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Get an AILANG teaching prompt

prompt_get
Read-onlyIdempotent

Fetch the canonical teaching prompt for a version. kind = "agent" | "devtools" | "compact" (full prompt = empty).

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": {
      "forVersion": "<forVersion>",
      "kind": "<kind>"
    },
    "name": "prompt_get"
  }
}

Input Schema

NameRequiredDescriptionDefault
kindYes
forVersionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so safety is covered. The description adds genuine behavioral value by enumerating the three variant kinds and disclosing that an empty kind yields the full prompt — information not present in the schema. It stops short of describing return payload shape or size, so not 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?

Two short sentences, front-loaded with the core action and followed by the variant list. Nothing is wasted, though the parenthetical phrasing for the full-prompt case is slightly crypted and could be stated more plainly.

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 simple two-parameter read tool with rich annotations and no output schema, the description is nearly sufficient. The notable gap is any guidance on the forVersion parameter's expected format, which an agent needs in order to call the tool correctly.

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?

Schema description coverage is 0% and neither parameter carries an enum, so the description must compensate. It fully documents the kind parameter's allowed values, but says nothing about forVersion (expected format, exact version string vs. alias), leaving one of two required parameters undefined.

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 concrete verb and resource: 'Fetch the canonical teaching prompt for a version.' This is clearly distinct from sibling tools like docs_search or example_get, though it doesn't explicitly contrast itself with them.

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?

The parenthetical '(full prompt = empty)' implies how to obtain the complete prompt, which is a useful usage cue, but there is no explicit when-to-use guidance, no mention of when another tool (e.g. docs_search, onboarding_guide) is the better choice.

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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