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

With no annotations, the description carries the transparency burden. It discloses that the tool outputs settings with measurement rationale or an explicit 'none exists' note, and it warns about output file size variation (8.5% to 100%) depending on a setting. This is meaningful behavioral disclosure, though it doesn't explicitly state the tool is read-only.

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 sentences: function, usage, and rationale. Every sentence earns its place, no fluff. The key information is 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?

The description explains what the tool returns, how to use it, and why timing matters. For a simple one-parameter tool with no output schema, this is complete enough for an agent to correctly invoke it and interpret results.

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?

The schema covers the parameter and enum values 100%, but the description adds context: purpose values are listed and the choice matters because source kind is known before capturing. This goes beyond the schema's 'what the capture is for' and justifies the parameter.

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 clearly states the tool recommends capture settings for a given purpose, with specifics about what is returned (measurement or explicit note). It distinguishes from siblings like extract_citation and get_measurement_data by focusing on pre-capture settings recommendation.

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?

It explicitly says 'Use before capturing' and explains why the timing matters (source kind known now, not afterwards). While it doesn't name alternative tools, the context and purpose are clear enough for an agent to decide when to invoke this tool.

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