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Gomo Sounds

Game progress

game_progress
Read-only

How much of the game already has a chosen sound (what goes into the game), in % and per tab (Ambience, Sound effects, Interface), and EVERY missing event, with its id. Call it at the end of any setup or bulk generation and whenever the user asks what's missing. Below 100%: show what's missing and the cost to complete it, and ask whether to generate.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "game_id": "<game_id>"
    },
    "name": "game_progress"
  }
}

Input Schema

NameRequiredDescriptionDefault
game_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

The readOnlyHint annotation already marks this as a safe read, and the description stays consistent while adding real behavioral context: the exact shape of the return (percentage, per-tab breakdown, exhaustive missing-event list with ids) and the recommended next step when incomplete. What's missing is any note on cost of the call, empty-state behavior, or error handling, so not a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The payload description is front-loaded in the first sentence, with usage triggers and the below-100% procedure following. Dense but every clause carries information; only the nested parenthetical '(what goes into the game)' is slightly redundant.

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?

With no output schema, the description takes on the burden of describing return values and does so thoroughly (percentage, per-tab counts, every missing event with id). Combined with readOnlyHint and a single simple parameter, this is sufficient to invoke correctly; only the game_id contract is left unstated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There is one required parameter, game_id, with 0% schema description coverage, and the description never mentions it or its format explicitly — only an implied 'the game'. The parameter is largely self-explanatory from its name, which keeps this from being worse, but the description does not compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific reporting job: the percentage of the game with chosen sounds, broken down per tab (Ambience, Sound effects, Interface), plus every missing event with its id. It is concrete about both scope and payload, so an agent can distinguish it from listing tools like get_game or game_scenes. It stops short of naming a sibling it should be preferred over, so it falls just under a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit triggers are given: call it at the end of any setup or bulk generation, and whenever the user asks what's missing. It also prescribes follow-up behavior below 100% (show what's missing, state completion cost, ask whether to generate), leaving no inference needed about when this tool belongs in a flow.

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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