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CadenceAI MCP

CadenceAI MCP

by chaosAIman
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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allegro_batch_commands

Lists all supported Allegro PCB batch commands, letting users choose the proper task for Gerber conversion, netlist import, library export, or photoplot generation.

Instructions

列出 Allegro batch 支持的所有命令 (75+ 条).可用于了解 Allegro 批处理能力,挑选合适的工具做 Gerber 转换、网表导入、库导出、光绘生成等。

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "allegro_batch_commands"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral burden. It discloses that it returns 75+ commands, but does not confirm read-only safety, describe the return format, or mention any side effects or auth requirements. For a listing tool this is adequate but not rich.

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?

Two short sentences, purpose first then usage, with no wasted words. The example list in the usage sentence is compact and directly relevant.

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 tool is simple (no params, no annotations), but the absence of an output schema means the description could usefully say what the returned command list looks like (names only, descriptions, format). It states the count and usage, which is helpful, but leaves the return shape unspecified.

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?

The tool takes zero parameters, so the baseline is 4; schema coverage is 100% (empty schema), and the description adds no parameter information because there are none to describe.

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 verb ('列出') and resource ('Allegro batch 支持的所有命令'), and notes the size (75+). It does not differentiate itself from the sibling safe_batch_commands or explain why one would choose this over that, so it falls short of the top score.

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 provides clear context: use to understand Allegro batch capabilities and pick suitable tools for Gerber conversion, netlist import, library export, etc. However, it offers no when-not guidance or explicit alternatives among the many sibling tools.

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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