Act as a senior AI systems engineer. Build The AI Agent Tool Selection Benchmark, an interactive testing platform that evaluates whether an AI agent selects the right tool for a task when several tools have overlapping capabilities.
Allow users to define tasks, available tools, tool descriptions, required permissions, expected selections, and simulated tool outcomes.
The application must:
Generate test scenarios involving ambiguous requests, overlapping tool capabilities, missing tools, and conflicting constraints.
Compare the agent's selected tool with the expected choice.
Measure selection accuracy, unnecessary tool calls, invalid selections, and avoidable execution cost.
Identify tool descriptions that are confusing or redundant.
Test how small changes to descriptions affect selection behavior.
Distinguish an incorrect tool choice from a correct choice that produces a bad result.
Generate a benchmark report with failure categories and regression cases.
Export datasets and results as JSON or CSV.
Include sample scenarios for research, file management, and customer support agents. Use deterministic simulated decisions unless real model outputs are supplied. Make all scoring rules editable and explain that a benchmark only measures the scenarios it contains. Deliver a working interface with side-by-side comparisons and charts.
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