菜单
Reference for Splitrail's core data types. Use when working with ConversationMessage, Stats, DailyStats, or other type definitions.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
Guide for updating model pricing in Splitrail. Use when adding new AI model costs or updating existing pricing data.
Guide for working with Splitrail's MCP server. Use when adding tools, resources, or modifying the MCP interface.
Guide for adding a new AI coding agent analyzer to Splitrail. Use when implementing support for a new tool like Copilot, Cline, or similar.
Performance optimization guidelines for Splitrail. Use when optimizing parsing, reducing memory usage, or improving throughput.
Guide for Splitrail's terminal UI and file watching. Use when modifying the TUI, stats display, or real-time update logic.
基于 SOC 职业分类
| name | types |
| description | Reference for Splitrail's core data types. Use when working with ConversationMessage, Stats, DailyStats, or other type definitions. |
Read src/types.rs for full definitions.
ConversationMessage - Normalized message format across all analyzers. Contains application source, timestamp, hashes for deduplication, model info, token/cost stats, and role.
Stats - Comprehensive usage metrics for a single message including token counts, costs, file operations, todo tracking, and composition stats by file type.
DailyStats - Pre-aggregated stats per date with message counts, conversation counts, model breakdown, and embedded Stats.
Application - Enum identifying which AI coding tool a message came from.
MessageRole - User or Assistant.
local_hash: Deduplication within a single analyzerglobal_hash: Deduplication on upload to Splitrail CloudUse crate::utils::aggregate_by_date() to group messages into daily stats. See src/utils.rs.