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clu

clu

by QiandingHuang666
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

job_list

Read-onlyIdempotent

Query the local job ledger to retrieve script details, requested resources, assigned nodes, stdout/stderr paths, and daemon-verified status; optionally filter to active jobs.

Instructions

查询本地作业台账：脚本路径与内容、申请资源、节点、stdout/stderr 路径、 最近一次核对的状态（daemon 定期刷新）。

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": "job_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
connectionNo
active_onlyNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.7

TDQS

C2.7/5.0
Behavior3/5

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

Annotations already declare this as a read-only, idempotent, non-destructive operation. The description adds useful behavior context by noting that status comes from a daemon that periodically refreshes it, which signals possible freshness limits, but it does not cover pagination, connection scope, or other operational details.

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 definition is a single front-loaded sentence with no filler and an efficient colon-delimited list. It spends some words on return fields that the output schema already covers, but remains compact overall.

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?

Annotations and the output schema carry the safety profile and return values, but the input schema is undocumented and the description never explains connection or active_only. It also does not disambiguate from sibling tools, so an agent lacks enough information to choose and invoke it confidently.

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

Parameters1/5

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

The schema has two parameters, connection and active_only, with 0% description coverage, and the description does not mention either parameter. It instead lists returned fields, leaving the agent with no semantic guidance for the 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 names a specific verb ('查询') and resource ('本地作业台账') and enumerates what the ledger contains, so the operation is clear. It does not distinguish this tool from nearby siblings such as jobs or ledger_query, so it stops short of a 5.

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?

It gives no explicit when-to-use guidance, no exclusions, and no alternatives among siblings like jobs or ledger_query. The agent must infer that this is for listing jobs, with no indication of when another tool is preferable.

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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