@mohndoe/pi-atlas

A pi extension that turns your session logs into an interactive dashboard — costs, languages, models, projects, tools, and token usage at a glance.

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Features

• Multiple time ranges — Today, Last 7 days, Last 30 days, or All time
• Cost tracking — per-model, per-project, based on real usage costs
• Language breakdown — lines written and edited
• Model analytics — provider-aware model cost, call count, works with local LLMs too
• Project attribution — cost and session count per project directory
• Usage overview — tool call frequency and token breakdown (input, output, cache read/write)
• Cache — SHA-256-gated persists day aggregates; near-instant open on next visits
• Zero dependencies — uses only the pi TUI and the @mohndoe/pi-tui-extras component library

Dashboard

Tabs

• Overview — Cards displaying total cost, sessions count, messages count, active days, average cost per day, total tokens. A bar chart displaying cost overtime. And top language, top model, and top project side by side.
• Languages — Languages ranked by line written.
• Models — Models ranked by cost. Shows providers, calls and cost per model.
• Projects — Projects ranked by cost. Shows session count and cost per project.
• Skills — Skills used ranked by cost. Estimation of what skill invocations cost.
• Usage — Token breakdown (Total, Input, Output, Cache Read, Cache Write) and table of tool usage.

All tabs displayed data correspond to the selected time range (press r to change it). Press left/right arrows to change tabs.

Install

pi install npm:@mohndoe/pi-atlas

Then run /reload in pi (or restart pi). The /atlas command is now available.

Usage

In the pi terminal, type /atlas to open the atlas dashboard. Session data is loaded from ~/.pi/agent/sessions/ -- on first load this may take a moment while JSONL files are parsed. Subsequent opens use a cached snapshot and load instantly.

How it works

~/.pi/agent/sessions/*.jsonl
         │
         ▼ parseFile()        ◄── entry types handled
  ┌──────────────────┐
  │  DayAgg[]         │   per calendar day
  └────────┬─────────┘
           │
           ▼ summarize(days, range)
  ┌──────────────────┐
  │ StatsSummary × 4  │   1d, 7d, 30d, All pre-computed
  └────────┬─────────┘
           │
           ▼
  Tab receives StatsSummary  ──→  Component render

Data sources — pi stores every session as a .jsonl file in ~/.pi/agent/sessions/. Pi Atlas parses entry types: session headers, user messages, assistant messages, tool results, model changes, thinking level changes, compactions, and branch summaries.

Caching — On first open, the sessions directory is scanned and all JSONL files are parsed into DayAgg objects. This aggregate is cached to disk alongside a SHA-256 signature of the directory (file paths, sizes, modification times). On subsequent opens, the cache is reused if the signature matches, making the dashboard appear instantly.

Language detection — Lines are counted by splitting written/edited content on \n. File extensions map to language names via a built-in mapping of 70+ extensions (TypeScript, Python, Rust, Go, etc.).

Cost attribution — Assistant message costs are attributed to all active projects in the session. See ADR-0001 for details.

Development

# Setup
git clone https://github.com/MohnDoe/pi-atlas.git
cd pi-atlas
bun install

# Type check
bun run typecheck

# Test
bun test

# Coverage
bun test --coverage

Architecture decisions

See docs/adr/ for recorded decisions:

• ADR-0001: Global session-project map — cost attribution model
• ADR-0002: Pre-computed summaries — all four time ranges computed at open

A higher-level ARCHITECTURE.md covers module structure and component hierarchy.

Data privacy

Pi Atlas reads session logs from ~/.pi/agent/sessions/. All processing is done locally - no data ever leaves your machine. The cache file is written to ~/.pi/pi-atlas-cache.json and contains aggregated statistics (costs and counts), not message content.

License

MIT