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Get template fields

get_template_fields
Read-onlyIdempotent

Use this after choosing a template slug, to read the fill-in fields before generating a document.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesTemplate slug from list_templates.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
titleYes
fieldsYes
categoryYes
source_urlYes
descriptionYes
when_neededYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changed
    • addedInput schema / properties / slug / description
      Added value: +"Template slug from list_templates."
    • removedOutput schema / additionalProperties
      Removed value: -true
    • addedOutput schema / description
      Added value: +"Field schema for one template."
    • addedOutput schema / properties
      Added value: +{
      +  "category": {
      +    "type": "string"
      +  },
      +  "description": {
      +    "type": "string"
      +  },
      +  "fields": {
      +    "items": {
      +      "description": "One fill-in field on a template.",
      +      "properties": {
      +        "key": {
      +          "type": "string"
      +        },
      +        "label": {
      +          "type": "string"
      +        },
      +        "marks": {
      +          "items": {
      +            "type": "integer"
      +          },
      +          "type": "array"
      +        },
      +        "max_length": {
      +          "anyOf": [
      +            {
      +              "type": "integer"
      +            },
      +            {
      +              "type": "null"
      +            }
      +          ],
      +          "default": null,
      +          "description": "Longest answer accepted, in characters. Null for choice fields, which must match one of options exactly."
      +        },
      +        "options": {
      +          "items": {
      +            "type": "string"
      +          },
      +          "type": "array"
      +        },
      +        "question": {
      +          "type": "string"
      +        },
      +        "replaces": {
      +          "default": "",
      +          "type": "string"
      +        },
      +        "required": {
      +          "type": "boolean"
      +        },
      +        "type": {
      +          "type": "string"
      +        }
      +      },
      +      "required": [
      +        "key",
      +        "label",
      +        "question",
      +        "type",
      +        "required"
      +      ],
      +      "type": "object"
      +    },
      +    "type": "array"
      +  },
      +  "slug": {
      +    "type": "string"
      +  },
      +  "source_url": {
      +    "type": "string"
      +  },
      +  "title": {
      +    "type": "string"
      +  },
      +  "when_needed": {
      +    "type": "string"
      +  }
      +}
    • addedOutput schema / required
      Added value: +[
      +  "slug",
      +  "title",
      +  "category",
      +  "description",
      +  "when_needed",
      +  "source_url",
      +  "fields"
      +]
  2. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds only workflow context, not behavioral traits like rate limits or what the returned fields look like. An output schema exists, so return-format detail is not required here.

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?

A single sentence with zero filler, front-loaded with the trigger ('after choosing a template slug') and ending with the purpose. Every clause earns its place.

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?

For a simple, read-only, one-parameter tool with a full output schema and complete annotations, the description covers placement in the workflow adequately. Nothing an agent needs to invoke it correctly is missing, though it is minimal.

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?

With a single parameter at 100% schema description coverage, the schema already explains that 'slug' is a template slug from list_templates. The description reinforces the source of the slug but adds no format, syntax, or validation detail beyond the schema, matching the baseline for fully documented parameters.

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 specific verb+resource ('read the fill-in fields') scoped to a template slug, so an agent knows exactly what it returns. It also implicitly distinguishes itself from siblings by referencing the slug source (list_templates) and the follow-up (generating a document). It stops short of explicitly contrasting itself with any sibling by name.

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 clear sequencing guidance: use it 'after choosing a template slug' and 'before generating a document.' This effectively tells the agent when in the workflow to call it relative to list_templates and generate_document. No when-not conditions or edge cases are mentioned, keeping it below a 5.

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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