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Surya96t

fastf1-mcp-server

clear_cache

Clear Formula 1 session data from in-memory cache. Optionally filter by year and event to remove specific cached sessions.

Instructions

Clear cached sessions from in-memory storage.

Args: year: Optional year filter — only clear sessions for this year event: Optional event filter — requires year to be set

Returns: {"cleared": 3, "remaining": 2}

Example: clear_cache() → {"cleared": 5, "remaining": 0} clear_cache(2024, "Monaco") → {"cleared": 1, "remaining": 4}

Note: Clears the in-memory LRU cache only. The FastF1 disk cache (raw timing files) is preserved and unaffected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNo
eventNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations are provided, so the description carries the full burden. It fully discloses behavioral traits: clears only in-memory LRU cache, preserves disk cache, returns a JSON with cleared and remaining counts, and parameter constraints (event requires year).

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

Conciseness5/5

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

The description is well-structured with Args, Returns, Example, and Note sections. Every sentence adds value, and the example clarifies expected usage. No wasted words.

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

Completeness5/5

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

Given no annotations and a complete input schema, the description provides all necessary context: clear action, parameter constraints, return format, and side effects (no effect on disk cache). The output schema exists but the description already explains return values.

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

Parameters5/5

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

Schema description coverage is 0%, but the description compensates excellently. It explains each parameter's purpose ('year: Optional year filter', 'event: Optional event filter — requires year to be set') and provides example calls demonstrating usage.

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

Purpose5/5

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

The description clearly states the tool's action: 'Clear cached sessions from in-memory storage.' It uses a specific verb (clear) and resource (cached sessions), and the note about disk cache distinguishes it from sibling tools like get_cache_status.

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

Usage Guidelines4/5

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

The description does not explicitly say when to use vs. alternatives, but it notes that the disk cache is preserved, which guides usage. It lacks explicit exclusion statements (e.g., 'use get_cache_status to view cache').

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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