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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it produces an optimal move, but does not disclose what output format is returned, whether the operation is read-only, how invalid or finished boards are handled, or whether it is deterministic. This is a significant gap for a calculation-style tool with no annotation safety cues.

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 a single front-loaded sentence with no filler. It efficiently communicates the core function and strategy qualifier. It loses a point because it repeats the tool name prefix and could have used the space more substantively (e.g., adding board format or return type), but structurally it is clean and well-scoped.

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?

For a tool with four ambiguously described optional parameters, no output schema, and no annotations, the description is incomplete. It omits input format details, return value shape, and edge-case behavior. An agent would need to guess or experiment, making correct invocation unlikely, especially given the large sibling set that offers no disambiguation help beyond the name.

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?

Although schema description coverage is 100%, every parameter description is the boilerplate 'X to process', which provides no meaningful semantics. The tool description also fails to explain what 'board', 'turn', 'state', or 'player' mean in practice (e.g., board encoding, player symbols, turn format). An agent cannot reliably construct a valid invocation from the available information.

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 names a specific game (tic-tac-toe), a specific strategy (minimax-optimal), and a specific function (generating a move per turn). It is distinguishable from game-move siblings like x402-chess-move or x402-connect4-move. The verb is implicit rather than explicit ('computes'), so it loses one point, but the resource and scope are unambiguous.

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?

There is no guidance on when to use this tool versus alternatives or any prerequisites. The only hint is the tool name and the phrase 'per turn', which weakly implies turn-based use. No exclusions, conditions, or alternative routing are stated, leaving the agent to infer usage entirely from the name.

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