PDF) into markdown or structured JSON with fastCRW. Use when the source is a file on disk — "parse this PDF", "extract text from this document", "read this report", "convert PDF to markdown". Routing rule: URL → use crw-scrape; file on disk → use crw-parse. Step 5 of the crw workflow ladder.
Use to write great prompts for Ideogram (Ideogram 4.0) to generate design-grade images for social media — the image-prompt-craft mini-skill for typography + layout, sibling to nano-banana under the image-prompt router. Run when the user wants an Ideogram / AI image prompt where TEXT and LAYOUT matter: quote cards, carousel covers, posters, logos/wordmark concepts, signage, ads with headlines, or any image that must say words correctly. Reads brand-profile for style/palette. Ideogram's standouts: best-in-class in-image text rendering, structured JSON prompting (bounding boxes, hex palettes), native 2K, transparency, and Layerize Text. Also covers the Ideogram app-editor workflow (Canvas, Magic Fill, Extend, Style References). Honest: review rendered text, disclose AI images and sign with C2PA, never generate real identifiable people or copyrighted characters/IP/logos. The API/connection and the generate -> upload to WoopSocial Media -> attach flow live in tools/integrations/ideogram.md.
Query KIRHA — a dynamic catalogue of authoritative data providers accessible from the command line. USE THIS SKILL whenever a question would be answered better by an authoritative source than by model memory or a generic web search: facts that change over time, provenance or citability, official records or canonical registries, claims to verify or fact-check, current documentation, or whenever accuracy beats guesswork. KIRHA's catalogue grows continuously and coverage is discovered at runtime, so do not assume in advance which domain applies. Prefer this skill over WebSearch when accuracy, freshness, or source-traceability matters. KIRHA returns structured facts from named providers, not scraped page summaries. Trigger EVEN IF the user does not mention KIRHA or "search" — if an authoritative source would answer better, this is the skill.