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CadenceAI MCP

CadenceAI MCP

by chaosAIman
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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safe_batch_commands

Lists whitelisted allegro_batch subcommands that require no GUI license, so users can run safe Cadence Allegro batch tasks.

Instructions

返回 allegro_batch 的白名单命令列表(无需 GUI license 即可使用的安全子命令)。

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": "safe_batch_commands"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does add real value by disclosing that the listed subcommands are the whitelisted/safe ones usable without a GUI license, but it says nothing about the return shape, ordering, or whether the result is static.

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?

A single front-loaded sentence that states the return value and the key qualifier with no filler. Nothing needs trimming and nothing important is buried.

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?

For a trivial no-input, no-output-schema listing tool, the description covers what is returned and the safety qualifier. The main omission is any hint about the size or format of the returned list, and the failure to reference the sibling command-listing tool.

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 there are no parameter semantics to document; the baseline for a 0-param tool is 4. Nothing in the description misleads about inputs.

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 (返回) and resource (allegro_batch 的白名单命令列表), and qualifies scope with the safe-subcommand/no-GUI-license clause. It is clear what the tool returns, but it does not explicitly distinguish itself from the sibling allegro_batch_commands, which an agent would reasonably confuse with this one.

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 only implied via the '无需 GUI license 即可使用的安全子命令' qualifier, which hints at the condition for wanting this list. There is no explicit when-to-use vs. when-not-to-use statement and no mention of the near-identical sibling allegro_batch_commands, leaving the routing decision to inference.

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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