Skill UI

This skill enables splitting extracted text into optimized chunks for LLM context windows or RAG ingestion pipelines. It supports configurable chunk sizes, overlap settings, and various chunker types including text, markdown, YAML, and semantic splitting. Users can utilize token-based sizing for specific models or standalone commands for pre-existing text. Ideal for preparing documents for vector stores or summarization tasks.

Learn how to configure xberg's --format and --content-format flags to optimize document extraction for different consumers. Covers LLM context, RAG indexing, JSON parsing, and token reduction strategies for efficient data pipelines.

This skill accesses DEX market data across eight EVM chains including Ethereum and Base. It prepares optimal swap routes and generates unsigned transaction details for user wallets. It never signs or moves funds, requiring explicit user confirmation before execution. Ideal for analyzing token prices, chart data, and executing secure decentralized exchanges trades without private key exposure.

This skill ensures AI models generate complete, unabridged code and files without placeholders, TODOs, or skipped sections. It enforces strict completeness for deliverables like full implementations or exhaustive lists. It prevents shortcuts like '...' or descriptions instead of code, ensuring every requested item is fully realized within token limits.

Install, check, restyle, and remove the agy-powerline statusline for Antigravity CLI. Shows model, quotas, reset times, context window, git status, and tokens.

This tool provides a unified cost view for AI agents like Claude Code, Codex, and Grok. It reads local logs to calculate spend, token usage, and cache hit ratios per provider and model. It flags unpriced models and supports filtering by time range, project, and provider. Output can be JSON or Markdown. All data stays local, ensuring privacy. Ideal for auditing AI usage costs and comparing provider pricing.

Calculate the cost per million tokens for running AI models locally on your own hardware like Ollama or llama.cpp. It factors in electricity prices, hardware costs, power consumption, and generation speed to determine the break-even point against hosted API models. Useful for deciding whether to deploy models locally or use cloud services based on actual usage and financial constraints.

This skill enables publishing HTML files or static folders to a permanent public URL via a single curl request without account registration. It assigns a unique slug and provides a token for updates. Ideal for sharing reports, prototypes, or docs quickly. Supports unattended agent workflows. Note: Static files only, no server-side logic.

Checks WCAG 2.2 contrast between project color tokens in light and dark themes, then suggests the closest passing color that preserves hue.