sum_qsvsqse_id_40d9190e

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered; the description goes further by disclosing the harmonic-mean construction and, critically, the edge-case behavior (score is 0 if any contributing percentile is 0, null if all percentiles are unavailable) plus the meaning of experiment_data_available. That is meaningful behavioral context beyond the structured fields, though it omits any hint about how the metrics are grouped in the response.

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 readable and reasonably compact, but it is a data dictionary rather than a front-loaded purpose statement — the first clause describes return-value math instead of what the tool does, wasting the most valuable position.

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 one read-only parameter and no output schema, the definition is nearly adequate because it explains the returned fields thoroughly. However, it never says the result is keyed to the supplied pdb_id or what the overall response shape is, leaving the agent to reconstruct the tool's contract from metric definitions alone.

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?

Only one parameter exists and schema coverage is 100%, so the schema fully documents 'pdb_id' (4-character PDB id code). The description adds nothing about the parameter, so the baseline of 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 text never states the tool's action (e.g., 'retrieve quality scores for a PDB entry'), it only defines what the returned scores mean. An agent can infer the resource (macromolecular structure quality metrics) from the metric names, but there is no explicit verb+resource statement and no differentiation from the many sibling entry-id tools.

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 statement of when to use this tool versus the numerous sibling tools that also take an id. No prerequisites, no scope notes, no alternative routing guidance — the agent must infer usage entirely from the metric semantics.

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