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Home/Collections/Piebald-AI/splitrail

Piebald-AI/splitrail

DirSkills catalogs 6 skills from this repository, across 4 categories: AI Engineering, Data, Frontend, Quality.

217 stars25 forksView on GitHub
🧩
2h ago

New Analyzer

New Analyzer guides adding support for a new AI coding agent analyzer in Splitrail. Use it when implementing parsing for a tool like Copilot, Cline, or another agent with its own data files.
AI Engineering
21725
⚡
2h ago

Performance

Performance provides guidelines for optimizing Splitrail code. Use it when improving parsing, reducing memory usage, or increasing throughput.
Quality
21725
💲
2h ago

Pricing

Pricing guides updating model cost data in Splitrail. Use it when adding new AI models, aliases, caching rules, or dated pricing overrides.
AI Engineering
21725
🔌
2h ago

Splitrail MCP

Splitrail MCP lets AI assistants query usage statistics, model breakdowns, cost data, and file operation counts through an MCP server. Use it when adding or modifying tools and resources for the interface.
AI Engineering
21725
🖥️
2h ago

TUI

TUI guides Splitrail's terminal interface, live stats updates, and file watching. Use it when changing the TUI, stats display, or real-time update logic.
Frontend
21725
🧩
2h ago

Types

Types is a reference for Splitrail's core data structures. Use it when working with ConversationMessage, Stats, DailyStats, hashing, or daily aggregation.
Data
21725
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