Token Tamer — AI API Cost Control

Monitor, budget, and optimize AI API spending across any provider. Tracks every call, enforces budgets, detects waste, provides optimization recommendations.

This appears to be a local, instruction-driven cost tracker that matches its description. Before installing: 1) Copy and edit config_example.py to set USAGE_FILE to a safe location you control; do not leave paths pointing to root or other sensitive dirs. 2) Ensure all your application API calls call tamer.log_usage()/check_before_call() if you want enforcement — the tool does not intercept calls automatically. 3) Back up the USAGE_FILE if you need history and avoid concurrent writes (multiple processes may corrupt the JSON). 4) Note the kill switch is process-local (resets on restart) and webhook/export fields are present in config_example but not active by default — review any future changes that enable network exports. 5) If you need team-wide or multi-host tracking, migrate to a DB or central exporter (the skill is intentionally local-only). Overall the package is coherent and does not request unrelated secrets or perform hidden network activity.

Type: OpenClaw Skill Name: token-tamer Version: 1.1.0 The 'Token Tamer' skill bundle is a utility designed to track and optimize AI API costs by logging usage to a local JSON file. The code (token_tamer.py, token_reports.py, token_optimizer.py) uses only Python standard libraries and performs legitimate operations such as cost calculation, budget enforcement, and report generation. No evidence of data exfiltration, malicious execution, or prompt injection was found; the file access is limited to the configured usage log, and the documentation accurately reflects the code's functionality.