ebi-pdbe-sum_qsvsqse_id_40d9190e

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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false), so the description's added value is the edge-case behavior it discloses: a contributing percentile of 0 forces the harmonic mean to 0, and all-unavailable percentiles yield null. The experiment_data_available flag is also explained. That is genuine behavioral context beyond the annotations, though it says nothing about permissions or response shape.

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 bulleted metric breakdown is scannable, but the lead sentence defines what the scores are rather than what the tool does, so the most decision-relevant information is not front-loaded. The content is dense rather than padded, but it duplicates the annotation title verbatim.

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?

With no output schema, the description usefully documents the returned fields and their null/zero behavior, which is the right thing to spend words on. It is still incomplete as a tool definition because it never states the operation or when to select it among 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?

Schema description coverage is 100% and there is a single required pdb_id already documented as a 4-character PDB id code. The description adds no parameter meaning at all, so the baseline 3 applies.

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 explains the semantics of three named output fields (geometry_quality, data_quality, overall_quality) but never states the action itself — that this tool retrieves quality scores for a given PDB entry. An agent can infer the resource (per-structure quality metrics) but not the verb, and nothing distinguishes it from the many other per-PDB-ID sibling tools such as key_val_stats or outliers.

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?

There is no when-to-use guidance, no mention of when a different sibling tool is preferable, and no statement of prerequisites. With ~50 sibling tools keyed on the same identifier, the absence of any routing signal is a real gap.

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