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prompt-to-scene

by 316sandon12
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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get_variants

Retrieve each candidate's exact status, report, and preview views using a study ID to compare variants without aesthetic scoring.

Instructions

Read each candidate's exact status, report and preview views; no aesthetic score.

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": {
      "study_id": "<study_id>"
    },
    "name": "get_variants"
  }
}

Input Schema

NameRequiredDescriptionDefault
study_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the burden. It implies a read-only operation and specifies included data (status, report, preview) and excluded data (no aesthetic score), but omits permissions, side effects, pagination, and response format details.

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 a single, front-loaded sentence that states the action, scope, and exclusion without filler. It is appropriately concise for a simple read tool.

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

Completeness2/5

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

Given no annotations, no output schema, and 0% schema coverage, the description is insufficient. It does not document the required study_id parameter, return structure, or when to prefer this tool over siblings like get_review or get_preview.

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?

Schema description coverage is 0% for the single required parameter study_id. The description never mentions study_id or explains what identifier it expects, adding no meaning beyond the schema's bare type and title.

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 verb 'Read' and resources ('exact status, report and preview views') and explicitly excludes aesthetic score, distinguishing its scope. However, it does not differentiate from sibling tools like get_preview or get_review, and 'candidate' is not tied to the tool name's 'variants' without inference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives such as get_review, get_preview, or choose_variant. The description is purely declarative and does not mention prerequisites, context, or selection criteria.

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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