qscore_view

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

Annotations already declare openWorldHint=false and idempotentHint=true, and the description reinforces this with 'no network, no map, no computation' and clarifies that values are read rather than re-derived. The note that real Q-scores go negative is genuinely useful behavioral context that no structured field carries. It does not state that B-factors are overwritten and recovered, leaving that to the schema's preserve_bfactors parameter.

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?

Purpose is front-loaded in the first sentence and the remaining paragraphs are caveats that earn their place. Slightly verbose in phrasing ('which is the common case for older EM structures'), but there is no filler or repetition.

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 an output schema present, 100% parameter coverage, and annotations covering the safety profile, the description only needs to explain the data caveats, which it does. The pre-2023 empty-result case is the key operational fact an agent needs and it is stated.

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%, so obj_name, validation_path, and preserve_bfactors are already fully documented. The description only incidentally touches validation_path by referring to the parsed report; it adds no format, path, or default guidance beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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 (colour), a specific resource (a model), and a specific data source (per-residue Q-score from a wwPDB validation report). That metric provenance distinguishes it cleanly from lookalike siblings such as plddt_view, bfactor_view, and occupancy_view without naming them.

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?

Provides a real usage condition: entries deposited before the September 2023 validation rollout carry no Q-scores, which is common for older EM structures. It does not explicitly route to an alternative view for those cases or name when-not-to-use-this, so it falls short of a 5.

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