read_optimization

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

The description merely repeats 'Read' with no additional behavioral context beyond the annotation readOnlyHint=true. It adds no insight into permissions, side effects, or response format.

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?

Extremely concise at one sentence. It is not verbose, but the conciseness comes at the cost of missing useful information. Still, it is well-structured and front-loaded.

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 simplicity of a read operation and the presence of an output schema, the description is minimally adequate. However, it could mention the required optimizationId or hint at the tool's purpose relative to siblings.

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?

Description does not mention the single required parameter (optimizationId) and provides no parameter guidance. Schema coverage is 0%, so the description fails to compensate for missing parameter semantics.

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?

Description states 'Read an optimization' which is a clear verb-resource pair. However, it does not differentiate itself from sibling tools like read_backtest or read_project, which have similar structure.

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?

No guidance on when to use this tool versus alternatives such as list_optimizations or update_optimization. The description fails to provide any usage context or exclusions.

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