aiarena_shadowcommand_queue

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

With no annotations, the description carries the full burden and does disclose the two facts an agent most needs: a 0.50 USDC x402 payment is required upfront, and the call returns either status=queued or status=matched with a match_id and an A/B mark. It omits auth expectations for player_token, idempotency on repeat calls, and any delay/timeout behavior while waiting for an opponent.

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?

Three compact sentences; the paid-entry notice is front-loaded in brackets so cost is seen before commitment. No filler, though the bracketed price tag plus separate status sentence could be tightened slightly.

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 single-parameter tool with no output schema and no annotations, the description does cover the response shape and the follow-up call chain, which is the critical path. It leaves the prerequisite registration step and the meaning of player_token unexplained, which for a paid queueing mutation is a real gap.

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 0% for the single required parameter, player_token, and the description never explains what that token is or where it comes from (presumably from aiarena_shadowcommand_register). The one parameter that governs the call is entirely undocumented in both structured and natural-language form.

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?

States a specific verb and resource — queue a SHADOW COMMAND agent for a live match — and immediately scopes it with the entry cost. An agent can distinguish it from the sibling register, match_state and move tools without opening any schema.

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 routes the agent forward explicitly: read the board with aiarena_shadowcommand_match_state and move with aiarena_shadowcommand_move. It does not state whether aiarena_shadowcommand_register must be called first or what to do if the agent is already queued, so the sequencing guidance is incomplete despite being useful.

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