An agent's tool calls often fail on bad arguments. What improves this most?
Why B is the answer
Precise tool schemas and descriptions, with validation
Clear schemas guide the model, and validation catches what slips through.
In detail
- Precise schemas help the model, and validation catches the rest.
- Say what each argument means.
Use case
An illustrative scenario, not a real incident.
An agent passes dates in the wrong format. A clear schema and a validation check stop that.
See it in different ways
sequenceDiagram participant M as Model participant A as Application participant T as Tool M->>A: Tool name and arguments A->>A: Validate arguments A->>T: Call T-->>A: Result or error A-->>M: Result as context
sequenceDiagram participant M as Model participant A as Application participant T as Tool M->>A: Tool name and arguments A->>A: Validate against the schema A->>T: Run, with an idempotency key T-->>A: Short result or clear error A-->>M: Result as context
flowchart LR S0["Precise schema"] --> S1["Model calls tool"] --> S2["Validate arguments"] --> S3["Run"]
Key point: Schemas guide, and validation catches.
Why the other options are wrong
- A. A bigger GPU so the model can reason over more tool options
- A GPU does not fix arguments.
- C. More agents in the system so that each can check the others
- More agents add cost, not correctness.
- D. A higher temperature so the model tries other arguments
- Temperature adds randomness.