القائمة
Reference for Splitrail's core data types. Use when working with ConversationMessage, Stats, DailyStats, or other type definitions.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| 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.
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.