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Create a prompt

create_prompt

Make a single prompt: a name, a model id from list_models, and messages (system, then user). Put {{name}} in a message for each value the caller fills in, and give a sample for each in variables. Add json_schema to get JSON back. Saved as the first prompt version; deploy_prompt publishes it.

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": {
      "name": "<name>",
      "model": "<model>",
      "messages": "<messages>"
    },
    "name": "create_prompt"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
modelYesA model id from list_models.
messagesYes
max_tokenNo
variablesNoSample value for each {{name}}, e.g. {"topic": "solar panels"}.
json_schemaNoA JSON schema for the answer.
temperatureNo
reasoning_effortNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, openWorldHint=false, so the mutation/safety profile is known. The description adds real value by noting the prompt is saved as the first version and only becomes live via deploy_prompt, but it says nothing about permissions, what a failed or duplicate name does, or whether repeated calls create new versions.

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 tight sentences, front-loaded with the required inputs before the templating advice and the deploy_prompt handoff. Dense but every clause carries information; only minor cost is the slightly crammed final clause joining versioning and publishing.

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 an 8-parameter, nested-object creation tool with no output schema, the description covers the core flow well but omits the return value entirely, so an agent cannot know whether the new prompt's id comes back (which it needs before calling deploy_prompt). It also leaves the optional generation parameters unexplained.

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 only 38%, and the description compensates for the most non-obvious parts: the {{name}} templating convention and the requirement that each placeholder have a sample in variables, plus what json_schema does. Three tuning parameters (max_token, temperature, reasoning_effort) are left entirely to the schema, which is a residual gap but they are near self-describing.

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?

Opens with a specific verb and resource ('Make a single prompt') and immediately enumerates the required shape: name, model id from list_models, and messages ordered system-then-user. It also distinguishes itself from deploy_prompt by stating that creation only saves the first version while deploy_prompt publishes it.

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 concrete usage direction: pull the model id from list_models, use {{name}} placeholders with matching entries in variables, and add json_schema when JSON output is wanted. It routes the publishing step to deploy_prompt but does not explicitly exclude the creation case from update_prompt or state prerequisites.

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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