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

No annotations are provided, so the description carries the full disclosure burden. 'In parallel' hints at concurrency, but nothing states the effect of max_workers, what enable_sota or scoring_backend do, whether API credentials are required, or how failures in a batch are reported.

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 naming the operation, the batching behavior, and the domain. Nothing is padded and the key scoping detail comes first.

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 6-parameter tool with zero schema-coverage and no annotations the description is far too thin. An agent has no basis for choosing databases, tuning parallelism, or understanding scoring_backend.

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% across 6 parameters, so the description must compensate and largely does not. 'In parallel' loosely gestures at max_workers, but spectra, databases, enable_sota, scoring_backend, and api_key are left completely undocumented in both the schema and the description.

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 ('Identify') and resource ('multiple spectra') and clarifies the batch scope with 'batch mode for LC-MS/MS runs', which implicitly distinguishes it from the singleton covams_identify. It stops short of naming the single-spectrum sibling explicitly, so an agent must infer the pairing from the name.

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?

'batch mode for LC-MS/MS runs' implies the usage context (many spectra from one run) but gives no explicit when-to-use vs. covams_identify, no exclusions, and no prerequisite guidance. Usage is inferable but not stated.

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