session-costAnalyze OpenClaw session logs to report token usage, costs, and performance metrics grouped by agent and model. Use when the user asks about API spending, to...
Install via ClawdBot CLI:
clawdbot install khaney64/session-costGrade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Mar 1, 2026
Development teams building AI applications can use this skill to track API spending across different models and sessions. This helps identify expensive models, optimize prompts, and manage budgets by analyzing token usage patterns over time.
Independent consultants offering AI services can generate detailed usage reports for clients. The session breakdown helps justify costs, demonstrate work volume, and provide transparent billing based on actual API consumption.
Large organizations deploying AI across departments can monitor usage by provider and model. This enables cost allocation, compliance tracking, and optimization decisions while maintaining oversight of AI expenditures.
Research institutions can analyze experimental sessions to compare model performance and costs. The detailed metrics help evaluate cost-effectiveness of different approaches and justify research budgets.
SaaS companies embedding AI features can track per-customer usage patterns. This helps with pricing strategy, resource planning, and identifying high-value customers based on their AI consumption.
Companies can implement pay-per-use pricing by tracking exact API consumption through session logs. This allows transparent billing where customers pay only for the tokens they actually use, with detailed breakdowns available.
Offer this tool as a service to help businesses monitor and optimize their AI spending. Provide analytics dashboards, cost alerts, and optimization recommendations based on session analysis.
Integrate this analysis capability into existing development tools or platforms. Offer it as a premium feature for teams needing advanced cost tracking and optimization insights.
💬 Integration Tip
Start by running basic summaries to understand usage patterns, then use filters like --offset and --provider to focus on specific time periods or models for deeper analysis.
Scored May 18, 2026
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