tokscale

A high-performance CLI tool and visualization dashboard for tracking token usage and costs across multiple AI coding agents.

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Overview	Models

Daily Summary	Stats

Frontend (3D Contributions Graph)	Wrapped 2025

Run bunx tokscale@latest submit to submit your usage data to the leaderboard and create your public profile!

Overview

Tokscale helps you monitor and analyze your token consumption from:

Logo	Client	Data Location
	OpenCode	~/.local/share/opencode/opencode.db (1.2+, all channels including opencode-stable.db) or/and ~/.local/share/opencode/storage/message/ (legacy/unmigrated)
	Claude Code	~/.claude/projects/ and ~/.claude/transcripts/
	OpenClaw	~/.openclaw/agents/ (+ legacy: .clawdbot, .moltbot, .moldbot)
	Codex CLI	~/.codex/sessions/
	Prime Agent	~/.prime/agent/sessions/ and ~/.prime/agent/session-artifacts/ (RLM child sessions)
	Sakana Fugu	via Codex — ~/.codex/sessions/*.jsonl (model_provider: sakana)
	GitHub Copilot CLI	~/.copilot/otel/*.jsonl (+ COPILOT_OTEL_FILE_EXPORTER_PATH)
	Hermes Agent	$HERMES_HOME/state.db and $HERMES_HOME/profiles/*/state.db (fallback: ~/.hermes/...)
	Gemini CLI	$GEMINI_CLI_HOME/tmp/*/chats/*.json (fallback: ~/.gemini/tmp/*/chats/*.json)
	Cursor IDE	Cursor API export cached at ~/.config/tokscale/cursor-cache/usage*.csv (desktop auto-login or cookie paste; not ~/.cursor)
	Amp (AmpCode)	~/.local/share/amp/threads/
	Codebuff	~/.config/manicode/ (+ manicode-dev, manicode-staging; override via CODEBUFF_DATA_DIR)
	Freebuff	shares ~/.config/manicode/ with Codebuff (same runtime); token usage is estimated from the transcript (no local usage; override via FREEBUFF_DATA_DIR)
	Droid (Factory Droid)	~/.factory/sessions/
	Pi	~/.pi/agent/sessions/ and ~/.omp/agent/sessions/ (Oh My Pi)
	Senpi (OmO Native)	~/.senpi/agent/sessions/ (override via SENPI_CODING_AGENT_DIR)
	Kimchi Coding	~/.config/kimchi/harness/sessions/ (override via KIMCHI_CODING_AGENT_DIR)
	Reasonix	~/.reasonix/stats/*.jsonl (override via REASONIX_STATE_HOME or REASONIX_HOME)
	Kimi CLI / Kimi Code	kimi-cli: ~/.kimi/sessions/ kimi-code: ~/.kimi-code/sessions/ (override via KIMI_CODE_HOME) kimi-work: desktop app-data root (auto-discovered)
	Qwen CLI	~/.qwen/projects/
	Roo Code	~/.config/Code/User/globalStorage/rooveterinaryinc.roo-cline/tasks/ (+ server: ~/.vscode-server/data/User/globalStorage/rooveterinaryinc.roo-cline/tasks/)
	Kilo	~/.config/Code/User/globalStorage/kilocode.kilo-code/tasks/ (+ server: ~/.vscode-server/data/User/globalStorage/kilocode.kilo-code/tasks/)
	Kilo CLI	~/.local/share/kilo/kilo.db
	Mux	~/.mux/sessions/
	Crush	$XDG_DATA_HOME/crush/projects.json (project registry; fallback: ~/.local/share/crush/projects.json)
	Goose	~/.local/share/goose/sessions/sessions.db (+ macOS Application Support, legacy Block/goose paths; override via GOOSE_PATH_ROOT)
	Google Antigravity	Cached via tokscale antigravity sync to ~/.config/tokscale/antigravity-cache/sessions/*.jsonl (live RPC against the local language server)
	Antigravity CLI	~/.gemini/antigravity-cli/conversations/*.db (override the Gemini home via GEMINI_CLI_HOME; local SQLite, read directly — no antigravity sync needed)
	Trae IDE / Trae Solo (international)	Cached via tokscale trae sync to ~/.config/tokscale/trae-cache/sessions/*.json (account-level usage from the official API)
	Warp / Oz	Cached via tokscale warp sync to ~/.config/tokscale/warp-cache/usage.json (aggregate requests and spend only; no token transcripts)
	Grok Build	$GROK_HOME/sessions/*/*/updates.jsonl (fallback: ~/.grok/sessions/*/*/updates.jsonl)
	Zed Agent	~/.local/share/zed/threads/threads.db (macOS: ~/Library/Application Support/Zed/threads/threads.db; Windows: %LOCALAPPDATA%/Zed/threads/threads.db; hosted Zed models only, not external ACP agents)
	Kiro	~/.kiro/sessions/cli/*.json (+ *.jsonl), ~/.local/share/kiro-cli/data.sqlite3 (macOS: ~/Library/Application Support/kiro-cli/data.sqlite3), and Kiro IDE globalStorage snapshots (Kiro/User/globalStorage/kiro.kiroagent; macOS Application Support, Linux ~/.config/Kiro, Windows %APPDATA%\Kiro)
	Cline	VS Code globalStorage tasks (Linux: ~/.config/Code/...; macOS: ~/Library/Application Support/Code/...; Windows: %APPDATA%\Code\...; server: ~/.vscode-server/data/User/globalStorage/saoudrizwan.claude-dev/tasks/) + Cline CLI sessions (first available root, in order: $CLINE_SESSION_DATA_DIR, $CLINE_DATA_DIR/sessions/, $CLINE_DIR/data/sessions/, fallback ~/.cline/data/sessions/; blank/whitespace-only environment values are ignored)
	gajae-code (gjc)	~/.gjc/agent/sessions/ (override via GJC_CODING_AGENT_DIR, GJC_CONFIG_DIR, PI_CONFIG_DIR; $XDG_DATA_HOME/gjc/sessions/ on Linux/macOS)
	Cherry Studio	%APPDATA%\CherryStudio\Data\Agents\.claude\projects\*.jsonl and legacy %APPDATA%\CherryStudio\.claude\projects\*.jsonl (macOS: ~/Library/Application Support/CherryStudio/Data/Agents/.claude/projects/; Linux: $XDG_CONFIG_HOME/CherryStudio/Data/Agents/.claude/projects/; Agent / Claude Code mode transcripts; V2 root preferred, legacy keeps untransferred history)
	Jcode	~/.jcode/sessions/session_*.json + session_*.journal.jsonl sidecars (override via JCODE_HOME)
	MiMo Code	~/.local/share/mimocode/mimocode.db (XDG data dir; SQLite)
	Junie	~/.junie/sessions/*/events.jsonl
	Command Code	~/.commandcode/projects/**/*.jsonl (token usage estimated from transcripts at ~4 chars/token; not persisted on disk)
	ZCode	~/.zcode/cli/db/db.sqlite (v2 usage database) and ~/.zcode/projects/**/*.jsonl (legacy transcripts)
	OpenCodeReview	~/.opencodereview/sessions/**/*.jsonl
	CodeBuddy (CLI, IDE, VS Code plugin)	~/.codebuddy/projects/**/*.jsonl + extension logs
	WorkBuddy	~/.workbuddy/projects/**/*.jsonl + SQLite fallback
	Devin CLI	~/.local/share/devin/cli/sessions.db (SQLite)
	Devin Desktop	ACP events: macOS ~/Library/Application Support/Devin/User/acp-events/; Linux ~/.config/Devin/User/acp-events/; Windows %APPDATA%\Devin\User\acp-events\
	Augment Code (Auggie CLI)	~/.augment/sessions/*.json
	Synthetic	Re-attributed from other sources via hf: model prefix or synthetic provider (+ Octofriend: ~/.local/share/octofriend/sqlite.db)
	DeepSeek Harness	~/.dsh/sessions/**/session.jsonl.zstd (or session.jsonl when written uncompressed; override via DSH_HOME)
	MiniMax Code	~/.config/tokscale/headless/mcode/*.jsonl (headless capture of mcode exec --output-format stream-json; override via TOKSCALE_HEADLESS_DIR)
	fx	~/.fx/sessions/<sessionId>/usage-v2.json (per-session aggregates)

Get real-time pricing calculations using 🚅 LiteLLM's pricing data, with support for tiered pricing models and cache token discounts.

