calibration

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark the tool as read-only and idempotent. The description adds context about the report's computation and interpretation, which goes beyond the annotations. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences, each with a clear function: definition, motivational question, scope instructions. No superfluous text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the optional parameters and presence of an output schema, the description fully explains what the tool does and how to filter. No missing information needed for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With no schema description coverage (0%), the description compensates by naming the three scope parameters (diagnostic, tag, intervention) and explaining their role in filtering. Does not specify formats or constraints, but provides essential meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly defines the tool as a prediction-accuracy report, specifying it computes the fraction of experiments where predicted direction equals observed direction. The description directly answers 'where is my intuition miscalibrated?', distinguishing it from sibling tools like 'recall' or 'list_interventions'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

States the tool can be scoped by diagnostic, tag, or intervention, providing clear usage context. Does not explicitly mention when not to use or alternatives, but the purpose is sufficiently specific for an AI agent to infer appropriate usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.