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TokDar2410621

publiar-mcp

render_visual

Transform a LeadMagnetVisualSpec into a PNG image, return base64-encoded data with mime-type, and support 8 visual archetypes.

Instructions

Rend un LeadMagnetVisualSpec en PNG (1080x1080 ou ratio adapté). Retourne le PNG encodé base64 + mime-type. 8 archétypes supportés.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
specYesLeadMagnetVisualSpec — discriminé par archetype
Behavior4/5

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

With no annotations provided, the description carries the burden of disclosure. It states the output is a base64-encoded PNG with mime-type, dimensions, and supported archetypes, which gives clear behavioral insight. It does not mention error handling or side effects, but for a render tool, these are less critical and the key output details are covered.

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?

The description is two sentences with no redundant content. It front-loads the core action and includes essential details (output format, dimensions, archetype count) without unnecessary words.

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?

Given the tool's simplicity and the schema covering the parameter, the description adequately covers the main aspects: input, output, format, and constraints. It lacks details about potential errors or prerequisites, but the core functionality is well specified, making it sufficient for selection and basic invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already describes the 'spec' parameter as a LeadMagnetVisualSpec discriminated by archetype. The description adds the fact that 8 archetypes are supported, which provides extra semantic value beyond the schema. However, it does not detail how to construct or specify the spec, but the schema covers the type.

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?

The description clearly states the tool renders a LeadMagnetVisualSpec into a PNG, specifying dimensions (1080x1080 or adapted ratio) and return format (base64 + mime-type). This is specific and distinguishes it from sibling tools like render_gif.

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

Usage Guidelines3/5

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

The description implies usage when a PNG rendering of a visual spec is needed, and mentions supported archetypes, but it does not explicitly differentiate from related tools like render_gif or provide when-not-to-use guidance. The context is sufficient to infer applicability but lacks explicit exclusions.

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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