ensemble_spread_view

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

Goes well beyond the annotations by disclosing the mechanism (RMSD written into the B-factor column) and a substantial interpretive caveat that the value is not a calibrated uncertainty or error bar. The annotations alone (readOnlyHint=false, idempotent=true) would not tell an agent that existing B-factors are overwritten or that a restore_bfactors sibling exists to undo it, which is the remaining gap.

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?

Front-loaded with the action in the first sentence, then the mechanism, then the interpretive caveat as its own paragraph. Three short blocks, each earning its place, with no repetition of schema fields.

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?

For a two-parameter visualisation tool with a full schema description, complete annotations, and an output schema that removes the need to describe returns, this covers action, mechanism, and interpretation. Nothing an agent needs in order to call it correctly is absent.

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 the baseline is 3, but the description adds genuine meaning not in the schema: the colour ramp direction (blue = rigid, red = variable) and that as_putty makes spread read as tube width as well as colour. The one required parameter's type expectation (multi-state object) is also reinforced in prose.

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 pair (colour, thicken), the target resource (multi-state object), and the exact quantity driving it (per-residue RMS deviation across states), plus where the value is stored (B-factor column). This makes it distinguishable from the neighbouring bfactor_view, putty_view, and conservation_view without opening any schema.

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?

Usage is implied by the phrase 'multi-state object' and the schema note about NMR/EM ensembles, so an agent can infer it applies to ensembles rather than single models. However, it never explicitly says when to prefer this over the many sibling *_view tools that also map a scalar onto B-factors and colour (bfactor_view, putty_view, occupancy_view), and no exclusion or prerequisite is stated.

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