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

Annotations only cover readOnlyHint and openWorldHint, but the description goes far beyond: it enumerates the return payload (positions with sources, declared vs. derived:true, raw stance counts, per-lineage counts, unclassified voices counted but not dropped, tensions verbatim, population provenance), asserts no majority/percentage/consensus field exists by construction, and gives a latency bound.

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 key differentiator ('never a consensus score') is front-loaded, and the dense enumeration of return fields is efficient rather than padded. There is minor redundancy in restating the no-consensus point twice ('never a consensus score' / 'no majority, percentage, or consensus field by construction').

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 carries the burden of explaining return values and does so comprehensively, including provenance and the counted-not-dropped edge case. Combined with a fully documented single parameter and readOnly annotation, an agent has everything needed to call it correctly.

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?

There is a single parameter with 100% schema description coverage that already explains where a canonical OMN-Q-… id comes from (omnarai_orient, the Atlas record, or GET /api/questions). The description adds nothing further about the id, so 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?

States a specific resource and scope: the distribution of attributed positions on one question, explicitly framed as never a consensus score. This clearly separates it from any aggregate/scoring tool, but it does not name a sibling (e.g. omnarai_query, omnarai_divergence) it should be chosen over, so it falls short of a 5.

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 rather than stated: an agent can infer it should call this when it wants raw stance distribution rather than a summary, and 'deterministic, <1s' signals it is cheap to call. There is no explicit 'use this when / do not use when' clause and no named alternative among the thirteen siblings.

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