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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower. The description still adds real behavioral context: the ranking is defined by MissedTakes Score (skill vs a naive baseline), provisional records are unranked, and the ranking scope changes when a slug is supplied.

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?

Two dense but front-loaded sentences; the identity, returned fields, and ranking caveat come before the optional parameter guidance. Every clause carries information, though the second sentence is slightly overloaded with the slug discovery hint.

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 compensates by naming the columns returned and the ranking rule, and it covers the optional parameter's purpose. An agent has enough to call this correctly and interpret the result.

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 coverage is 100%, so baseline is 3, but the description goes further: it defines what a prediction type slug means conceptually ('rank within one kind of claim'), gives a concrete example (mock drafts), and routes the agent to find_entities, kind prediction_type, to discover slugs.

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+resource (ranked NFL pundit leaderboard) and enumerates the returned rows — MissedTakes Score, accuracy, graded takes, articles. Anchoring it to 'the same rows missedtakes.co/nfl/leaderboard prints' makes the scope unambiguous and implicitly separates it from the single-entity sibling pundit_record.

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?

Explains the one usage variation (pass a typeSlug to rank within one claim kind, e.g. mock drafts) and notes that provisional records under ten graded articles are excluded. However, it never says when to reach for this versus pundit_record, outlet_record, or list_takes, so alternative selection is left to inference.

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