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Proma Manager MCP Server

Proma Manager MCP Server

by climashscape
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

group_list

Retrieves group status and summaries for skills in a workspace, enabling AI to auto-assign groups. Excludes default-synced skills and returns name, description, group, and preview.

Instructions

列出指定工作区所有 skill 的 group 状态和内容摘要，供 AI 分析后自动分配 group。自动排除 default-skills 管理的 19 个 watcher 同步 skill。返回每个 skill 的 name、description、当前 group、正文预览。默认扫描 default 工作区。

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": "group_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
workspaceNo工作区 slug，默认 default。可选值由运行时动态扫描 ~/.proma/agent-workspaces/ 确定。

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses several behavioral traits: automatic exclusion of 19 watcher-sync skills, the return fields (name, description, current group, body preview), and default workspace scanning. This adds meaningful context beyond the bare parameters.

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 sentences, each earning its place: first states the main function and purpose, second covers exclusions and return/defaults. No fluff, front-loaded with the essential action.

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 simple listing tool with no output schema, the description covers the purpose, the output fields, default workspace, and a key exclusion. It omits potential edge cases (e.g., empty workspace, errors) but is otherwise complete for agent decision-making.

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?

The only parameter (workspace) has full schema description coverage, including default and dynamic discovery. The description reiterates the default but adds no syntax or value details beyond the schema, so the schema does the heavy lifting (baseline 3).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool lists group status and content summaries for all skills in a workspace, with a specific verb ('列出') and resource. It distinguishes from group_set by noting it is for AI analysis before assigning groups, and additionally specifies auto-exclusion of certain skills.

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 analyze skills before automatically assigning groups, and defaults to the default workspace. It does not explicitly name alternative tools or when not to use it, but the intended usage is evident from the '供 AI 分析后自动分配 group' phrase.

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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