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

The description discloses the core advisory behavior: the tool analyzes and suggests, and it supports configurable difficulty levels. However, with no annotations provided, there is no explicit statement about read-only status, determinism, rate limits, or output behavior beyond the suggestion itself.

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 short, front-loaded sentences with no filler. The first sentence states the action, and the second adds useful scope and feature information without repeating schema details.

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?

The tool's purpose, scope, and parameters are adequately clear, but there is no output schema and no mention of the return shape or whether the suggested move can be fed directly into play_apply_move. Given the lack of annotations, this leaves a meaningful integration gap for the agent.

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 coverage is 100%: both state and difficulty are already documented in the input schema, including the enum values and default. The description adds no parameter-level meaning beyond reinforcing that difficulty levels exist, so no uplift above the baseline is warranted.

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 a specific action ('analyse the position and suggest the best move') and a specific resource scope ('all 10 playable families'). This distinguishes it from move-executing siblings like play_apply_move and from chess-only tools like chess_analyze_position.

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 opening phrase implicitly instructs when to use the tool: when the agent wants an AI-suggested move rather than a move execution or validation. The scope 'all 10 playable families' gives clear context, but no alternatives are explicitly named and no when-not-to-use guidance is provided.

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