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init_project

Start tracking a game on Steam: create steamworks.yaml and .steam-mcp/ without overwriting, then scan the project for a report.

Instructions

Start tracking a game: create steamworks.yaml and .steam-mcp/ in path (existing files are kept, never overwritten), then scan the game project unless scan is false.

Args: path: Folder for steamworks.yaml, usually the game project's root (relative to the workspace root). name: Product name as it will appear on Steam, if known. appid: The main game's Steam app id, if already created in Steamworks. scan: Run the project scanners (Unity, …) right away. source_dir: The engine project folder, when it is not path itself.

Returns created/existing files, .gitignore lines to suggest to the user (this server never edits the project's own .gitignore), and the scan report when scanning.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
pathYes
scanNo
appidNo
source_dirNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and openWorldHint=false. Beyond that the description adds genuinely useful behavioral context: existing files are kept and never overwritten, the server never edits the project's own .gitignore (it only suggests lines), and scanning can be suppressed via `scan`.

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 behavioral summary is front-loaded in the first sentence, with parameters and return values in a clean structured block. Slightly verbose, but each line carries information an agent needs.

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?

The tool has an output schema, so return values need not be explained, yet the description still summarizes them (created/existing files, .gitignore lines, scan report). Combined with full parameter coverage and mutation context, it is essentially complete.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must carry the burden, and it does: all five params (path, name, appid, scan, source_dir) are given meaning beyond their JSON types, e.g. path is 'usually the game project's root' and source_dir applies 'when it is not `path` itself.'

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 opens with a specific verb+resource: 'Start tracking a game: create steamworks.yaml and .steam-mcp/ in `path`.' It is clearly distinguishable from a bare scanner like scan_project because it states it creates tracking files and then scans. It stops short of naming a sibling or a decision boundary, so it is clear but not sibling-differentiating.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: this is obviously the first step of a workflow, and 'scan the game project unless `scan` is false' describes internal sequencing. There is no explicit when-to-use/when-not or pointer to an alternative tool, so it lands at minimum-viable.

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