ai-engineering-fluency: Skill for Claude Code

Load Cache Data Skill

Use --json for output; don't pretty-print or write extra files. The default output omits session titles, prompt excerpts, workspace paths, repository URLs, and cache file paths. Never use --include-sensitive unless the task explicitly requires those fields.

This skill helps you access and inspect the AI Engineering Fluency's local session file cache. The cache stores pre-computed statistics for session files to avoid re-processing unchanged files.

Overview

The extension keeps a cache of session file statistics in memory and persists it to a snapshot file in its globalStorage directory (cache_prod.snapshot.json, or cache_dev.snapshot.json in the Extension Development Host). This cache contains:

• Token counts (total and per-model)
• Interaction counts
• Model usage breakdowns
• File modification times (for cache validation)
• Usage analysis data (tool calls, mode usage, context references)

When to Use This Skill

Use this skill when you need to:

• Inspect cached session file data
• Debug cache behavior or validation logic
• Understand what data is being cached
• Work with real cached data for testing or development
• Iterate on features that rely on cached statistics

Cache Structure

The snapshot file is an envelope ({ schemaVersion, cacheVersion, cacheId, generatedAt, entryCount, entries }) whose entries map is keyed by the absolute session file path. Each entry contains (abridged; see SessionFileCache in src/types.ts):

interface SessionFileCache {
  tokens: number;                      // Total token count
  interactions: number;                // Number of interactions
  modelUsage: ModelUsage;              // Per-model token breakdown
  mtime: number;                       // File modification timestamp
  usageAnalysis?: SessionUsageAnalysis; // Detailed usage statistics
  subAgentCalls?: number;               // Sub-agent/delegation tool calls (absent when 0)
}

interface ModelUsage {
  [model: string]: {
    inputTokens: number;
    outputTokens: number;
  };
}

interface SessionUsageAnalysis {
  toolCalls: ToolCallUsage;            // Tool usage statistics
  modeUsage: ModeUsage;                // Mode distribution
  contextReferences: ContextReferenceUsage; // Context reference counts
  mcpTools: McpToolUsage;              // MCP tool usage
}