Why "Tokscale"?

This project is inspired by the Kardashev scale, a method proposed by astrophysicist Nikolai Kardashev to measure a civilization's level of technological advancement based on its energy consumption. A Type I civilization harnesses all energy available on its planet, Type II captures the entire output of its star, and Type III commands the energy of an entire galaxy.

In the age of AI-assisted development, tokens are the new energy. They power our reasoning, fuel our productivity, and drive our creative output. Just as the Kardashev scale tracks energy consumption at cosmic scales, Tokscale measures your token consumption as you scale the ranks of AI-augmented development. Whether you're a casual user or burning through millions of tokens daily, Tokscale helps you visualize your journey up the scale—from planetary developer to galactic code architect.

Contents

• Overview
  • Why "Tokscale"?
• Features
• Installation
  • Quick Start
  • Prerequisites
  • Development Setup
  • Building the Native Module
• Usage
  • Basic Commands
  • TUI Features
  • Filtering by Platform
  • Date Filtering
  • Pricing Lookup
  • Social
  • Autosubmit
  • Cursor IDE Commands
  • Antigravity Commands
  • Trae Commands
  • Warp/Oz Commands
  • Task-Attributed Report
  • Subscription Usage
  • Example Output
  • Configuration
  • Environment Variables
• Frontend Visualization
  • Features
  • Running the Frontend
• Social Platform
  • Features
  • Getting Started
  • Data Validation
• Wrapped 2025
  • Command
  • What's Included
• Development
  • Prerequisites
  • How to Run
  • Container Setup
• Supported Platforms
  • Native Module Targets
  • Windows Support
• Session Data Retention
• Data Sources
• Pricing
• Contributing
  • Development Guidelines
• Acknowledgments
• License

Features

• Interactive TUI Mode - Beautiful terminal UI powered by Ratatui (default mode)
  • 6 interactive views: Overview, Models, Daily, Hourly, Stats, Agents (plus an optional Minutely view, opt-in via minutelyTabEnabled)
  • Keyboard & mouse navigation
  • GitHub-style contribution graph with configurable color themes
  • Real-time filtering and sorting
  • Zero flicker rendering
• Multi-platform support - Track usage across OpenCode, Claude Code, Codex CLI, Prime Agent, Copilot CLI, Cursor IDE, Gemini CLI, Amp, Codebuff, Droid, OpenClaw, Hermes Agent, Pi, Kimchi Coding, Reasonix, Kimi CLI, Kimi Work, Qwen CLI, Roo Code, Kilo, Mux, Kilo CLI, Crush, Goose, Antigravity, Antigravity CLI, Zed, Kiro, Trae, Warp/Oz, Cline, Gajae-Code, Grok Build, Jcode, MiMo Code, Command Code, Junie, ZCode, OpenCodeReview, CodeBuddy, WorkBuddy, Devin CLI, Devin Desktop, Augment Code, Synthetic, Cherry Studio, and fx
• Real-time pricing - Fetches current pricing from LiteLLM with 1-hour disk cache; automatic OpenRouter fallback and Cursor model pricing for newly released models
• Detailed breakdowns - Input, output, cache read/write, and reasoning token tracking
• Native Rust core - All parsing and aggregation done in Rust for 10x faster processing
• Web visualization - Interactive contribution graph with 2D and 3D views
• Flexible filtering - Filter by platform, date range, or year
• Task-attributed reports - LLM-powered session summarization and task grouping with multi-backend support (Apple FM, Claude, Codex, Gemini, Kiro, MiniMax)
• Export to JSON - Generate data for external visualization tools
• Social Platform - Share your usage, compete on leaderboards, and view public profiles

Installation

Quick Start

# Run directly with npx
npx tokscale@latest

# Or use bunx
bunx tokscale@latest

# Or use Deno without installing an alias
deno x npm:tokscale@latest

# Light mode (table rendering only)
npx tokscale@latest --light

That's it! This gives you the full interactive TUI experience with zero setup.

Package Structure: tokscale is an alias package (like swc) that installs @tokscale/cli. Both install the same CLI with the native Rust core (@tokscale/core) included.

Prerequisites

• Node.js or Bun
• (Optional) Rust toolchain for building native module from source

Development Setup

For local development or building from source:

# Clone the repository
git clone https://github.com/junhoyeo/tokscale.git
cd tokscale

# Install Bun (if not already installed)
curl -fsSL https://bun.sh/install | bash

# Install dependencies
bun install

# Run the CLI in development mode
bun run cli

Note: bun run cli is for local development. When installed via bunx tokscale, the command runs directly. The Usage section below shows the installed binary commands.

Building the Native Module

The native Rust module is required for CLI operation. It provides ~10x faster processing through parallel file scanning and SIMD JSON parsing:

# Build the native core (run from repository root)
bun run build:core

Note: Native binaries are pre-built and included when you install via bunx tokscale@latest. Building from source is only needed for local development.

Usage

Basic Commands

# Launch interactive TUI (default)
tokscale

# Launch TUI with specific tab
tokscale models    # Models tab
tokscale monthly   # Daily view (shows daily breakdown)
tokscale hourly    # Hourly tab

# Use legacy CLI table output
tokscale --light
tokscale models --light

# Launch TUI explicitly
tokscale tui

# Export contribution graph data as JSON
tokscale graph --output data.json

# Output data as JSON (for scripting/automation)
tokscale --json                    # Default models view as JSON
tokscale models --json             # Models breakdown as JSON
tokscale monthly --json            # Monthly breakdown as JSON
tokscale models --json > report.json   # Save to file

TUI Features

The interactive TUI mode provides:

• 8 Views: Overview (chart + top models), Usage (subscription quotas), Models, Daily, Hourly, Stats (contribution graph), Agents. A per-minute view (Minutely) is hidden by default and can be enabled with minutelyTabEnabled in settings.json — see Configuration
• Keyboard Navigation:
  • ←/→/Tab/BackTab: Switch views
  • ↑/↓ or Home/End: Navigate lists
  • Enter: Open daily detail (Daily tab) / select graph cell (Stats tab)
  • Esc or Backspace: Close dialog or exit detail view
  • c/d/t: Sort by cost/date/tokens
  • j: Jump to today
  • s: Open source picker dialog
  • g: Open group-by picker dialog (model, client+model, client+provider+model, workspace+model, session+model, client+session+model)
  • h: Toggle Daily/Hourly chart granularity (Overview tab)
  • v: Toggle Table/Profile view (Hourly tab)
  • y: Copy selected row to clipboard
  • p: Cycle through color themes
  • r: Refresh data; Shift+R toggles auto-refresh; +/- adjusts interval
  • e: Export to JSON
  • q or Ctrl+C: Quit
• Mouse Support: Click tabs, buttons, and filters
• Themes: Green, Halloween, Teal, Blue, Pink, Purple, Orange, Monochrome, YlGnBu, Graphite, Lagoon, Dusk
• Settings Persistence: Preferences saved to ~/.config/tokscale/settings.json (see Configuration)

Group-By Strategies

Press g in the TUI or use --group-by in --light/--json mode to control how model rows are aggregated:

--group-by model (most consolidated)

--group-by client,model (CLI default)

--group-by client,provider,model (most granular)

--group-by session,model (per-session cost attribution)

tokscale models --json --group-by session,model emits one entry per (session_id, model). Each entry includes a top-level sessionId field so downstream tools (e.g. multi-agent IDEs) can join cost data back to a specific agent-CLI session:

{
  "groupBy": "session,model",
  "entries": [
    {
      "sessionId": "019e1e27-af49-7cd1-89b7-7bad1c3f3be2",
      "client": "codex",
      "provider": "openai",
      "model": "gpt-5",
      "input": 25251,
      "output": 47,
      "cacheRead": 1920,
      "cacheWrite": 0,
      "reasoning": 40,
      "messageCount": 12,
      "cost": 0.0123
    }
  ]
}

Use --group-by client,session,model when you also need the client name on every row (one spawn across all 20+ supported CLIs at once).

