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ellettie

iRacing MCP Server

get_leaderboard

Retrieve real-time iRacing leaderboard with positions, gaps, lap times, and driver info. Automatically filters out non-competitors like pace car and missing starts for accurate rankings.

Instructions

get leaderboard

Note: When filtering for competitive leaderboard results, exclude entries where: 1. if driver_name="Pace Car" (not a competitor. so ignore this row from leaderboard) 2. if is_missing_start=True (indicates missed start. so this car is not correct position) 3. if is_towing=True (indicates towing. so this car is not correct position) 4. if status="not_in_world" (not in world. so this car is not correct position)

Returns: list: leaderboard each element is a dict with the following keys: - car_idx: int - position: int | None - class_position: int | None - car_number: int - car_number_raw: int (use this value for camera switching functions) - driver_name: str - team_name: str - irating: int - license_str: str - lap_and_lap_dist_pct: float - best_lap_time: float - last_lap_time: float - car_name: str - class_name: str - class_est_time: float - gap_to_leader_str: str - gap_to_next_str: str - gap_to_class_leader_str: str - gap_to_class_next_str: str - flags: list[str] (e.g. ["black", "repair", "furled", "servicible"]. "servicible" means no flags) - status: str (e.g. "off_track", "in_pit_stall", "approaching_pits", "on_track", "not_in_world") - is_missing_start: bool - is_towing: bool

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

The description discloses the return format and filtering caveats, which is adequate for a read-only tool. However, it does not explicitly state that the tool is read-only, and no annotations are provided to fill that gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear header, filtering notes, and a detailed return schema. It is concise for the amount of information provided, though the return schema could be more compact.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given zero parameters and no output schema, the description provides a comprehensive return schema and usage notes. It is sufficient for an agent to understand the tool's output and filtering nuances.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are no parameters, so schema coverage is 100%. The description adds filtering notes but these are about interpreting results, not parameters. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns a leaderboard and provides a detailed list of fields. It is a specific verb+resource combination. However, it could be more explicit about which session (e.g., live session) it refers to, slightly reducing clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a note on filtering for competitive results, but does not provide guidance on when to use this tool versus alternatives like get_qualify_results_info. No explicit when/when-not advice is given.

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

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