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Generate text

generate_text

Generate text with GenMagic: copy, an answer, a draft, code, an SVG graphic, or a complete web page. Pass 'type' to make a specific artifact ("website" for a full self-contained HTML page, "svg" for a vector graphic, "code" for a code snippet, "writing" for prose); omit it for plain text. Attach files for the model to read via 'attachments' (PDF, Word/Excel/PowerPoint, CSV, text/code, images, audio); GenMagic converts anything a model cannot ingest natively. If the caller's account has brand personalization on, the output comes out on-brand automatically, and a website or svg also picks up the brand's palette and typeface.

Input Schema

NameRequiredDescriptionDefault
typeNoThe kind of artifact to make. Omit for plain text.
modelNoOptional GenMagic model id for the text (call list_models with category "text" for the ids and prices). Omit it to let GenMagic choose its default.
promptYesWhat to write or produce.
systemNoOptional system instruction to steer tone, role, or format.
attachmentsNoFiles for the model to read. Each item is { name, mime, dataUrl } where dataUrl is a base64 data URL (data:<mime>;base64,...). Any type is accepted: PDF, docx/xlsx/pptx, csv, text/code, images, audio.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / model
      Added value: +{
      +  "description": "Optional GenMagic model id for the text (call list_models with category \"text\" for the ids and prices). Omit it to let GenMagic choose its default.",
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare openWorldHint=true and non-idempotent/non-destructive, so the safety profile is covered. The description adds genuinely non-obvious behavior: account-level brand personalization silently alters output (palette and typeface for website/svg), and non-native file types are auto-converted. It stops short of stating latency, cost, or output shape, but list_models is named as the pricing path.

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?

Front-loaded with the core action and artifact options, then attachments, then brand behavior — a sensible order. It is one dense paragraph and re-enumerates the 'type' values already spelled out in the schema, which is mild waste but not distracting.

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?

No output schema exists, so the description carries the return-value burden; it does so implicitly (a self-contained HTML page, a vector graphic, a snippet, prose), though it never states the response envelope or where the artifact lands. For a five-parameter generative tool with full schema coverage and rich annotations, that is a small residual gap.

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?

Schema coverage is 100%, so the baseline is 3; the description earns above that by explaining the consequence of omitting 'type' (plain text) and by clarifying the attachment contract in prose — including that any file type is accepted and converted server-side. The restated enum values overlap with the schema rather than extend it.

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?

States a specific verb and resource ("Generate text with GenMagic") and enumerates the concrete artifact classes it can produce, which cleanly separates it from generate_image, generate_music, and generate_speech. An agent can identify the tool's job without opening the schema.

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 explicit selection logic for its own 'type' parameter (use "website"/"svg"/"code"/"writing", omit for plain text) and explains when to use attachments. It never routes to or excludes siblings, however — notably it does not clarify how "svg" here differs from generate_image, which is a plausible point of confusion.

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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