Per-workspace cost

--group-by workspace,model attributes usage to the directory an agent ran in, so you can see what a given project cost:

# One row per (workspace, model)
tokscale models --light --group-by workspace,model --month

# Fold every git worktree into its parent repository — one row per repo
tokscale models --light --group-by workspace,model --merge-worktrees --month

# JSON carries workspaceKey (grouping identity) and workspaceLabel (display name)
tokscale models --json --group-by workspace,model --merge-worktrees

In the TUI, press g → Workspace + Model, then w to toggle worktree rollup (the footer shows [w:worktrees] or [w:repos]).

Workspace rows are labeled repo or repo ⑃ worktree. Clients disagree about how they record a workspace — Claude Code stores a dash-mangled directory slug (-Users-me-devpro-app) while Codex and OpenCode store real paths — so tokscale resolves slugs back to their true path against the filesystem. Four consequences worth knowing:

• Without --merge-worktrees, each git worktree is its own row. Agent CLIs that isolate every task into a worktree will therefore spread one repository across many rows; --merge-worktrees re-unites them (and also merges a repo recorded by different clients under different key formats).
• --merge-worktrees finds worktrees kept inside the repo and beside it. <repo>/.claude/worktrees/<name> (what agent CLIs create) and <repo>/.git/worktrees/<name> are recognized from the path alone; a worktree checked out elsewhere (git worktree add ../feature-x) is recognized by reading its .git pointer file back to the repository. A repo reached through two different path spellings (a symlink and its target) still stays two rows, because a workspace identity is compared as a string. Totals are unaffected either way — usage is split across rows, never lost or double counted.
• Rows that would show the same name are qualified with their parent directory. A label is the directory's own name, so ~/work/api and ~/oss/api would both read api; colliding labels gain as many leading path segments as it takes to tell them apart (work/api, oss/api), and when no path segment can — the same directory recorded by two clients under different key formats — the row is qualified with its workspace key instead. Grouping is unaffected — this only changes the displayed text.
• Clients that never record a workspace roll up into a single Unknown workspace row. Roughly half the supported clients (including gemini, cursor, amp, droid, roocode, kilocode, goose, and Copilot's OTEL path) do not write one, so their usage cannot be attributed to a directory.

Filtering by Platform

Use --client (short -c) to scope reports to one or more clients. The flag is repeatable, accepts comma-separated values, and works with every report command:

# Show only OpenCode usage
tokscale --client opencode

# Comma-separated: combine multiple clients
tokscale --client opencode,claude

# Repeated: same effect, useful with shell aliases
tokscale -c opencode -c claude

# Cursor IDE uses Tokscale's API cache; run login + sync --json first
tokscale --client cursor

# Synthetic (synthetic.new) is detected from other agent sessions
tokscale --client synthetic

# Combine with other filters
tokscale --client opencode,claude --week --json

Possible values: opencode, claude, codex, copilot, gemini, cursor, amp, codebuff, droid, openclaw, hermes, pi, prime-agent, kimchi, kimi, qwen, roocode, kilocode, kilo, mux, crush, goose, antigravity, antigravity-cli, zed, kiro, trae, warp, cline, gjc, grok, jcode, micode, commandcode, junie, zcode, opencodereview, codebuddy, augment, synthetic, cherrystudio.

Breaking change (v4.0.0): The per-client boolean flags (--opencode, --claude, --codex, etc.) have been removed and now error. Use the canonical --client/-c flag instead — e.g. tokscale --client opencode,claude.

Date Filtering

Date filters work across all commands that generate reports (tokscale, tokscale models, tokscale monthly, tokscale graph):

# Quick date shortcuts
tokscale --today              # Today only
tokscale --yesterday          # Yesterday only
tokscale --week               # Last 7 days
tokscale --month              # Current calendar month

# Custom date range (inclusive, local timezone)
tokscale --since 2024-01-01 --until 2024-12-31

# Filter by year
tokscale --year 2024

# Combine with other options
tokscale models --week --client claude --json
tokscale monthly --month --benchmark

Note: Date filters use your local timezone. Both --since and --until are inclusive. v2.2.0 note: Session active-time daily buckets also use your local timezone, so users outside UTC may see active-time dates align with local token/cost report days instead of UTC day boundaries.

Pricing Lookup

Look up real-time pricing for any model:

# Look up model pricing
tokscale pricing "claude-3-5-sonnet-20241022"
tokscale pricing "gpt-4o"
tokscale pricing "grok-code"

# Force specific provider source
tokscale pricing "grok-code" --provider openrouter
tokscale pricing "claude-3-5-sonnet" --provider litellm

# Inspect custom pricing overrides
tokscale pricing list-overrides

Lookup Strategy:

The pricing lookup uses a multi-step resolution strategy:

1. Custom Pricing Overrides - Exact user-defined entries from ~/.config/tokscale/custom-pricing.json
2. Exact Match - Direct lookup in LiteLLM/OpenRouter databases
3. Alias Resolution - Resolves friendly names (e.g., big-pickle → glm-4.7)
4. Tier Suffix Stripping - Removes quality tiers (gpt-5.2-xhigh → gpt-5.2)
5. Version Normalization - Handles version formats (claude-3-5-sonnet ↔ claude-3.5-sonnet)
6. Provider Prefix Matching - Tries common prefixes (anthropic/, openai/, etc.)
7. Cursor Model Pricing - Hardcoded pricing for models not yet in LiteLLM/OpenRouter (e.g., gpt-5.3-codex)
8. Fuzzy Matching - Word-boundary matching for partial model names

Custom Pricing Overrides

Create custom-pricing.json in Tokscale's config directory (~/.config/tokscale/custom-pricing.json on macOS/Linux by default; the same directory resolved by TOKSCALE_CONFIG_DIR when set) to override prices for model IDs that upstream pricing databases do not yet cover correctly.

