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Render a smart prompt template

render_template

Fills curated photography, design, or editing templates with your values and returns a ready-to-use image prompt for generate_image or edit_image.

Instructions

Fills a curated photography/design/editing template with your values and returns a ready-to-use prompt. Feed the result straight into generate_image's or edit_image's prompt argument.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoValues for the template's fields (see list_templates for each template's field names).
templateYesTemplate id. See list_templates for the full catalog. One of: photo_realistic_scene, product_mockup, logo_design, sticker_illustration, infographic, minimalist_negative_space, add_remove_element, inpaint_replace, style_transfer, combine_images

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that this is a pure transform producing a prompt string (no side effects implied), but says nothing about failure modes such as an unrecognized template id or missing/extra field values, which are realistic for a 10-template catalog with a free-form fields object.

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?

Two sentences, zero filler, and the input action is front-loaded ahead of the downstream wiring. 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 2-parameter tool with no output schema, the description covers what comes back (a usable prompt) and where to send it, and the nested `fields` object is explained by the schema. Only the error/edge-case behavior is left unaddressed.

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 100% and the template enum list and fields-object semantics are fully documented in the schema, so the schema does the heavy lifting. The description's 'with your values' adds no syntax or format detail beyond it, making the baseline 3 correct.

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?

Specific verb (fills/renders) plus resource (curated template) plus the concrete output (a ready-to-use prompt). It also implicitly separates itself from the generation siblings by being the pre-generation step that feeds them.

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?

Explicitly routes the agent forward: feed the result into generate_image's or edit_image's `prompt` argument, which is exactly the downstream action an agent needs. It does not state when *not* to use it (e.g., writing a prompt from scratch), so it stops short of a 5.

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