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blessed0x

scratch-unified-mcp

by blessed0x

Sb3 Vm Input

sb3_vm_input

Send keyboard, mouse, and answer inputs to a headless Scratch VM to simulate user interactions during automated playtesting.

Instructions

Feed keyboard/mouse/answer input to the headless VM. (proxied)

keys accepts a JSON array of {key, isDown?} objects or a single key name (wrapped to a full tap). Anything else that parses to a non-list raises ValueError before touching the sidecar — the sidecar's zod schema would reject it anyway, but failing here gives the shorter, proxy-attributed error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keysNo
answerNo
mouseXNo
mouseYNo
mouseDownNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description must disclose behavior itself. It does mention the validation behavior: invalid `keys` input raises a ValueError before reaching the sidecar, and explains the proxy-attributed error rationale. However, it does not describe success behavior, side effects on the VM, whether input is immediate or queued, or any state changes. This is partial transparency.

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 compact and front-loaded. The main purpose is stated in the first sentence, and the additional paragraph about `keys` is precise and necessary. There is no filler or redundancy; every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has five optional parameters and no annotations, and the schema provides zero descriptions. The description only covers one parameter and omits any mention of return values, side effects, or preconditions. Given the tool's complexity (multiple input channels), this is incomplete and leaves the agent guessing about `answer`, mouse coordinates, and expected behavior.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It only explains the `keys` parameter in detail (JSON array or single key name, wrapping behavior). The other four parameters (`answer`, `mouseX`, `mouseY`, `mouseDown`) are not described at all, leaving the agent with no semantic guidance for them. This is a significant gap.

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 opens with a clear, specific verb-resource pair: 'Feed keyboard/mouse/answer input to the headless VM.' This distinguishes it from sibling VM tools (load, run, stop, etc.) and conveys exactly what the tool accomplishes. The phrase 'to the headless VM' anchors the resource and context.

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

Usage Guidelines2/5

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. It does not mention any prerequisites (e.g., a loaded/running project) or contrast with other input-related tools. The description only states the action, leaving the agent to infer context from the tool's name and sibling list.

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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