A well-crafted, self-contained application for analyzing and visualizing Claude Code usage logs. The system reads local JSONL transcript files (written by Claude Code regardless of subscription plan), parses them into a local SQLite database, and surfaces token counts, cost estimates, session histories, and subagent attribution through both a terminal CLI (`python cli.py today` / `stats` / `week`) and a rich single-page web dashboard (`python cli.py dashboard`). The dashboard is served by a stdlib-only Python HTTP server and bundles all HTML/JS/CSS inline, using Chart.js from CDN for visualizations. A companion VS Code extension embeds the same dashboard as a sidebar webview, auto-discovering the Python runtime via a flexible install-mode resolution chain (bundled `.py` sources, Homebrew shim, workspace clone, or explicit path). Architecturally, the code is split into three top-level Python modules—`scanner.py` (JSONL parsing, SQLite schema management, incremental scanning with deduplication by message ID), `cli.py` (CLI dispatch with per-turn cost calculation using a tiered pricing lookup), and `dashboard.py` (HTTP server with an embedded SPA). There are no third-party Python runtime dependencies; the VS Code extension uses TypeScript with minimal Node.js dependencies (only `@vscode/vsce` for packaging). The test suite is comprehensive, covering unit, integration, and HTTP-level scenarios across all three Python modules plus the entire TypeScript extension. A strict version parity test (`test_version.py`) enforces lockstep between the Python constant, the CHANGELOG heading, and the extension's `package.json`. Notable craftsmanship includes: the incremental scan engine that tracks file mtimes and line counts, processes only new/changed lines, and deduplicates streaming events via a conditional unique index on `message_id`; the one-time topic backfill mechanism for schema upgrades that re-reads only title records without touching token totals; and the VS Code extension's server-manager with configurable readiness probes that distinguishes the dashboard's JSON response shape from arbitrary HTTP 200s. The project is actively maintained with frequent releases, a weekly triage automation, and a detailed AGENTS.md that documents non-obvious invariants (streaming dedup, session model priority, cost calculation per-turn).
Claudoscope is a native macOS menu-bar application that serves as an observability and configuration management dashboard for Claude Code, Anthropic's AI coding assistant. It reads local Claude Code session transcripts (JSONL), caches parsed summaries in a GRDB-backed SQLite store, and presents analytics on token usage, cost, cache effectiveness, model distribution, and attribution per skill, MCP tool, or agent. The app also includes a comprehensive configuration linter (100+ rules for security, skills, hooks, routing, hardening, and more), an installer for Claude Code hardening baselines and agent routing stacks, real-time file monitoring via FSEvents, and an optional MCP server that exposes read-only tools for AI-driven querying. It operates as a background agent with a menu bar popover and a full dashboard window. The application is built as a monolithic SwiftUI macOS app with modular service actors, extensive unit tests (60+ test files), and a clean separation of concerns. Key entry points include the session parser, analytics engine, linter service, and installer file operations. It depends on Claude Code's local file structure and specific JSONL schemas, which drives a medium technical drift risk as those formats evolve. The codebase demonstrates high craftsmanship with reusable patterns such as pure analytic functions, atomic configuration writers, and a design token system, making it a strong example of a well-engineered developer tool.