{
  "$schema": "https://tokscale.ai/custom-pricing.schema.json",
  "models": {
    "accounts/fireworks/routers/kimi-k2p6-turbo": {
      "input_cost_per_million_tokens": 2.00,
      "output_cost_per_million_tokens": 8.00,
      "cache_read_input_token_cost_per_million_tokens": 0.30,
      "source": "https://docs.fireworks.ai/serverless/pricing",
      "notes": "Fireworks Kimi K2.6 Turbo (preview)"
    },
    "accounts/fireworks/models/kimi-k2p6": {
      "input_cost_per_million_tokens": 0.95,
      "output_cost_per_million_tokens": 4.00,
      "cache_read_input_token_cost_per_million_tokens": 0.16
    },
    "kimi-k2p6-turbo": {
      "input_cost_per_million_tokens": 2.00,
      "output_cost_per_million_tokens": 8.00
    }
  }
}

Override prices are entered in dollars per million tokens, matching how most API providers publish pricing; Tokscale converts them to per-token rates internally. At least one of input_cost_per_million_tokens or output_cost_per_million_tokens must be present, and cache-read/cache-creation fields are optional. An explicit 0 is allowed and is the way to declare a free model — it is a statement ("this costs nothing"), unlike an omitted field, which means the rate is unknown and leaves the usage unpriced. LiteLLM-style per-token field names such as input_cost_per_token, output_cost_per_token, and cache_read_input_token_cost are also accepted for copy/paste compatibility, but the per-million names are the recommended user-facing form. To omit a tier or cache price, leave the field out; negative or non-finite values are treated as invalid and the whole model entry is skipped so typos do not silently alter accounting. Optional source and notes fields are ignored by Tokscale and can be used for your own bookkeeping.

Overrides are exact-only and case-insensitive. Tokscale checks the raw model ID first, then the existing synthetic /models/ normalization, then falls through to LiteLLM, OpenRouter, Cursor pricing, and fuzzy matching if no override matches. Raw exact matches beat normalized exact matches, so accounts/fireworks/routers/kimi-k2p6-turbo can override one gateway-specific model while kimi-k2p6-turbo can cover normalized /models/ paths. Overrides are loaded once at startup; restart the command after editing the file. This is the recommended local fix for wrong-model pricing bugs while waiting on upstream LiteLLM pricing updates.

Provider Preference:

When multiple matches exist, original model creators are preferred over resellers:

Example: grok-code matches xai/grok-code-fast-1 ($0.20/$1.50) instead of azure_ai/grok-code-fast-1 ($3.50/$17.50).

Social

# Login to Tokscale (opens browser for GitHub auth)
tokscale login

# Save an existing Tokscale API token without browser auth
tokscale login --token tt_xxx

# Check who you're logged in as
tokscale whoami

# Display your saved API token as a QR code (useful for sharing to another device)
# Encodes {"token":"tt_xxx","username":"..."} — scan with any QR reader
tokscale qr

# Submit your usage data to the leaderboard
tokscale submit

# Submit in CI/headless environments without writing credentials
# Precedence: TOKSCALE_API_TOKEN env > saved credentials file (~/.config/tokscale/credentials.json).
# When the env var is set, the saved file is ignored for that invocation.
TOKSCALE_API_TOKEN=tt_xxx tokscale submit

# Revoke a token: visit Settings > API Tokens on the leaderboard site
# (https://tokscale.ai/settings) and click "Revoke" on the token row.
# Revocation takes effect immediately — subsequent requests with that
# token will get HTTP 401 "Invalid API token".

# Submit with filters
tokscale submit --client opencode,claude --since 2024-01-01

# Preview what would be submitted (dry run)
tokscale submit --dry-run

# Logout
tokscale logout

Unpriced usage is excluded from submission

Before anything is submitted, every message must resolve to an authoritative price that covers every token bucket the message populated (input, output, cache read, cache write). Messages that cannot be priced are skipped and reported as Warning: excluded N unpriced provider/model message(s) — unknown models never submit invented or guessed spend, and all remaining priced usage still submits normally.

The exclusion reasons:

• no authoritative model-to-price mapping — the model ID is absent from LiteLLM, OpenRouter, models.dev, and your custom overrides.
• generic routing label has no authoritative model-to-price mapping — the ID is a router label (auto, gemini-default, …) whose underlying model varies per request, so it is refused outright. An explicit entry for the label in custom-pricing.json is the supported way to assert a rate you know applies.
• pricing does not cover every populated token bucket — a price row was found, but it is missing a rate (most often cache read or cache creation) that this usage actually populates.
• model price match does not establish the requested provider — a price row was found only by matching the model part of the ID, or by trying a provider prefix, which does not prove your provider bills at that row's rate.
• model price match does not exactly name the requested model — a fuzzy or provider-scoped match was found, but nothing proves the priced key names the model you actually used.
• model price lookup is ambiguous across non-equivalent candidates — several candidate rows matched and they quote different prices.

To include previously excluded usage, add an exact-match entry to custom-pricing.json (see Custom Pricing Overrides) — an explicit 0 declares a genuinely free model — then re-run tokscale submit --dry-run until no warnings remain. tokscale pricing <model-id> shows which entry matched. The file is keyed by the model ID alone — the model half of the provider/model pair shown in the warning.

Autosubmit

Autosubmit schedules the normal tokscale submit flow with the operating system scheduler. It is useful for keeping your public profile current without a manual terminal run.

# Enable periodic submission. Uses launchd on macOS, systemd user timers on Linux
# when available, cron as a Linux fallback, and Windows Task Scheduler on Windows.
tokscale autosubmit enable --interval 24h

# Keep the same client and date filters you would pass to submit.
tokscale autosubmit enable --interval 2h --client opencode,claude --week

# Show saved settings and the last run/error.
tokscale autosubmit status
tokscale autosubmit status --json

# Run once now, even if the saved interval has not elapsed.
tokscale autosubmit run --force

# Disable autosubmit and remove the scheduler entry.
tokscale autosubmit disable

Scheduled runs are non-interactive: they never prompt for GitHub auth or star confirmation. Run tokscale login --token tt_xxx once, or set TOKSCALE_API_TOKEN in the scheduler environment. Tokscale records scheduler state in settings.json, writes logs under ~/.config/tokscale/autosubmit/, and uses a lock file so overlapping scheduler ticks do not submit twice.

Cursor IDE Commands

Cursor IDE support uses Cursor's web API export, cached by Tokscale at ~/.config/tokscale/cursor-cache/usage*.csv. Tokscale does not parse local Cursor Agent CLI state under ~/.cursor, and it does not treat the desktop SQLite DB as a usage ledger.

When the Cursor desktop app is installed and signed in, tokscale cursor login prefers the local cursorAuth/accessToken from Cursor's state.vscdb and builds the session cookie automatically. tokscale cursor sync also refreshes that token when available. Usage rows still come only from Cursor's usage-export API.

Setup (desktop auto-login):

1. Sign in to the Cursor desktop app.
2. Run tokscale cursor login --name work (auto-detects the local desktop session when available).
3. Run tokscale cursor sync --json to populate ~/.config/tokscale/cursor-cache/usage.csv.
4. Run tokscale --client cursor or any report command.

Fallback (manual browser cookie), if desktop login is unavailable:

1. Open https://www.cursor.com/settings in your browser and sign in.
2. Copy the WorkosCursorSessionToken cookie value:
   • Network tab: make any request to cursor.com/api/*, then copy the value after WorkosCursorSessionToken= from the Cookie request header.
   • Application tab: open Cookies -> https://www.cursor.com, then copy the WorkosCursorSessionToken value.
3. Run tokscale cursor login --name work and paste the token when prompted.
4. Continue with tokscale cursor sync --json as above.

Treat the session token like a password. It is stored locally in ~/.config/tokscale/cursor-credentials.json.

# Login to Cursor (auto-detects Cursor desktop login; falls back to browser cookie paste)
# --name is optional; it just helps you identify accounts later
tokscale cursor login --name work

# Check Cursor authentication status and session validity
tokscale cursor status

# List saved Cursor accounts
tokscale cursor accounts

# Manually refresh cached Cursor usage
tokscale cursor sync --json

# Switch active account (controls which account syncs to cursor-cache/usage.csv)
tokscale cursor switch work

# Logout from a specific account (keeps history; excludes it from aggregation)
tokscale cursor logout --name work

# Logout and delete cached usage for that account
tokscale cursor logout --name work --purge-cache

# Logout from all Cursor accounts (keeps history; excludes from aggregation)
tokscale cursor logout --all

# Logout from all accounts and delete cached usage
tokscale cursor logout --all --purge-cache

By default, Tokscale aggregates usage across all saved Cursor accounts by reading cursor-cache/usage*.csv. The active account syncs to usage.csv; additional accounts sync to usage.<account>.csv.

