Lichess MCP

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool 'returns' analysis results, implying a read-only operation, but doesn't specify rate limits, authentication needs, data freshness, or error handling. For a cloud-based tool with no annotation coverage, this leaves significant behavioral gaps.

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 two sentences with zero waste: the first sentence states the purpose and input, the second specifies the output. It's front-loaded with essential information and appropriately sized for the tool's complexity.

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?

Given no annotations and no output schema, the description adequately covers the basic purpose and output but lacks details on behavioral aspects like rate limits or error cases. For a cloud evaluation tool with two parameters, it's minimally viable but could benefit from more context on usage constraints and result interpretation.

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 100%, with clear documentation for both parameters (fen and multiPV). The description adds minimal value beyond the schema by mentioning FEN notation and Stockfish analysis, but doesn't provide additional context like FEN validation rules or multiPV impact on performance. Baseline 3 is appropriate as the schema does the heavy lifting.

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 clearly states the specific action ('Get Lichess cloud engine evaluation'), the resource ('for a chess position in FEN notation'), and the output ('Returns the best move, score, and top lines from Stockfish cloud analysis'). It distinguishes itself from sibling tools that focus on game management, challenges, puzzles, and user data rather than position analysis.

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 description implies usage for evaluating chess positions via cloud analysis, but provides no explicit guidance on when to use this tool versus alternatives (e.g., local analysis tools or other evaluation methods). It doesn't mention prerequisites, limitations, or exclusions, leaving usage context inferred rather than stated.

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