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danilop

chess-support-mcp

by danilop

add_move

Submit a chess move in UCI format (like e2e4) for validation. If legal, updates the game state and returns the new status; otherwise, indicates the move is illegal.

Instructions

Apply a move in UCI format if legal.

Parameters:

  • uci: string like "e2e4", "g1f3", promotions like "e7e8q".

Returns (in result):

  • On success: { accepted:true, status: Status, moves:[...], moves_detailed:[...] } where Status is the same shape returned by get_status(), including last_move_{uci,san}.

  • On failure: { accepted:false, reason:"illegal", expected_turn:"white"|"black", status: Status }

Notes:

  • This tool validates legality only; it does not suggest or score moves.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uciYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Even without annotations, the description discloses the main behavioral contract: it returns accepted true/false, provides an illegal reason and expected_turn on failure, and returns Status. It also explicitly notes the tool does not suggest or score moves. It could mention prerequisites like an active game, but the failure and return contracts are well specified.

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 organized with Parameters, Returns, and Notes sections. It is concise yet complete, with no filler, and every sentence contributes functional information such as examples, return shape, and validation behavior.

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 the tool's moderate complexity and the absence of annotations, the description covers the essential invocation contract: input format, success/failure result shape, and the tool's limited role. It does not explicitly state that an existing game is required, but this is inferable from the sibling create_or_reset_game and get_status tools and the Status return value.

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?

The input schema only provides 'uci' as a string with no description, so the parameter semantics are fully carried by the description. The description adds concrete UCI examples, including regular moves like 'e2e4' and promotion notation like 'e7e8q', which meaningfully compensates for the 0% schema coverage.

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 uses a specific verb ('Apply') and clear resource ('move in UCI format'), while adding the legality constraint. It is easily distinguished from sibling tools like is_legal (which would only validate) and list_moves (which would list options), because this tool actually changes the game state.

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 states that the tool 'validates legality only' and explicitly says it does not suggest or score moves, which gives useful context for when to use it. It does not directly name alternatives like is_legal or list_moves, but the action-oriented language and sibling names make the intended usage clear.

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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