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by Sebtiago
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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get_validate_prompt

Generate a validation prompt to test a service design against a user profile. Reads the profile and design document, then provides a prompt for evaluating the design's alignment with user needs.

Instructions

Generate a validation prompt for testing a design against a profile.

Reads the specified profile and design document, then returns a prompt for you to evaluate the design against the user's criteria and needs.

Args: project_path: Absolute path to the project directory. profile_id: The profile to validate against (e.g. "maria-cuidadora"). design_file: Path to the design document to validate (relative to project).

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": {
      "project_path": "<project_path>",
      "profile_id": "<profile_id>",
      "design_file": "<design_file>"
    },
    "name": "get_validate_prompt"
  }
}

Input Schema

NameRequiredDescriptionDefault
project_pathYes
profile_idYes
design_fileYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions reading files but does not disclose behavioral traits like error handling (e.g., if files don't exist), authorization needs, or side effects. The read-only nature is implied but not confirmed.

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?

The description is concise, front-loaded with the main purpose, and structured with a clear Args list. Every sentence adds value, with no redundant or vague statements.

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?

Considering no annotations, 3 params, and existence of an output schema, the description covers core purpose and parameter semantics. However, it lacks context on error behavior (e.g., missing files), prerequisites, or what the output prompt contains beyond being 'for you to evaluate'. The output schema might cover return format, so it's adequate but not fully complete.

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?

With 0% schema description coverage, the description compensates by including an Args section that explains each parameter's purpose (e.g., 'Absolute path to the project directory', 'The profile to validate against (e.g. "maria-cuidadora")', 'Path to the design document to validate (relative to project)'). This adds significant meaning beyond the schema.

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?

The description clearly states the tool's purpose: 'Generate a validation prompt for testing a design against a profile.' It specifies the verb (generate/read/return), resource (validation prompt from profile and design), and distinguishes from siblings like get_generate_prompt and get_research_prompt.

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?

While the description implies when to use (validating a design), it does not explicitly state when not to use or name alternative tools. It lacks explicit guidance on when to choose this tool over siblings, such as get_generate_prompt or get_research_prompt.

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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