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dsh-baton

dsh-baton

by JialaoLiu
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JavaScript
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dsh_list_models

Read-onlyIdempotent

Lists the models this DeepSeek Harness can run (provider, model id, name, reasoning efforts) and its default, so you can verify a model name before passing it to dsh_send. Read-only.

Instructions

List the models this DeepSeek Harness can run (provider, model id, name, reasoning efforts) and its default model, to check a name before passing model to dsh_send. Read-only. Needs the dsh-baton-host plugin.

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": "dsh_list_models"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.4

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds two things beyond the annotations: the prerequisite 'Needs the dsh-baton-host plugin' and a hint at the return shape (fields listed). That is meaningful extra context for a zero-parameter tool.

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 efficient sentence that front-loads the action and scope, then gives the purpose ('to check a name before passing model to dsh_send'), then two short clauses for safety and prerequisites. No waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no input schema, no output schema, and full annotation coverage, the description fills the remaining gaps: what the tool returns, why to call it, and the plugin prerequisite. Nothing an agent needs in order to call it correctly is missing.

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 has zero parameters, so the baseline is 4. The description does not need to explain inputs, and it correctly spends its words on output content and prerequisites instead.

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?

States a specific verb ('List') and resource ('models this DeepSeek Harness can run') and enumerates the fields returned (provider, model id, name, reasoning efforts) plus the default model. An agent can immediately distinguish this from sibling tools like dsh_list_workspaces or dsh_status.

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?

Explicitly names the downstream use case — 'check a name before passing model to dsh_send' — which tells the agent both when to call this and which sibling consumes the result. It stops short of stating when *not* to use it, but the context is clear enough to route correctly.

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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