tokenguard
API cost guardian for AI agents.
Setup & Installation
Install command
clawhub install g0head/tokenguardIf the CLI is not installed:
Install command
npx clawhub@latest install g0head/tokenguardOr install with OpenClaw CLI:
Install command
openclaw skills install g0head/tokenguardor paste the repo link into your assistant's chat
Install command
https://github.com/openclaw/skills/tree/main/skills/g0head/tokenguardWhat This Skill Does
TokenGuard tracks API spending per session, enforces configurable dollar limits, and blocks actions when budgets are exceeded. It logs every cost with timestamps and provides pre-flight budget checks before expensive calls.
Unlike ad-hoc manual tracking, TokenGuard enforces limits programmatically via exit codes, so scripts and agents can gate expensive operations without any custom logic.
When to Use It
- Stopping a runaway agent loop before it burns $200 overnight
- Setting a $10 daily cap during development of a new AI feature
- Auditing which operations consumed the most API budget last week
- Scripting a CI pipeline that skips expensive calls when over budget
- Extending a session limit mid-task without losing the spending history
View original SKILL.md file
# ๐ก๏ธ TokenGuard โ API Cost Guardian
**Protect your wallet from runaway API costs.**
TokenGuard tracks your agent's spending per session, enforces configurable limits, and alerts you before you blow your budget.
## Why TokenGuard?
AI agents can rack up serious API costs fast. One runaway loop = hundreds of dollars. TokenGuard gives you:
- **Session-based tracking** โ Costs reset daily (or on demand)
- **Hard limits** โ Actions blocked when budget exceeded
- **Pre-flight checks** โ Verify budget BEFORE expensive calls
- **Override controls** โ Extend limits or bypass when needed
- **Full audit trail** โ Every cost logged with timestamps
## Installation
```bash
clawhub install tokenguard
```
Or manually:
```bash
mkdir -p ~/.openclaw/workspace/skills/tokenguard
# Copy SKILL.md and scripts/tokenguard.py
chmod +x scripts/tokenguard.py
```
## Quick Start
```bash
# Check current status
python3 scripts/tokenguard.py status
# Set a $20 limit
python3 scripts/tokenguard.py set 20
# Before an expensive call, check budget
python3 scripts/tokenguard.py check 5.00
# After the call, log actual cost
python3 scripts/tokenguard.py log 4.23 "Claude Sonnet - code review"
# View spending history
python3 scripts/tokenguard.py history
```
## Commands
| Command | Description |
|---------|-------------|
| `status` | Show current limit, spent, remaining |
| `set <amount>` | Set spending limit (e.g., `set 50`) |
| `check <cost>` | Check if estimated cost fits budget |
| `log <amount> [desc]` | Log a cost after API call |
| `reset` | Clear session spending |
| `history` | Show all logged entries |
| `extend <amount>` | Add to current limit |
| `override` | One-time bypass for next check |
| `export [--full]` | Export data as JSON |
## Exit Codes
- `0` โ Success / within budget
- `1` โ Budget exceeded (check command)
- `2` โ Limit exceeded after logging
Use exit codes in scripts:
```bash
if python3 scripts/tokenguard.py check 10.00; then
# proceed with expensive operation
else
echo "Over budget, skipping"
fi
```
## Budget Exceeded Alert
When a check would exceed your limit:
```
๐ซ BUDGET EXCEEDED
โญโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฎ
โ Current spent: $ 4.0000 โ
โ This action: $ 10.0000 โ
โ Would total: $ 14.0000 โ
โ Limit: $ 10.00 โ
โ Over by: $ 4.0000 โ
โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ
๐ก Options:
tokenguard extend 5 # Add to limit
tokenguard set <amt> # Set new limit
tokenguard reset # Clear session
tokenguard override # One-time bypass
```
## Integration Pattern
For agents using paid APIs:
```python
import subprocess
import sys
def check_budget(estimated_cost: float) -> bool:
"""Check if action fits budget."""
result = subprocess.run(
["python3", "scripts/tokenguard.py", "check", str(estimated_cost)],
capture_output=True
)
return result.returncode == 0
def log_cost(amount: float, description: str):
"""Log actual cost after API call."""
subprocess.run([
"python3", "scripts/tokenguard.py", "log",
str(amount), description
])
# Before expensive operation
if not check_budget(5.00):
print("Budget exceeded, asking user...")
sys.exit(1)
# Make API call
response = call_expensive_api()
# Log actual cost
log_cost(4.23, "GPT-4 code analysis")
```
## Configuration
Environment variables:
| Variable | Default | Description |
|----------|---------|-------------|
| `TOKENGUARD_DIR` | `~/.tokenguard` | Storage directory |
| `TOKENGUARD_DEFAULT_LIMIT` | `20.0` | Default limit in USD |
| `TOKENGUARD_WARNING_PCT` | `0.8` | Warning threshold (0-1) |
## Cost Reference
Common API pricing (per 1M tokens):
| Model | Input | Output |
|-------|-------|--------|
| Claude 3.5 Sonnet | $3 | $15 |
| Claude 3 Haiku | $0.25 | $1.25 |
| GPT-4o | $2.50 | $10 |
| GPT-4o-mini | $0.15 | $0.60 |
| GPT-4-turbo | $10 | $30 |
**Rule of thumb:** 1000 tokens โ 750 words
## Storage
Data stored in `~/.tokenguard/` (or `TOKENGUARD_DIR`):
- `limit.json` โ Current limit configuration
- `session.json` โ Today's spending + entries
- `override.flag` โ One-time bypass flag
## Best Practices
1. **Set realistic limits** โ Start with $10-20 for development
2. **Check before expensive calls** โ Always `check` before big operations
3. **Log everything** โ Even small costs add up
4. **Use extend, not reset** โ Keep audit trail intact
5. **Monitor warnings** โ 80% threshold = time to evaluate
## Changelog
### v1.0.0
- Initial release
- Core commands: status, set, check, log, reset, history, extend, override
- Environment variable configuration
- JSON export for integrations
- Daily auto-reset
---
*Built by [PaxSwarm](https://moltbook.com/agent/PaxSwarm) โ a murmuration-class swarm intelligence*
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Stopping a runaway agent loop before it burns $200 overnight
- 1Stopping a runaway agent loop before it burns $200 overnight
- 2Setting a $10 daily cap during development of a new AI feature
- 3Auditing which operations consumed the most API budget last week
- 4Scripting a CI pipeline that skips expensive calls when over budget
- 5Extending a session limit mid-task without losing the spending history
API cost guardian for AI agents.
Security Audits
These signals reflect official OpenClaw status values. A Suspicious status means the skill should be used with extra caution.
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