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CLI Subagents MCP Server

CLI Subagents MCP Server

by lunati228
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

subagent_message

Send a follow-up or answer to a running subagent, or continue its finished conversation as a new job.

Instructions

Send a message to a subagent. While it runs: a follow-up or an answer to its question (set reply_to to the question's id). After it finished: continues the same conversation as a new job and returns that job.

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": {
      "job_id": "<job_id>",
      "text": "<text>"
    },
    "name": "subagent_message"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes
job_idYesJob ID returned by subagent_start.
reply_toNoId of the question you are answering.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose the non-obvious dual-mode semantics: same tool either injects into a live job (requiring reply_to when answering) or spawns a continuation job after completion, returning that job. It omits what the live-path call returns, queueing behavior, and error cases, which keeps it from a 5.

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?

Three short clauses, front-loaded with the verb and resource, then the two timing branches. Telegraphic fragments ('While it runs:', 'After it finished:') are slightly rough but every clause carries information.

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?

For a 3-parameter tool with no annotations and no output schema, the description covers timing and continuation behavior but leaves the live-path return value and failure modes unstated. An agent can call it, but cannot predict the response shape in the while-running case.

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?

Schema coverage is 67%; the description adds real meaning beyond the schema by tying reply_to to answering a question and by explaining that job_id refers to a running subagent in one branch and a finished one in the other. Only 'text' is left entirely to the schema.

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?

States a specific verb and resource ('Send a message to a subagent') and then characterizes two distinct behaviors, which separates it from siblings like subagent_start. It doesn't explicitly name an alternative tool, but the mode descriptions make the distinction inferable.

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?

Gives clear state-based guidance: use it while the subagent runs for a follow-up or to answer a question, and after it finishes to continue the conversation as a new job. No explicit exclusions or named alternatives, so it stops short of a 5.

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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