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BlueMonkey262

subagent-mcp

List models

list_models

Retrieve configured models with per-backend usage counters, remaining allowances, and concurrency status so you can check capacity and quota before spawning agents.

Instructions

Config-sourced model roster plus per-backend usage counters (spawns, resumes, turns, failures, timeouts, tokens, and cost) and, when models.yaml sets allowances, how much of each allowance is left. Also reports the concurrency cap, the number of active agents, and how many spawns are waiting for a slot.

Input Schema

NameRequiredDescriptionDefault
backendNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does add meaningful context: it reports counters, allowance remaining, concurrency cap, active agents, and queued spawns. It does not explicitly state read-only safety or permission requirements, but the detailed output disclosure is substantial for a listing tool.

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 description is front-loaded with the core resource and then enumerates the supporting counters in a compact, information-dense sentence. It is appropriately sized, though the long list of counters is slightly heavy for a single sentence.

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?

There is no output schema and no annotations, so the description must explain return values, which it does thoroughly for a listing tool. Its main gap is the unmentioned optional backend filter, but overall it gives an agent enough context to understand what will be returned and why the tool matters.

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

Parameters2/5

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

There is one optional parameter (backend) with an enum of five values, and schema description coverage is 0%. The description never mentions this filter parameter or explains how the results change when a backend is supplied, so the parameter semantics are not compensated for in the description.

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 resource (config-sourced model roster) and the additional reporting it includes (usage counters, allowances, concurrency cap, active agents, waiting spawns). This clearly separates it from sibling tools like list_agents or list_agent_configs, though it does not explicitly name a sibling or exclusion.

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?

There is no explicit 'use this when' or 'do not use this when' guidance. The intended use is strongly implied by the content (model roster and usage/capacity reporting), but an agent must infer it rather than being told.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.