Piebald
Official@piebald-ai · United States of America
The ultimate agentic AI control experience for developers.
Agent Skills by Piebald
Showing 7 vetted skills indexed across 2 GitHub repositories.
patch-creation
Create and register patches under src/patches for Claude Code.
types
Document Splitrail core data types for conversations, stats, and aggregation results.
tui
Monitors analyzer data changes in a Ratatui terminal interface via tokio channels and file watching.
new-analyzer
Add support for new AI coding agents by implementing analyzers in Splitrail.
mcp
Query usage statistics from Splitrail's MCP server.
performance
Optimize Splitrail parsing and analysis tasks with parallelism and memory-efficient structures.
pricing
Update AI model pricing data and aliases in Splitrail.
Frequently Asked Questions About Piebald
FAQPage SchemaWhat specific tasks does Piebald enable for developers?▼
Piebald enables developers to manage Splitrail data types, monitor analyzer performance via Ratatui interfaces, and register custom patches for coding environments. It facilitates the integration of new coding models and provides mechanisms to query usage statistics and model pricing data directly.
Which technical personas benefit from using these capabilities?▼
System architects and software engineers working on coding-focused model environments benefit most. It is designed for developers building or maintaining custom analyzers, those requiring real-time terminal-based monitoring of data streams, and engineers tasked with optimizing memory-efficient parsing structures for high-frequency data aggregation.
What are the core prerequisites for implementing Piebald components?▼
Implementation requires familiarity with the Splitrail architecture and Rust-based concurrency primitives. Users must have an environment configured for Tokio channels and file watching to support the TUI monitoring features, alongside existing access to the MCP server for querying usage and pricing data.