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get_form_fields

Read-only

What a site's form asks beyond the message, in order: each field's key, label, kind (text, number, date, select, checkbox, hidden), options and whether it is required. paused lists the keys the plan has no room for now (kept, and not asked); limit is how many fields of its own a form may have (severity and category are ready-made and not counted; null means any number); conditions is whether a field may depend on another.

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": {
      "product_id": "<product_id>"
    },
    "name": "get_form_fields"
  }
}

Input Schema

NameRequiredDescriptionDefault
product_idYesThe site's id (a uuid), from list_products.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds meaningful behavioral context beyond annotations by explaining the plan-limit semantics (`paused`, `limit`) and conditional-field behavior (`conditions`), which an agent would not otherwise know without an output schema.

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 dense but front-loads the core return shape before explaining `paused`, `limit`, and `conditions`. It earns its space with specific field-kind enumeration and plan-limit semantics, though the single long sentence with semicolons is somewhat harder to parse than necessary.

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

Completeness4/5

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

With no output schema, the description carries the burden of explaining return content, and it does so reasonably well by listing field properties and the special `paused`, `limit`, and `conditions` semantics. It is not fully complete about response structure or error behavior, but it covers the essential shape an agent needs 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 coverage is 100% and the single `product_id` parameter is fully documented in the schema. The description does not mention the parameter at all, so it adds no semantic value beyond the schema, which is acceptable at the baseline when the schema does the heavy lifting.

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 clearly identifies the resource as the fields a site's form asks beyond the message, and enumerates their key attributes (key, label, kind, options, required). It is specific about the returned data but lacks an explicit verb and does not differentiate itself from related siblings such as get_form or set_form_fields.

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?

There is no guidance on when to use this tool versus alternatives. It never mentions get_form, set_form_fields, use_simple_form, or the conditions under which an agent should prefer one over another, leaving selection to inference from the name alone.

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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