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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds behavioral context beyond those: it explains the measurement method ('dropoff from top player to replacement level') and indicates dependence on scoring format. This is consistent with the annotations and adds useful nuance about what the tool computes.

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 sentences, both purposeful and front-loaded. The first defines the metric and its measurement basis; the second gives a concrete use case. No filler or repetition of schema details. Every word earns its place.

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 simple one-parameter tool with an output schema, the description covers the core concept and typical use. It does not describe what positions are included or how the output is structured, but the output schema handles the latter, and the tool is conceptually straightforward. A minor gap: it doesn't mention that the default scoring_format is half_ppr, but the schema covers that. Overall, sufficient for correct invocation.

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?

The schema provides 100% coverage for the single parameter scoring_format, including descriptions of each enum value and its default. The tool description does not add any parameter-specific details beyond mentioning 'in a given scoring format'—which is already implicit. Since the schema handles the semantics fully, a baseline 3 is appropriate.

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?

The description clearly states what the tool computes: 'How steep the fantasy dropoff is at each position in a given scoring format, measured from the top player to replacement level.' It gives a specific verb ('compare' per title) and resource ('positional scarcity'), and distinguishes it from sibling tools like compare_players by focusing on scarcity rather than direct player comparison. The example use case further pins down its intent.

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?

The description explicitly says 'Use this for draft-strategy questions like whether to take a running back or a wide receiver first,' which provides clear when-to-use guidance. It does not mention alternatives or exclusions (e.g., 'for direct player comparison use compare_players'), so it lacks explicit sibling differentiation, but the intended use case is clear enough for an agent to route correctly.

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