When you log out, Tokscale moves cached usage to cursor-cache/archive/ so it is no longer aggregated. Use --purge-cache to delete cached usage instead.

Antigravity Commands

Antigravity sync currently works on macOS and Linux only. The Antigravity-enabled editor must be running and its local language server available; tokscale reads usage from that local language server and caches normalized artifacts locally.

# Check whether tokscale can see running Antigravity language servers
tokscale antigravity status

# Sync usage from local Antigravity language servers into tokscale's cache
tokscale antigravity sync

# Delete the cached Antigravity artifacts
tokscale antigravity purge-cache

Cache location: ~/.config/tokscale/antigravity-cache/

How it works: tokscale antigravity sync discovers local Antigravity session candidates, fetches confirmed usage data from the local language server RPC, and stores normalized JSONL artifacts for tokscale-core to parse later. Run sync before reports if you want the freshest Antigravity data.

Trae Commands

Trae (ByteDance's AI IDE) ships in two international product lines — Trae IDE and Trae Solo. They share the same account-level usage data (same backend, same JWT), so tokscale reports them as a single trae client. You can install either or both desktop apps; tokscale auto-discovers credentials from whichever is present.

Credentials are identified per desktop app via --variant:

• --variant ide — credentials from Trae IDE (~/Library/Application Support/Trae/)
• --variant solo — credentials from Trae Solo (~/Library/Application Support/TRAE SOLO/)

tokscale trae sync calls the official query_user_usage_group_by_session API exactly once per run (regardless of how many desktop apps are installed) and persists the raw JSON to a local cache.

# Log in (auto-detects credentials from any installed Trae desktop client)
tokscale trae login

# Manual JWT entry (for environments where auto-detect can't find storage.json,
# e.g. Linux/Windows or a headless server). Open https://www.trae.ai/account-setting#usage
# in your browser, then F12 → Network → filter `query_user_usage` and copy the
# `Authorization` header value.
tokscale trae login --manual --variant solo

# Show which variants have cached credentials
tokscale trae status

# Sync usage (uses the first available credential source)
tokscale trae sync --since 30

# Forget cached credentials for one variant
tokscale trae logout --variant solo

Cache location: ~/.config/tokscale/trae-cache/

How it works: tokscale either decrypts the desktop client's iCubeAuthInfo://* blob (globalStorage/storage.json) to recover a JWT, or accepts one pasted via --manual. It then calls POST /trae/api/v1/pay/query_user_usage_group_by_session paginated and stores the raw JSON. Run sync before reports if you want the freshest Trae data.

Sync-lock recovery during upgrades

Antigravity and Trae syncs use a legacy-compatible sync.lock file to avoid overlapping an older tokscale binary during a rolling upgrade. After a crash or forced stop, that file can remain. Tokscale intentionally fails closed instead of replacing it, because an older binary may still be creating or updating the same path. Confirm that no tokscale antigravity sync or tokscale trae sync process is active, remove the exact quoted sync.lock path printed by the command, then retry. Do not remove the lock while a sync may still be running.

Note on pricing: Trae cost figures are vendor-reported — tokscale surfaces the dollar_float value returned by Trae's own API rather than recomputing cost from token counts through tokscale's pricing engine. Numbers will match what you see on trae.ai/account-setting#usage, not what tokscale would otherwise calculate for the same usage.

China variants: The China editions (trae.com.cn) are intentionally not supported. The CN backend does not expose a session-level usage query API. Trae CN / Trae Solo CN support will be added once an official endpoint becomes available upstream.

Warp/Oz Commands

Warp/Oz does not expose local token transcripts. Tokscale only syncs the aggregate request and spend counters returned by Warp's GraphQL API, then reports them as warp / aggregate-requests rows with zero token buckets.

# Save a bearer token or Cookie header copied from an authenticated Warp request
tokscale warp login

# Inspect credential/cache state and diagnostics
tokscale warp status

# Sync aggregate requests and spend into tokscale's local cache
tokscale warp sync

# Remove saved credentials; add --purge-cache to delete synced usage too
tokscale warp logout --purge-cache

Cache location: ~/.config/tokscale/warp-cache/usage.json

How it works: tokscale warp sync calls Warp's authenticated GraphQL API for account and workspace aggregate counters. Tokscale preserves request counts as message counts and vendor-reported spend as cost, but it never converts requests into synthetic tokens. Warp is excluded from default submit data because the public leaderboard accepts token-attributed usage, not aggregate request counters.

Task-Attributed Report

The report command generates a task-attributed usage breakdown. It uses an LLM to summarize each session into a short title and category, then groups related sessions into high-level task clusters for a bird's-eye view of where your tokens went.

# Basic report (today, default Apple FM summarizer)
tokscale report

# Last 7 days
tokscale report --week

# Use Claude Code as the summarizer backend
tokscale report --week --summarizer claude

# Use Codex, Gemini, Kiro, or MiniMax
tokscale report --summarizer codex
tokscale report --summarizer gemini
tokscale report --summarizer kiro
tokscale report --summarizer minimax

# Skip LLM summarization (show raw data only)
tokscale report --no-summarize

# Re-summarize from scratch (resets cached summaries in range)
tokscale report --week --rebuild

# Output as JSON
tokscale report --week --json

# Filter by workspace or client
tokscale report --workspace my-project --client opencode

Summarizer backends:

How it works:

1. Sessions are scanned and inserted into a local SQLite wiki database (wiki.db in your platform config dir — e.g. ~/.config/tokscale/ on Linux, ~/Library/Application Support/tokscale/ on macOS)
2. Unsummarized sessions are sent to the chosen LLM backend in batches, which returns a title, category, description, and complexity for each
3. A second LLM pass groups all titled sessions into 3–8 high-level task clusters (e.g. "Kiro Auth", "Tokscale Report", "System Config")
4. Results are cached in the wiki DB — subsequent runs skip already-summarized sessions

Example output:

  Task Group                                  Sess     Tokens     Cost
  ───────────────────────────────────────────────────────────────────────
  Tokscale Development                          19      4.2B    $22.66
    Add task-attributed report command
    Implement wiki DB schema
    Fix pricing lookup for new models
  System Config                                 28      2.1B    $10.06
    Configure OpenCode workspace settings
    Update shell aliases
  Kiro Auth                                      4    890.5M     $3.10
    Implement JWT refresh flow

Subscription Usage

Tokscale can fetch and display your real-time subscription quota across AI providers. This shows how much of your plan you've used and when limits reset.

# Show subscription usage for all detected providers
tokscale usage

# Output as JSON (for scripting)
tokscale usage --json

# Lightweight terminal output (no TUI)
tokscale usage --light

In the TUI, navigate to the Usage tab to see subscription data. Use [Refresh] to refresh subscription quotas. The keyboard refresh shortcut r uses the same refresh path.

Note: Subscription quotas and balances are vendor-reported — tokscale calls each provider's own quota endpoint and surfaces the response verbatim. Numbers reflect what the provider reports (which is also what shows up in their official dashboards) and are not independently verified against tokscale's own usage tracking.

Supported Providers

Providers are auto-detected — only those with valid credentials are shown. If a provider is missing, ensure you've logged in or set the required environment variable.

