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

With no annotations, the description carries the full behavioral disclosure burden. It does well by specifying data sources (official FPL API for fpl-check), pricing for each endpoint, and the content of each response (e.g., 'team form, H2H, injuries, xG comparison'). It does not reveal response format, rate limits, or authentication, but given the breadth of endpoints, the description offers substantial transparency.

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 front-loaded with a clear one-sentence summary, then uses a structured bullet list for endpoints. Each bullet includes the action name, price, and a brief description. While the list is long (11 items), it is dense with unique, non-redundant information. The structure is easy to scan, though slightly longer than strictly necessary.

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?

Given the tool's complexity (22 parameters, multi-action dispatcher), the description is remarkably complete: it lists all endpoints and their expected outputs (e.g., 'clean sheet probability — GK stats, defensive metrics, BTTS probability'). It does not provide an output schema, but the endpoint descriptions effectively inform the agent of return content. It lacks a general note on response format or error handling, but overall it covers the essential context.

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 descriptions for most parameters are tautological (e.g., 'away', 'home', 'date'), providing no real meaning. However, the tool description adds crucial semantics for key parameters: 'action' is fully explained with an enum list, 'player' is described as 'for deep check', 'position' is explained as 'ranked shortlist mode', and 'max_price' as 'budget cap'. Despite this, many parameters remain undefined in both schema and description, so the description only partially compensates for the shallow schema.

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 purpose: 'Football/soccer intelligence for fans, fantasy managers, and betting analysts.' It then enumerates 11 specific endpoints (fpl-check, match-preview, value-bets, etc.), each with a distinct function. This goes far beyond a mere restatement of the name and effectively distinguishes it from sibling tools like racingpulse or marketpulse by its football-specific scope.

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 implicitly defines usage context by covering all football/soccer intelligence needs (FPL, match previews, betting, transfers). It does not explicitly name alternatives or state when not to use the tool, but the endpoint list provides clear scenarios for each action. However, there is no 'use this instead of X' guidance, so it stops short of a 5.

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