mech-cad-design-mcp

by bloodreaper005

Overview Schema Source Related Servers Discussions Admin

Python

Local

design_lesson_decide

Approve selected or all review-card lessons, or decline publication to control which design lessons are published.

Instructions

Approve all or selected review-card lessons, or decline publication.

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": {
      "design_id": "<design_id>",
      "decision_text": "<decision_text>"
    },
    "name": "design_lesson_decide"
  }
}

Input Schema

Name	Required	Default
`design_id`	Yes
`decision_text`	Yes
`selected_lesson_numbers_json`	No	[]

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.11.0Sep 15, 2026

TDQS

C2.7/5.0

Behavior2/5

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

With no annotations, the description must disclose behavioral traits but only reveals that the tool changes publication state. It does not mention authorization requirements, reversibility, effects on non-selected lessons, or how the default decision applies. The 'decline publication' hint is a thin signal with no detail.

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 description is a single front-loaded sentence with a clear verb and scope. It is concise and readable, but the brevity is achieved at the cost of leaving important operational details unexplained. Still, it earns a 4 for clarity of structure.

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?

For a mutating decision tool with no annotations, the description lacks critical context: how to specify approval vs decline, how to choose which lessons to act on, and what design_id refers to. The presence of an output schema does not compensate for missing parameter semantics and workflow guidance.

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 for undefined parameters. It does not explain what decision_text should contain, how selected_lesson_numbers_json selects lessons, or what the default '[]' means. The phrase 'all or selected' hints at the selection parameter but leaves format and values ambiguous.

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 clearly states the action — approving or declining publication of review-card lessons — and distinguishes between approving all or selected lessons. It is specific about the resource and operation, though it does not contrast with sibling tools like design_confirm or design_record_result.

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 such as design_confirm or design_record_result. The description implies it is used after reviewing lessons but does not state prerequisites, workflow position, or when to choose this tool over siblings.

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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