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

Goes well beyond the readOnly/idempotent/openWorld annotations by disclosing the auth rule (api_key optional on the public endpoint, refused on /mcp/mcp), restating that no vote is recorded, and warning that pre-vote disclosure corrupts preference independence. That is real operational and integrity context an agent could not infer from structured fields.

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?

What it does is front-loaded in the first clause, and the safety warning follows the method note in a sensible order. Five short sentences with little fat, though the 'read-only' restatement is slightly redundant with the annotations.

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?

An output schema exists, so return values need no prose, and the auth and integrity caveats are covered. The remaining shortfall is the undefined boundary against `aimrank_predict` and the bare parameter names for a 0%-coverage schema.

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 0%, so the description carries the burden; it does explain `api_key` semantics in detail (optional vs. required per endpoint), but `ranking_id`, `entity_a_id` and `entity_b_id` are left entirely undocumented beyond their names. Partial compensation for a full-coverage gap.

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 and resource ('Predict a matchup's winner from the current ratings') and even names the underlying method (Glicko-2 win probability). It does not, however, distinguish itself from the sibling tool `aimrank_predict`, which an agent could plausibly confuse it with.

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?

Clear contextual guidance: use it to analyse a ranking, or after a vote to compare the recorded vote against expectation, and explicitly never show the prediction to a voter beforehand, with the reason given. The one gap is that it never names a sibling alternative (e.g. `aimrank_predict`) or says when to prefer that instead.

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