ai-limit-checker 0.7.0

Check usage limits for Claude Code and Antigravity CLI from terminal

AI Limit Checker

Check usage limits for Claude Code and Antigravity CLI from your terminal.

---

✨ Features

• Claude Code — 5h & 7d usage windows with Sonnet/Opus breakdown
• Antigravity CLI — Per-group (Gemini / Claude+GPT) weekly + five-hour limits
• Watch mode — Automatically detect when a 5h limit resets and notify you
• JSON output — Structured output for AI agents (Hermes, Claude Code, etc.)
• Zero dependencies — Pure Python stdlib, no pip conflicts
• Cross-platform — Windows, macOS, and Linux
• No credential leakage — Tokens never printed; only official API endpoints are called

Install

pip install ai-limit-checker

Requires Python 3.10+. No external dependencies.

Quick Start

# Show all limits (default)
aichecker

# JSON output for AI agents / scripts
aichecker --json

# Compact one-liner (great for shell prompts / tmux status bars)
aichecker --oneline

# Check only one tool
aichecker --claude
aichecker --antigravity

# Ignore the 60s cache (force fresh API call)
aichecker --no-cache

Two command names are available — aichecker and ailimits — both invoke the same entry point.

Watch Mode

Watch mode polls usage every 5 minutes and automatically sends a ping to the CLI when a 5h limit window resets — triggering a fresh usage window so you can resume work immediately.

CLI

# Run continuously (polls every 5 min, pings on reset)
aichecker --watch

# Single check — perfect for cron jobs
aichecker --watch --once

# Customise poll interval and post-reset delay
aichecker --watch --interval 60 --delay 30

# Dry-run — log what would happen without calling the CLIs
aichecker --watch --once --dry-run

How it works:

1. Every poll, the tool records each 5h window's resets_at timestamp and used_pct
2. When now >= resets_at + delay (default 120s) and the window had usage > 0% before, a reset is detected
3. A trivial prompt ("hi") is sent to claude -p or agy -p to trigger a new 5h usage window
4. State is persisted to ~/.cache/ai-limit-checker/watch_state.json across restarts

The 2-minute delay ensures the server has fully refreshed before triggering.

Deduplication: if both Gemini and Claude/GPT groups on Antigravity reset at the same time, only one ping is sent to agy (they share the same 5h window on the same CLI).

Cron setup

For scheduled use, run a single check with --once:

# crontab — every 5 minutes
*/5 * * * * /usr/local/bin/aichecker --watch --once

The tool stays silent when no reset has occurred (empty stdout = nothing to report).

Programmatic API

from ai_limit_checker.watch import watch_5h_resets

# Built-in: pings the CLI and prints to stdout on reset
watch_5h_resets(once=True)

# Custom callback — send to Discord, Telegram, Slack, etc.
# (the CLI ping still happens automatically; this is for extra notifications)
def on_reset(reset_labels: list[str]) -> None:
    msg = f"🔄 Limits reset: {', '.join(reset_labels)}"
    send_to_discord(msg)  # your notification function

watch_5h_resets(on_reset=on_reset, interval=300, delay=120, once=True)

# Dry-run mode — log without calling the CLIs (for testing)
watch_5h_resets(once=True, dry_run=True)

Parameter	Type	Default	Description
on_reset	Callable | None	None	Callback receiving a list of reset window labels. If None, prints to stdout. The CLI ping happens regardless.
interval	int	300	Seconds between polls (when not --once).
delay	int	120	Seconds to wait after resets_at before triggering.
once	bool	False	Run a single check and exit (for cron/scheduled use).
dry_run	bool	False	Log what would happen without calling the CLIs.

JSON Output

aichecker --json

Returns structured JSON with all limits, remaining percentages, and reset timestamps. AI agents can parse this to plan task delegation based on remaining quota.

Example JSON structure

{
  "claude": {
    "status": "ok",
    "plan": "max",
    "five_hour": {
      "used_pct": 1.0,
      "remaining_pct": 99.0,
      "resets_at": "2026-06-29T16:31:00Z"
    },
    "seven_day": {
      "used_pct": 56.0,
      "remaining_pct": 44.0,
      "resets_at": "2026-07-02T05:00:00Z"
    }
  },
  "antigravity": {
    "status": "ok",
    "tier": "Google AI Ultra",
    "is_paid": true,
    "project_id": "my-project-12345",
    "groups": [
      {
        "name": "Gemini Models",
        "buckets": [
          {
            "window": "weekly",
            "label": "Weekly Limit",
            "used_pct": 0.0,
            "remaining_pct": 100.0,
            "remaining_fraction": 1.0,
            "resets_at": "2026-07-06T12:00:00Z"
          },
          {
            "window": "5h",
            "label": "Five Hour Limit",
            "used_pct": 0.0,
            "remaining_pct": 100.0,
            "remaining_fraction": 1.0,
            "resets_at": "2026-06-29T18:31:00Z"
          }
        ]
      },
      {
        "name": "Claude and GPT models",
        "buckets": [
          {
            "window": "weekly",
            "label": "Weekly Limit",
            "used_pct": 93.0,
            "remaining_pct": 7.0,
            "remaining_fraction": 0.07,
            "resets_at": "2026-07-02T12:00:00Z"
          },
          {
            "window": "5h",
            "label": "Five Hour Limit",
            "used_pct": 95.0,
            "remaining_pct": 5.0,
            "remaining_fraction": 0.05,
            "resets_at": "2026-06-29T12:50:00Z"
          }
        ]
      }
    ],
    "highest_used_pct": 95.0
  }
}

