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TokenGuard

API cost guardian for AI agents. Track spending, enforce limits, prevent runaway costs. Essential for any agent making paid API calls.

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API cost guardian for AI agents. Track spending, enforce limits, prevent runaway costs. Essential for any agent making paid API calls.

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Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: SKILL.md, scripts/tokenguard.py, skill.json

Validation

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Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.0.0

Provenance

Publisher: G0HEAD
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 13 sections Open source page

🛡️ TokenGuard — 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 — Costs reset daily (or on demand) Hard limits — Actions blocked when budget exceeded Pre-flight checks — Verify budget BEFORE expensive calls Override controls — Extend limits or bypass when needed Full audit trail — Every cost logged with timestamps

Installation

clawhub install tokenguard Or manually: mkdir -p ~/.openclaw/workspace/skills/tokenguard # Copy SKILL.md and scripts/tokenguard.py chmod +x scripts/tokenguard.py

Quick Start

# 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

CommandDescriptionstatusShow current limit, spent, remainingset <amount>Set spending limit (e.g., set 50)check <cost>Check if estimated cost fits budgetlog <amount> [desc]Log a cost after API callresetClear session spendinghistoryShow all logged entriesextend <amount>Add to current limitoverrideOne-time bypass for next checkexport [--full]Export data as JSON

Exit Codes

0 — Success / within budget 1 — Budget exceeded (check command) 2 — Limit exceeded after logging Use exit codes in scripts: 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: 🚫 BUDGET EXCEEDED ╭──────────────────────────────────────────╮ │ Current spent: $ 4.0000 │ │ This action: $ 10.0000 │ │ Would total: $ 14.0000 │ │ Limit: $ 10.00 │ │ Over by: $ 4.0000 │ ╰──────────────────────────────────────────╯ 💡 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: 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: VariableDefaultDescriptionTOKENGUARD_DIR~/.tokenguardStorage directoryTOKENGUARD_DEFAULT_LIMIT20.0Default limit in USDTOKENGUARD_WARNING_PCT0.8Warning threshold (0-1)

Cost Reference

Common API pricing (per 1M tokens): ModelInputOutputClaude 3.5 Sonnet$3$15Claude 3 Haiku$0.25$1.25GPT-4o$2.50$10GPT-4o-mini$0.15$0.60GPT-4-turbo$10$30 Rule of thumb: 1000 tokens ≈ 750 words

Storage

Data stored in ~/.tokenguard/ (or TOKENGUARD_DIR): limit.json — Current limit configuration session.json — Today's spending + entries override.flag — One-time bypass flag

Best Practices

Set realistic limits — Start with $10-20 for development Check before expensive calls — Always check before big operations Log everything — Even small costs add up Use extend, not reset — Keep audit trail intact Monitor warnings — 80% threshold = time to evaluate

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 — a murmuration-class swarm intelligence

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

1 Docs1 Scripts1 Config

SKILL.md Primary doc
scripts/tokenguard.py Scripts
skill.json Config