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Glama

f1_undercut_window

Read-onlyIdempotent

Estimate whether an F1 attacker can undercut a target driver on the current lap, returning viability, marginal status, and laps needed to clear.

Instructions

Estimate whether an undercut is viable for the attacker against the target.

Args: session_key: OpenF1 session identifier. attacker_number: Attacking driver's race number. target_number: Target driver's race number. current_lap: Current lap number in the race.

Returns: data: {laps_to_clear, viable, marginal}. meta.gap_to_target_s: attacker-minus-target race time at current_lap. meta.gap_source: "cumulative_lap_time", or "default" (assumed 2.0 s, also in meta.assumed_gap_s) when either driver lacks a full lap history. meta.estimated: true.

Input Schema

NameRequiredDescriptionDefault
current_lapYesCurrent lap number in the race.
session_keyYesOpenF1 session identifier.
target_numberYesTarget driver's race number.
attacker_numberYesAttacking driver's race number.

Output Schema

NameRequiredDescriptionDefault
dataNo
metaNo
errorNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the description's real contribution is the disclosure that the result is an estimate and that a fallback constant of 2.0 s is substituted when either driver lacks a full lap history, surfaced via meta.gap_source and meta.assumed_gap_s. That is exactly the kind of silently-degraded-output warning an agent needs and cannot get from annotations. Only the absence of any note on data requirements or cost keeps it from a 5.

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

Conciseness3/5

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

The purpose sentence is correctly front-loaded, but the four-line Args block is pure duplication of a 100%-covered schema, and the Returns block partly restates an output schema that already exists. The useful content (gap_source fallback semantics) is buried in the middle of the Returns section rather than promoted.

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?

With an output schema present, the description needn't enumerate return fields, and it adds genuinely non-derivable context about the estimated result and the 2.0 s default gap. What is missing is the data prerequisite (both drivers need lap history for a non-default gap) stated as a precondition rather than buried in the return narrative, and any routing versus sibling strategy tools.

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?

Schema description coverage is 100%, so per the rubric the baseline is 3. The Args block restates each parameter's schema description almost verbatim ('Attacking driver's race number' etc.) without adding format, range, or validation meaning (e.g., whether attacker_number must differ from target_number, or whether current_lap must be >= 2).

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 first line states a specific verb and resource ('Estimate whether an undercut is viable') and names both actors (attacker, target), so an agent knows exactly what question is being answered. It does not distinguish itself from the nearest F1 siblings such as f1_predict_pit_strategy or f1_race_pace_compare, which keeps it out of 5 territory.

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?

There is no 'when to use' guidance at all: no statement of prerequisites (lap history needed), no mention of when to prefer f1_predict_pit_strategy or f1_race_pace_compare, and no exclusion conditions. Usage must be inferred entirely from the tool name and the one-line purpose.

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