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

With no annotations, the description carries the full behavioral burden. It does not state whether this requires a license/api_key, whether it is a pure computation or a server call, how peaks input should be formatted, or how tolerance is applied. Only the basic transformation is conveyed.

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?

A single front-loaded sentence with no filler, immediately establishing verb and resource. Appropriately sized, though its brevity is partly under-specification rather than economy.

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?

An output schema exists, so return values need not be explained, but for a 4-parameter tool with 0% schema coverage and no annotations the description is too thin: input formats, the tolerance parameter, and authentication are all unaddressed.

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%, so the description must compensate. It only loosely implies that 'structure' maps to smiles and 'measured peaks' maps to peaks; it says nothing about api_key or tolerance_ppm, and gives no format/syntax for the peaks array.

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?

States a specific verb (annotate) and resource (measured MS/MS peaks against predicted fragments for a structure), which clearly distinguishes it from sibling covams_fragment_predict (prediction) and covams_process_spectrum. Clear but does not explicitly name the alternative it differs from.

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 when-to-use or when-not-to-use guidance, and no mention of the natural alternative covams_fragment_predict when the agent needs fragments generated rather than labeled. The agent must infer the workflow context.

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