Codex Multi-Account Usage

Tokscale can save multiple Codex OAuth accounts for subscription usage display. The TUI Usage tab groups saved accounts under one Codex section. The active account is marked with *; inactive accounts can be selected with [Use]; account removal uses [Remove] followed by [Confirm].

To add an account without leaving the TUI, click [Add Codex] in the Usage tab. Tokscale starts codex login with a temporary CODEX_HOME, displays the login output in the Usage tab, imports the resulting auth into Tokscale's saved account store, and then refreshes usage. This keeps the login isolated and does not switch the current Codex auth; click [Use] on a saved account when you want Tokscale to write that account into the real Codex auth file.

The CLI commands are still available for scripted or manual account management, plus a separate opt-in account-activity snapshot:

# Save the current Codex auth as a named Tokscale account
tokscale codex import --name work

# List saved Codex accounts
tokscale codex accounts
tokscale codex accounts --json

# Switch the active Codex account and write Codex auth.json
tokscale codex switch work

# Stop tracking a saved Codex account (removes it from Tokscale's store
# only — the codex CLI's own auth.json/login is never touched)
tokscale codex remove personal

# Check subscription usage for the active or a named account
tokscale codex status
tokscale codex status --name personal --json

# Fetch the active Codex app-server account activity separately from local totals
tokscale codex activity
tokscale codex activity --json

When saved Codex accounts exist, tokscale usage --json includes structured account metadata for each Codex entry and the TUI displays those entries under one Codex group. Without saved accounts, Tokscale falls back to the current Codex auth discovery path (CODEX_HOME/auth.json, ~/.config/codex/auth.json, ~/.codex/auth.json, then macOS Keychain).

If those native Codex sources produce no successful usage result, Tokscale reads the openai OAuth entry from OpenCode's $XDG_DATA_HOME/opencode/auth.json (normally ~/.local/share/opencode/auth.json). OpenAI API-key entries are not ChatGPT subscription credentials and are ignored. OpenCode credentials are read-only: Tokscale never imports, refreshes, or rewrites them. If the access token is rejected, use OpenCode so it can refresh the login, or reconnect OpenAI with /connect.

tokscale codex activity uses only the installed Codex app-server's active authentication to fetch a timestamped, account-level snapshot. It is supplemental data: it is never included in local totals, reports, exports, submissions, or leaderboards.

Example Output

╭──────────────────────────────────────────────────────────╮
│ Session    85% left  [=========---] resets in 2h 15m     │
│ Weekly     72% left  [========----] resets Fri 3pm       │
│ Plan     Max 20x                                         │
╰──────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────────────────╮
│ Session    40% left  [=====-------] resets in 4h 30m     │
│ Weekly     90% left  [==========--] resets Mon 12am      │
│ Account  user@example.com                                │
│ Plan     Pro                                             │
╰──────────────────────────────────────────────────────────╯

Example Output (--light version)

Configuration

Tokscale stores settings in ~/.config/tokscale/settings.json:

{
  "colorPalette": "blue",
  "includeUnusedModels": false,
  "defaultClients": ["opencode", "claude"],
  "scanner": {
    "extraScanPaths": {
      "codex": [
        "/Users/me/workspace/project-a/.codex/sessions",
        "/Users/me/workspace/project-b/.codex/archived_sessions"
      ],
      "hermes": [
        "/Users/me/.hermes/profiles/director_planning",
        "/Users/me/.hermes/profiles/research/state.db"
      ]
    }
  }
}

Day boundaries and scanner.bucketTimezone

Which calendar day a message counts toward depends on a timezone. Tokscale records this device's timezone on first run and reuses it, rather than reading the machine's current timezone on every scan.

This matters because day totals are submitted per day and never allowed to decrease. If the same history were re-bucketed under a different timezone — you travel, you change your system clock, you run in CI with a different TZ — a session near midnight would move to the neighbouring day, and both the old and the new day would keep their value. The total would go up without any new usage. Pinning the zone makes the day boundary stable, so a rescan of unchanged history always produces the same buckets.

$ tokscale config list
timezone     Asia/Seoul

$ tokscale config get timezone
Asia/Seoul

# `set timezone auto` is allowed only before a valid pin exists (or while
# recovering an invalid hand-edited value). It cannot repin an established
# device.
$ tokscale config set timezone auto

Only IANA zone names are accepted. Fixed UTC offsets such as +09:00 are rejected: an offset cannot follow daylight saving time, so a pinned offset stops matching local midnight after a DST transition and re-splits usage near the day boundary — a smaller version of the problem pinning removes.

An established valid pin cannot be changed or unset, including with auto. Historical submitted day rows are monotonic, so re-keying prior usage would permanently double count it. Relocating a device requires a server resync/replacement transition before choosing a different bucket timezone.

Existing installs are unaffected until they pin, and the run that pins reports exactly what it would have reported anyway: the zone recorded is the one the machine was already using.

Use scanner.extraScanPaths for persistent extra roots such as project-level .codex directories or imported Gemini/OpenClaw histories. Tokscale automatically discovers Hermes profile databases under $HERMES_HOME/profiles/*/state.db (or ~/.hermes/profiles/*/state.db when HERMES_HOME is unset). Use scanner.extraScanPaths.hermes only for non-standard Hermes profile locations; entries may point at a profile directory containing state.db or directly at a state.db file. Tokscale merges these paths with the default scan roots on every run and deduplicates overlapping roots by canonical path.

Use defaultClients to pin a personal default — for example, set it to ["opencode", "claude"] if those are the only clients you use, and tokscale (with no flags) will scope every report to them automatically. Pass --client on the command line to override for a single run.

Enabling the Minutely tab

The Minutely tab shows a per-minute breakdown of token usage and is most useful for diagnosing burst patterns, debugging a single session, or watching activity in near-real-time alongside autoRefreshEnabled. It is hidden by default because the per-minute aggregation runs over every parsed message during data loading, which adds RAM and CPU cost that most users do not need.

To enable it, set minutelyTabEnabled to true in ~/.config/tokscale/settings.json:

{
  "minutelyTabEnabled": true
}

After restart, the Minutely tab appears between Hourly and Stats in the tab strip, and Tab / BackTab / Left / Right navigation cycles through it. Set the flag back to false to hide the tab and skip the aggregation again.

Cache directory layout

The regenerable CLI/TUI/pricing/Wrapped caches now live under ~/.config/tokscale/cache/ (or ${TOKSCALE_CONFIG_DIR}/cache/ when overridden). Integration sync artifacts remain in client-specific cache roots such as ~/.config/tokscale/antigravity-cache/ and ~/.config/tokscale/trae-cache/:

• tui-data-cache.json — TUI startup cache
• source-message-cache-v2/ + source-message-cache.lock — sharded source-message cache + lock file
• pricing-litellm.json / pricing-openrouter.json — pricing caches
• opencode-migration.json — OpenCode migration record
• fonts/ and images/ — Wrapped asset caches

It is safe to delete this directory. Tokscale will recreate and repopulate it on demand.

One caveat, for Claude Code only. Claude Code rewrites a session transcript in place when you resume or compact it: the file keeps its name but loses assistant turns it had already written. source-message-cache-v2/ remembers those turns for as long as the transcript file exists, so they keep counting toward your totals. That is the only place they still exist — the transcript itself no longer has them. Deleting the cache (or letting a Claude parser upgrade rebuild it) rebuilds from the compacted transcripts, so totals for heavily compacted sessions can come back lower. Deleting a transcript still drops its turns either way, which is what makes local disk the source of truth.

