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canva_autofill

Create a new design from a brand template by injecting supplied text and image data into defined fields.

Instructions

Generate a new design from a brand template. data example: {"headline": {"type": "text", "text": "Promo"}, "photo": {"type": "image", "asset_id": "..."}}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
titleNo
brand_template_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden, and it discloses almost nothing behavioral: no indication that it creates a persistent design (side effect), no auth/quota/rate-limit notes, no statement about what happens to unfilled placeholders, and no return information.

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 compact sentences with the purpose front-loaded and the concrete example immediately after. The example is useful but abbreviated ('...' placeholders) and slightly cryptic, leaving a bit of decoding work for the reader.

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?

For a write tool with a nested, fully opaque parameter, no annotations, and no output schema, the description is thin. It should at minimum explain the autofill concept, where the required ids come from, and what the caller receives, none of which is present.

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 `data` is an opaque additionalProperties object, so the schema explains nothing. The inline JSON example does add real, non-redundant value about the `data` shape, but it never explains where `brand_template_id` comes from or what `title` controls, so it only partially compensates.

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 clear verb and resource: 'Generate a new design from a brand template.' However, it offers no differentiation from the near-identical sibling 'canva_make_from_template', and it never mentions the defining trait implied by the tool name — autofilling template placeholder fields with supplied data.

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 when-to-use, when-not-to-use, or alternative-routing guidance. An agent cannot tell from this text whether it should prefer this over canva_make_from_template, nor that canva_brand_template_fields / canva_list_brand_templates must be called first to discover valid ids and field names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.