Example Output

🔍 AI CLI Usage Checker
2026-06-29 12:00:00

════════════════════════════════════════
  Claude Code (Max Plan)
════════════════════════════════════════
  ✅ Connected
  5h Window:  1.0% used (99.0% left) → resets in 4h 56m
  7d Window:  56.0% used (44.0% left) → resets in 2d 17h

════════════════════════════════════════
  Antigravity CLI
════════════════════════════════════════
  ✅ Connected
  Tier: Google AI Ultra
  Project: my-project-12345

  Gemini Models
    Weekly Limit:       0.0% used → resets in 6d 23h
    Five Hour Limit:    0.0% used → resets in 4h 59m

  Claude and GPT models
    Weekly Limit:      93.0% used → resets in 2d 20h
    Five Hour Limit:   95.0% used → resets in 19m

One-liner mode (--oneline):

Claude: 1.0% (5h) 🟢 | 56.0% (7d) 🟡 | Antigravity: 95.0% used 🔴

How It Works

Claude Code

1. Reads OAuth credentials from ~/.claude/.credentials.json (Windows/Linux) or macOS Keychain
2. Calls the official Anthropic usage API to get 5h and 7d window data

Antigravity CLI

1. Reads OAuth credentials from Windows Credential Manager (gemini:antigravity) or ~/.gemini/oauth_creds.json
2. Calls daily-cloudcode-pa.googleapis.com — the same endpoint the Antigravity desktop app uses
3. Fetches tier info via loadCodeAssist, then per-model-group quota buckets

Why daily- prefix? The base endpoint cloudcode-pa.googleapis.com always returns remainingFraction: 1 (100% remaining) regardless of actual usage. The daily- prefixed host returns real-time usage data that matches the desktop app's "Weekly Limit" / "Five Hour Limit" readouts.

Antigravity usage readouts

Usage is reported as % used, matching the Antigravity desktop app. Models are grouped (Gemini vs. Claude/GPT); within a group the weekly and five-hour windows are shared.

Tier note: loadCodeAssist returns two tiers. currentTier is the Cloud Code Assist API tier — always free-tier for consumer (non-GCP) accounts, regardless of any Google One AI subscription. paidTier carries the real subscription (e.g. Google AI Ultra) and only appears when one exists, so the tool prefers it. The raw API tier is still available as api_tier_id in --json output. Accounts with no Google One AI plan correctly show Antigravity (free-tier).

Why "Gemini Models" can sit at 0.0%: on a Google AI Ultra account the Gemini group is effectively unmetered — the server reports remainingFraction of exactly 1 no matter how much you use Gemini (verified against a run that consumed millions of Gemini tokens). Only the third-party group (Claude and GPT) is metered and moves. So a Gemini group stuck at 0.0% used after heavy Antigravity use is expected, not a bug. Genuinely tiny usage (under 0.1%) is shown as <0.1% used to distinguish it from an untouched 0.0% limit, and the raw remaining_fraction (0–1, full precision) is included per bucket in --json output.

Supported Tools

Tool	Metrics
Claude Code	5h window, 7d window, Sonnet/Opus breakdown
Antigravity CLI	Per-group weekly + five-hour limits, % used, reset time

Programmatic API

All functions are importable from ai_limit_checker:

from ai_limit_checker import check_claude, check_antigravity

# Check Claude Code usage
claude_result = check_claude()
print(claude_result["five_hour"]["used_pct"])

# Check Antigravity usage
agy_result = check_antigravity()
for group in agy_result.get("groups", []):
    print(group["name"])
    for bucket in group["buckets"]:
        print(f"  {bucket['label']}: {bucket['used_pct']}% used")

from ai_limit_checker.cli import gather, format_json, format_oneline

# Gather both tools at once (with 60s caching)
result = gather(do_claude=True, do_antigravity=True)
print(format_json(result))

CLI Reference

aichecker [OPTIONS]

Options:
  --json              Output structured JSON
  --oneline           Output a compact one-liner
  --claude            Check only Claude Code
  --antigravity       Check only Antigravity CLI
  --no-cache          Ignore the 60s result cache
  --watch             Watch mode: poll and ping CLI on 5h limit reset
  --once              Watch mode: single check (for cron)
  --interval SECONDS  Watch mode: poll interval (default 300)
  --delay SECONDS     Watch mode: delay after reset before triggering (default 120)
  --dry-run           Watch mode: log without calling the CLIs
  --version           Show version
  -h, --help          Show help

Development

git clone https://github.com/peetwan/ai-limit-checker.git
cd ai-limit-checker

# Install in editable mode with test dependencies
pip install -e ".[test]"
# or: pip install -e . && pip install pytest ruff

# Run tests
pytest

# Lint
ruff check src/ tests/

# Run locally
python -m ai_limit_checker --json

Testing

The test suite uses pytest with 86 tests covering:

• Credential parsing (Claude & Antigravity)
• API response parsing and normalization
• Output formatting (human, JSON, one-liner)
• Watch mode: reset detection, state persistence, CLI ping triggering, deduplication, dry-run
• Edge cases: missing credentials, API errors, unmetered groups, zero-usage rounding

pytest          # run all tests
pytest -q       # quiet mode
pytest -k watch # run only watch-mode tests

License

MIT © Peet Chanut

Links

• PyPI
• GitHub
• Issue Tracker