livefpl_player_prediction

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

With no annotations provided, the description carries the burden of behavioral disclosure. It covers major behaviors: accepts partial/case-insensitive names, returns JSON with matching predictions, returns all matches if ambiguous, and raises an error if no match. It also clarifies that the output is a prediction, not an actual price change. Minor omissions like rate limits or authentication are not critical for a simple query tool.

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 concise and well-structured: a one-sentence purpose followed by Args and Returns sections. Every sentence adds value—there's no filler. The most important information (the function) is front-loaded, and the format is easy to parse.

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, the description is largely complete. It covers the input, the return behavior (matches, ambiguity, errors), and examples. Since an output schema exists, it doesn't need to detail the JSON structure. It could mention potential rate limiting or authentication, but these are not essential for basic usage, so a 4 is appropriate.

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 must fully explain the parameter. It does so effectively: 'name: Full or partial player name (case-insensitive, e.g. "Haaland", "Calafiori", "salah")' provides clear semantics, examples, and the flexibility of partial matches. This is strong compensation for the missing schema description.

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 the tool's function: 'Get the price-change prediction for a specific FPL player by name.' It specifies the verb (get), resource (price-change prediction), and unique context (by player name), effectively distinguishing it from sibling tools like livefpl_price_risers or livefpl_top_transfers that address different queries.

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 explicit: the description indicates you'd use this when you need a specific player's price prediction, but it doesn't contrast with alternatives or state when not to use it. There's no 'use this for X, otherwise use Y' guidance, so the agent must infer when this is the right tool among the listed siblings.

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