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Check a project

validate_project
Read-onlyIdempotent

Check a project the way the Mokxi editor does: every unknown part, wrong pin, bad setting and code problem, in plain words naming the part and pin. Fix every error, then call create_project.

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": {
      "project": "<project>"
    },
    "name": "validate_project"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectYesA project in the Mokxi AI format: {"format": "mokxi-ai/1", "name": "...", "board": "uno", "parts": [{"id": "led1", "type": "led"}], "wires": [["board.13", "led1.A"]], "code": {"sketch.ino": "..."}}. get_project_format has the full rules.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

The annotations already declare read-only, idempotent, non-destructive behavior, so the description need not restate safety. It adds useful context by saying validation is exhaustive ("every") and that diagnostics are in plain words naming the part and pin, and it makes clear the tool only reports problems—the caller must fix them before creating. It does not say what a clean result looks like or whether warnings are separated from errors.

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?

Two sentences, front-loaded with the action and scope, then the follow-up workflow. Every clause carries information, though "the way the Mokxi editor does" is slightly vague framing rather than a precise detail.

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

Completeness3/5

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

The complex nested input is fully covered by the schema, and the description explains purpose and next steps. With no output schema, however, it leaves unclear whether the result is structured or purely prose, how a successful validation is reported, and whether warnings are distinguished from errors.

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?

Schema coverage is 100% and the nested project object is fully documented with an example and a pointer to get_project_format. The description adds no parameter-specific meaning beyond what the schema already provides, so the baseline of 3 applies.

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 names a specific verb and resource ("Check a project") and enumerates the validation scope: unknown parts, wrong pins, bad settings, and code problems. It also distinguishes itself from the sibling create_project by framing validation as the step that precedes creation.

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

Usage Guidelines4/5

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

It clearly states the intended workflow: validate first, fix every error, then call create_project. That gives an agent a concrete when-to-use context, though it does not explicitly state when validation is unnecessary or name any alternative validation tool.

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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