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lichess_tablebase

Read-only

Returns the legal moves and position outcome for a supplied FEN in the standard, atomic, or antichess tablebase. Use it to analyze a board position; standard queries also accept dtc=never, auxiliary, or always.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "variant": "<variant>",
      "fen": "<fen>"
    },
    "name": "lichess_tablebase"
  }
}

Input Schema

NameRequiredDescriptionDefault
dtcNoOptional distance-to-conversion mode for the standard variant; the source does not accept this parameter for atomic or antichess.
fenYesRequired chess position in Forsyth-Edwards Notation.
variantYesRequired supported tablebase variant: standard, atomic, or antichess.

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

The annotations already establish read-only and open-world behavior, so the description's main added value is its variant-specific constraint: dtc is accepted for standard but not for atomic or antichess. That is useful behavioral context, though it does not discuss error behavior, response shape, or source limitations beyond dtc.

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 two tight sentences with the primary return behavior front-loaded and the variant constraint following immediately. Every clause adds useful information without repetition or filler.

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 three parameters, full schema coverage, and an output schema, the description supplies enough context to invoke the tool correctly. Its main omission is guidance on choosing this tool over the sibling cloud-evaluation tool for position analysis.

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 the input schema already explains fen, variant, and dtc in detail. The description reinforces variant support and the standard-only dtc restriction, but it adds little semantic meaning beyond what the schema already provides.

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 states a specific action and resource: it returns legal moves and the position outcome for a FEN from a tablebase. It also names the three supported variants, making the tool's domain clear, but it does not explicitly distinguish itself from the sibling cloud-evaluation tool.

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

Usage Guidelines3/5

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

It says to use the tool to analyze a board position and clarifies that dtc applies only to standard queries. That gives implied usage context, but it does not say when to prefer this tablebase over alternatives such as lichess_cloud_eval, nor does it state when not to use it.

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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