Environment Variables

Environment variables override config file values. For CI/CD or one-off use:

# Example: Increase timeout for very large datasets
TOKSCALE_NATIVE_TIMEOUT_MS=600000 tokscale graph --output data.json

# Example: one-off extra scan roots
TOKSCALE_EXTRA_DIRS='codex:/Users/me/workspace/project-a/.codex/sessions,gemini:/Users/me/imports/imac/gemini/tmp' tokscale

# Example: submit from CI without an interactive browser login
TOKSCALE_API_TOKEN=tt_xxx tokscale submit

Note: For persistent extra roots, prefer scanner.extraScanPaths in ~/.config/tokscale/settings.json. TOKSCALE_EXTRA_DIRS is best for one-off overrides or CI/CD.

Headless Mode

Tokscale can aggregate token usage from Codex CLI and MiniMax Code headless outputs for automation, CI/CD pipelines, and batch processing.

What is headless mode?

When you run Codex CLI or MiniMax Code with JSON output flags, the CLI writes usage data to stdout. Headless mode captures that stream and keeps it attributable to the originating CLI. MiniMax Code is intentionally read from Tokscale's capture directory rather than its shared Desktop/Runtime session store, whose records do not identify the originating surface.

Storage location: ~/.config/tokscale/headless/

On macOS, Tokscale also scans ~/Library/Application Support/tokscale/headless/ when TOKSCALE_HEADLESS_DIR is not set.

Tokscale automatically scans this directory structure:

~/.config/tokscale/headless/
├── codex/       # Codex CLI JSONL outputs
└── mcode/       # MiniMax Code stream-json outputs

Environment variable: Set TOKSCALE_HEADLESS_DIR to customize the headless log directory:

export TOKSCALE_HEADLESS_DIR="$HOME/my-custom-logs"

Recommended (automatic capture):

Manual redirect (optional):

MiniMax Code usage is counted only when the final exec.result includes model.providerId and model.modelId. Partial captures and older MiniMax Code releases that omit this identity are skipped instead of being priced against a guessed model.

Diagnostics:

# Show scan locations and headless counts
tokscale sources
tokscale sources --json

CI/CD integration example:

# In your GitHub Actions workflow
- name: Run AI automation
  run: |
    mkdir -p ~/.config/tokscale/headless/codex
    codex exec --json "review code changes" \
      > ~/.config/tokscale/headless/codex/pr-${{ github.event.pull_request.number }}.jsonl

# Later, track usage
- name: Report token usage
  run: tokscale --json

Note: Headless capture is supported for Codex CLI and MiniMax Code. If you run either CLI directly, redirect stdout to its matching headless directory as shown above.

Frontend Visualization

The frontend provides a GitHub-style contribution graph visualization:

Features

• 2D View: Classic GitHub contribution calendar
• 3D View: Isometric 3D contribution graph with height based on token usage
• Multiple color palettes: GitHub, GitLab, Halloween, Winter, and more
• 3-way theme toggle: Light / Dark / System (follows OS preference)
• GitHub Primer design: Uses GitHub's official color system
• Interactive tooltips: Hover for detailed daily breakdowns
• Day breakdown panel: Click to see per-source and per-model details
• Year filtering: Navigate between years
• Source filtering: Filter by platform (OpenCode, Claude, Codex, MiniMax Code, Copilot, Cursor, Gemini, Amp, Codebuff, Droid, OpenClaw, Hermes Agent, Pi, Prime Agent, Kimi, Qwen, Roo Code, Kilo, Mux, Kilo CLI, Crush, Goose, Antigravity, Antigravity CLI, Zed, Kiro, Trae, Warp, Cline, Gajae-Code, Grok Build, Jcode, MiMo Code, Command Code, Junie, ZCode, OpenCodeReview, CodeBuddy, WorkBuddy, Devin CLI, Devin Desktop, Augment Code, Synthetic, Cherry Studio)
• Stats panel: Total cost, tokens, active days, streaks
• FOUC prevention: Theme applied before React hydrates (no flash)

Running the Frontend

cd packages/frontend
bun install
bun run dev

Open http://localhost:3000 to access the social platform.

Social Platform

Tokscale includes a social platform where you can share your usage data and compete with other developers.

Features

• Leaderboard - See who's using the most tokens across all platforms
• User Profiles - Public profiles with contribution graphs and statistics
• Period Filtering - View stats for all time, this month, or this week
• GitHub Integration - Login with your GitHub account
• Local Viewer - View your data privately without submitting

GitHub Profile Embed Widget

You can embed your public Tokscale stats directly in your GitHub profile README:

[![Tokscale Stats](https://tokscale.ai/api/embed/<username>/svg)](https://tokscale.ai/u/<username>)

Replace <username> with your GitHub username. With no query parameters this renders the default classic card; append any of the parameters below to customize the design.

Examples:

![](https://tokscale.ai/api/embed/<username>/svg?template=minimal&color=purple&graph=1)
![](https://tokscale.ai/api/embed/<username>/svg?template=orbit&color=pink&rank=percent)
![](https://tokscale.ai/api/embed/<username>/svg?template=terminal&color=green&theme=light)
![](https://tokscale.ai/api/embed/<username>/svg?template=receipt&color=YlGnBu&graph=1)
![](https://tokscale.ai/api/embed/<username>/svg?view=3d&compact=1)

GitHub Profile Badge

You can also use a shields.io-style badge for a more compact display:

![Tokscale Tokens](https://tokscale.ai/api/badge/<username>/svg)

• Replace <username> with your GitHub username
• Optional query params:
  • metric=tokens (default), metric=cost, or metric=rank
  • style=flat (default) or style=flat-square
  • sort=tokens (default) or sort=cost to control ranking basis
  • compact=1 to use compact number notation (e.g., 1.2M, $3.4K)
  • label=<text> to override the left-side label
  • color=<hex> to override the right-side color (e.g., color=ff5733)
• Examples:
  • https://tokscale.ai/api/badge/<username>/svg?metric=cost&compact=1
  • https://tokscale.ai/api/badge/<username>/svg?metric=rank&sort=cost&style=flat-square

Getting Started

1. Login - Run tokscale login to authenticate via GitHub, or create an API token in Settings for CI/headless use
2. Submit - Run tokscale submit to upload your usage data
3. View - Visit the web platform to see your profile and the leaderboard

Data Validation

Submitted data goes through Level 1 validation:

• Mathematical consistency (totals match, no negatives)
• No future dates
• Required fields present
• Duplicate detection

Wrapped 2025

Generate a beautiful year-in-review image summarizing your AI coding assistant usage—inspired by Spotify Wrapped.

bunx tokscale@latest wrapped	bunx tokscale@latest wrapped --clients	bunx tokscale@latest wrapped --agents --disable-pinned

Command

# Generate wrapped image for current year
tokscale wrapped

# Generate for a specific year
tokscale wrapped --year 2025

What's Included

The generated image includes:

• Total Tokens - Your total token consumption for the year
• Top Models - Your 3 most-used AI models ranked by cost
• Top Clients - Your 3 most-used platforms (OpenCode, Claude Code, Cursor, etc.)
• Messages - Total number of AI interactions
• Active Days - Days with at least one AI interaction
• Cost - Estimated total cost based on LiteLLM pricing
• Streak - Your longest consecutive streak of active days
• Contribution Graph - A visual heatmap of your yearly activity

The generated PNG is optimized for sharing on social media. Share your coding journey with the community!

Development

Quick setup: If you just want to get started quickly, see Development Setup in the Installation section above.

