price_predictions

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

With no annotations provided, the description carries the full burden. It states the tool's purpose (price prediction) and implications for user actions, but it lacks details on how predictions are made, update frequency, data sources, or any limitations. For a prediction tool, more behavioral context would be beneficial.

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 extremely concise (3 sentences). The first sentence states the purpose, the second gives usage triggers, and the third provides actionable advice. Every sentence earns its place with no redundancy or filler.

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 has no parameters, no annotations, and no output schema, the description is the sole source of information. It covers purpose and usage adequately but fails to describe the output format or any technical details (e.g., whether results are a list, probabilities, etc.). This leaves the agent with incomplete guidance on how to handle the tool's response.

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 tool has zero parameters, so the description does not need to explain any. Schema coverage is 100%, and the description adds no param-specific info, which is appropriate. Baseline for 0-param tools is 4.

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 predicts which FPL players are likely to rise or fall in price. It uses specific verbs ('predict', 'rise', 'fall') and identifies the resource ('FPL players'). This distinguishes it from sibling tools like transfer_suggestions or squad_scout, which do not focus on price predictions.

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 provides example user queries that should trigger this tool ('Who's about to rise in price?', etc.) and explains the consequence of using it ('Buy before a rise...'), giving clear context. However, it does not mention when not to use the tool or suggest alternatives, which keeps it from a top score.

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