Retrieve real stint breakdowns, tire compounds, and finish positions from past F1 races at a specific circuit to inform strategy decisions.
Real stint breakdown (compound, start/end lap) and finish position from past race sessions at this circuit.
| Name | Required | Description | Default |
|---|---|---|---|
| circuit | Yes | ||
| drivers | No | ||
| seasons | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It communicates that the data is historical, real, and circuit-scoped, but it does not clarify default behavior for optional drivers or seasons filters, nor any other operational constraints.
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 a single, front-loaded sentence with no filler. Every part contributes useful information about what the tool returns and its scope.
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 output schema covers return shape, so that is not a gap. However, with no annotations and minimal usage or parameter-filter guidance, the description is only adequate for safe selection and invocation, not fully self-sufficient.
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 compensate. It only maps the 'circuit' parameter via 'at this circuit'; 'drivers' and 'seasons' are left undocumented in both the schema and the description, even though their names suggest filtering behavior.
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 names a specific resource: real stint breakdown including compound and start/end lap, plus finish position, scoped to past race sessions at a circuit. It clearly separates this from sibling simulation/prediction tools by emphasizing 'real' and 'past' data.
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 phrase 'past race sessions at this circuit' implies the tool is for historical data, but it does not explicitly say when to prefer it over siblings such as simulate_undercut_overcut or predict_finish_position. No exclusions or alternative-routing guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.