Observability & Evaluation · Software component
Tool Usage Analyzer
Software componentObservability & EvaluationObservability & Evaluationarc:ToolUsageAnalyzer
An analytics component that monitors production tool-call patterns to detect overuse, underuse, redundant calls, and poor tool selection.
Responsibility. Detects inefficient or incorrect tool usage patterns.
Also known as: Tool usage monitoring, Tool audit pattern analysis
Relationships
reads dependency
evaluates assurance
monitors assurance
Design guidance
- SHOULD monitor tool usage in production and optimise configurations from the data.
- SHOULD analyse patterns across thousands of invocations: frequent wrong-tool choices, parameter-error clusters, and per-tool hallucination rates.
- SHOULD feed findings into documentation improvement cycles for frequently misunderstood tools rather than treating auditing as error detection only.
Quantitative guidance
As stated by the sources; verify before use.
- Tool overuse rate can reach 50% or higher (Ch1.2).
Classification
- Patterns
- Documentation-accuracy feedback loop
- Quality attributes
- Cost efficiencyMaintainability (ISO/IEC 25010)
- Risks mitigated
- Tool overuseTool underusePoor tool selection
Sources
- Ch1.2: T. Nguyen, "Core Agent Patterns," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 1.2. ISBN: 9798244538229.
- Ch3.7: T. Nguyen, "Tool Usage Auditing," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 3.7. ISBN: 9798244538229.
- Ch4.1: T. Nguyen, "Introduction to AI Agent Deployment and Scaling," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 4.1. ISBN: 9798244538229.
- Ref3.10: "Powering the Next Generation of AI Agents," unpublished reference note (10-Powering-Next-Generation-AI-Agents.md), Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam supplementary materials, 2026. unpublished note