Compare positional scarcity

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains the conceptual output (steepness of dropoff) but does not describe the exact return format (e.g., a table, numeric scores per position, or how it is presented). It also omits mention of any edge cases (e.g., default scoring format handling). For a simple read-only analytics tool, this is adequate but not richly transparent.

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 description is two sentences with no waste. The first sentence front-loads the core definition, and the second gives a concrete usage example. Every word serves a purpose, making it highly concise and well-structured.

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?

The tool is simple (one parameter) and the description explains its purpose and use case. However, without an output schema, the agent is left to infer the response structure. Given the conceptual clarity and the example, it's mostly complete, but a mention of the expected output format would make it fully self-sufficient. The description adequately distinguishes it from siblings like get_rankings or compare_players.

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% because the sole parameter 'scoring_format' is fully documented with an enum, default value, and explanation. The description adds no additional information about the parameter, so the baseline of 3 applies per the rubric.

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 does: measures the steepness of fantasy dropoff at each position for a given scoring format, defined from top player to replacement level. It uses specific terms like 'dropoff' and 'replacement level' and distinguishes itself from siblings like get_rankings or compare_players by focusing on scarcity across positions.

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 provides a concrete use case: 'draft-strategy questions like whether to take a running back or a wide receiver first.' This gives clear context for when to use it, though it doesn't explicitly name alternatives or state when not to use it. Since the tool is focused on scarcity, the example effectively implies its niche.

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