optimize_context_structured

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

No annotations are provided, and the description does not disclose any behavioral traits (e.g., whether it modifies state, permissions needed, side effects). It only mentions output format, which is already in the schema.

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?

The description is very short, but this results from under-specification rather than efficient communication. Every sentence should add value; here, the second sentence merely restates a parameter default.

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 complexity (4 parameters, no output schema, multiple siblings), the description is completely inadequate. It does not explain the tool's purpose, behavior, or when to use it, leaving the agent without essential information.

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?

Schema description coverage is 0%. The description only mentions the output_format parameter, but adds no further meaning to any of the four parameters. This is a significant gap; the description fails to compensate for the lack of schema documentation.

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?

The description states 'Full pipeline with structured JSON output mode' but does not specify what the pipeline does. It lacks a clear verb and resource, making it vague. Compared to calibration, this is above a tautology but still minimal.

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 its siblings (optimize_context_batch, optimize_context_stream, optimize_context_tool). The description provides no context for tool selection.

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