Prerequisites

# Bun (required for JS tooling)
bun --version

# Rust (for native CLI binary)
rustc --version
cargo --version

How to Run

After following the Development Setup, you can:

# Build native module (optional but recommended)
bun run build:core

# Run in development mode (launches TUI)
cd packages/cli && bun src/index.ts

# Or use legacy CLI mode
cd packages/cli && bun src/index.ts --light

make docker/build   # build and tag the frontend image (tokscale:latest)
make up             # start Postgres and the frontend on http://localhost:3333

make up

make tui/build   # build once
make tui         # launch

TOKSCALE_UID=$(id -u) TOKSCALE_GID=$(id -g) \
  docker compose --profile tui run --rm \
  -v "$HOME/.claude:/home/tokscale/.claude:ro" tui

make down         # stop all services
make logs/app     # tail app logs
make help         # full target list

export POSTGRES_USER=myuser
export POSTGRES_PASSWORD=mypass
export POSTGRES_DB=mydb
export DATABASE_URL=postgresql://myuser:mypass@db:5432/mydb

# Test native module (Rust)
cd packages/core
bun run test:rust      # Cargo tests
bun run test           # Node.js integration tests
bun run test:all       # Both

cd packages/core

# Build in debug mode (faster compilation)
bun run build:debug

# Build in release mode (optimized)
bun run build

# Run Rust benchmarks
bun run bench

# Export graph data to file
tokscale graph --output usage-data.json

# Date filtering (all shortcuts work)
tokscale graph --today
tokscale graph --week
tokscale graph --since 2024-01-01 --until 2024-12-31
tokscale graph --year 2024

# Filter by platform
tokscale graph --client opencode,claude

# Show processing time benchmark
tokscale graph --output data.json --benchmark

tokscale --benchmark           # Show processing time with default view
tokscale models --benchmark    # Benchmark models report
tokscale monthly --benchmark   # Benchmark monthly report
tokscale graph --benchmark     # Benchmark graph generation

# Export data for visualization
tokscale graph --output packages/frontend/public/my-data.json

# Generate synthetic data
cd packages/benchmarks && bun run generate

# Run Rust benchmarks
cd packages/core && bun run bench

Supported Platforms

Native Module Targets

On Linux, the launcher detects glibc vs musl automatically (via process.report, the musl dynamic loader at /lib/ld-musl-*.so.1, and ldd). If detection ever picks the wrong flavor — e.g. in minimal containers — set TOKSCALE_LIBC=musl (or TOKSCALE_LIBC=gnu) to force it.

Windows Support

Tokscale fully supports Windows. The TUI and CLI work the same as on macOS/Linux.

Installation on Windows:

# Install Bun (PowerShell)
powershell -c "irm bun.sh/install.ps1 | iex"

# Run tokscale
bunx tokscale@latest

Data Locations on Windows

AI coding tools store their session data in cross-platform locations. Most tools use the same relative paths on all platforms:

Devin Desktop agent support: Local usage parsing works for ACP-connected agents (e.g. Cascade/Windsurf, claude-code, opencode) that emit usage_update events in the NDJSON stream. The default devin-cloud agent does not emit local usage_update events — its usage stays server-side and cannot be tracked by tokscale without an account-level API.

Note: On Windows, ~ expands to %USERPROFILE% (e.g., C:\Users\YourName). These tools intentionally use Unix-style paths (like .local/share) even on Windows for cross-platform consistency, rather than Windows-native paths like %APPDATA%.

Windows-Specific Configuration

Tokscale stores its configuration in:

• TUI settings: %APPDATA%\tokscale\settings.json (platform default; override with TOKSCALE_CONFIG_DIR)
• Cache: %APPDATA%\tokscale\cache\ (consolidated cache root)
• Legacy cache paths: %USERPROFILE%\.cache\tokscale\ and %LOCALAPPDATA%\tokscale\cache\ equivalents from older releases may still exist until regenerated data is written to the new path
• Cursor credentials: %USERPROFILE%\.config\tokscale\cursor-credentials.json
• Trae credentials and synced usage: %APPDATA%\tokscale\trae-cache\
• Tokscale account credentials: %USERPROFILE%\.config\tokscale\credentials.json

Session Data Retention

By default, some AI coding assistants automatically delete old session files. To preserve your usage history for accurate tracking, disable or extend the cleanup period.

Claude Code

Default: 30 days cleanup period

Add to ~/.claude/settings.json:

{
  "cleanupPeriodDays": 9999999999
}

Setting an extremely large value (e.g., 9999999999 days ≈ 27 million years) effectively disables cleanup.

Gemini CLI

Default: Cleanup disabled (sessions persist forever)

If you've enabled cleanup and want to disable it, remove or set enabled: false in $GEMINI_CLI_HOME/settings.json (fallback: ~/.gemini/settings.json):

{
  "general": {
    "sessionRetention": {
      "enabled": false
    }
  }
}

Or set an extremely long retention period:

{
  "general": {
    "sessionRetention": {
      "enabled": true,
      "maxAge": "9999999d"
    }
  }
}

Codex CLI

Default: No automatic cleanup (sessions persist forever)

Codex CLI does not have built-in session cleanup. Sessions in ~/.codex/sessions/ persist indefinitely.

Note: There's an open feature request for this: #6015

OpenCode

Default: No automatic cleanup (sessions persist forever)

OpenCode does not have built-in session cleanup. Sessions in ~/.local/share/opencode/storage/ persist indefinitely.

Note: See #4980

Data Sources

OpenCode

Location: ~/.local/share/opencode/opencode.db (v1.2+) or storage/message/{sessionId}/*.json (legacy)

OpenCode 1.2+ stores sessions in SQLite. Tokscale reads from SQLite first and falls back to legacy JSON files for older versions.

OpenCode picks the db filename from the release channel the binary was built against: the latest and beta channels use opencode.db, while other channels use opencode-<channel>.db (e.g. opencode-stable.db, opencode-nightly.db). Tokscale scans all of them, so users running multiple channels side by side get a unified view.

If you launched opencode with OPENCODE_DB pointing at a file outside ~/.local/share/opencode, add the absolute path to ~/.config/tokscale/settings.json so tokscale can find it on every run:

{
  "scanner": {
    "opencodeDbPaths": [
      "/custom/location/opencode.db",
      "/another/location/opencode-stable.db"
    ]
  }
}

Paths are merged with auto-discovery, deduped by canonical path, and non-existent entries are silently skipped (so stale config never breaks a scan). opencode.db-wal, opencode.db-shm, and other SQLite sidecars are rejected.

If you keep sessions outside Tokscale's default home-root locations, you can also persist extra scan roots per client:

{
  "scanner": {
    "extraScanPaths": {
      "codex": [
        "/Users/me/workspace/project-a/.codex/sessions",
        "/Users/me/workspace/project-b/.codex/archived_sessions"
      ],
      "gemini": ["/Users/me/imports/imac/gemini/tmp"],
      "hermes": [
        "/Users/me/.hermes/profiles/director_planning",
        "/Users/me/.hermes/profiles/research/state.db"
      ],
      "openclaw": ["/Users/me/imports/imac/openclaw/agents"]
    }
  }
}

This is useful for project-level .codex directories, imported histories, and Hermes profile databases outside the default $HERMES_HOME/state.db or ~/.hermes/state.db location. Tokscale still scans its default roots, then merges scanner.extraScanPaths and TOKSCALE_EXTRA_DIRS on top with canonical-path deduplication. It does not auto-discover your whole workspace.

Each message contains:

{
  "id": "msg_xxx",
  "role": "assistant",
  "modelID": "claude-sonnet-4-20250514",
  "providerID": "anthropic",
  "tokens": {
    "input": 1234,
    "output": 567,
    "reasoning": 0,
    "cache": { "read": 890, "write": 123 }
  },
  "time": { "created": 1699999999999 }
}

Claude Code

Location: ~/.claude/projects/{projectPath}/*.jsonl and ~/.claude/transcripts/*.jsonl

JSONL format with assistant mess