export_mapEngine-ready map JSON built from the SAVED level data, with custom-field values baked in. For the zip bundle (per-tile PNGs, loader scripts, tileset files) use get_export_command instead.
| Name | Required | Description | Default |
|---|---|---|---|
| mapId | Yes | Map id. | |
| engine | No | Target engine (default tiled). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation as read-only, idempotent, and non-destructive. The description adds useful behavioral context by stating output is 'engine-ready map JSON' from 'SAVED level data' with custom fields baked in, clarifying the source and transformation. No contradictions found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, with the primary purpose stated first and the alternative tool mentioned second. Every word adds value, and there is no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple export tool with only two parameters and full schema coverage, the description adequately conveys the output type (JSON), source data (SAVED level), included transformations (custom-field values baked in), and alternative use case (zip bundle). No output schema is needed, and the explanation covers the essential context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with clear parameter names and descriptions for mapId and engine. The description does not add parameter-level details, but since the schema already fully documents both parameters, the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool produces 'Engine-ready map JSON' from saved level data with custom-field values baked in. It distinguishes itself from the sibling get_export_command, which handles the zip bundle, making the tool's specific purpose and resource unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly directs users to get_export_command for the zip bundle alternative, providing clear when-to-use guidance. It also implies the tool is for JSON-only exports, which aligns with its title and avoids confusion with sibling export-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, and the descriptions are extremely detailed with cross-references (e.g., animate_asset vs frame_animation vs generate_character_animation). A few pairs like reprocess_asset vs revise_asset could be confused initially, but their descriptions and use cases are explicit enough to prevent misselection.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., create_project, get_asset, cancel_job). Verbs are imperative and nouns are appropriately singular/plural, making the API predictable and readable.
At 41 tools, the server is far beyond the 15-25 range considered reasonable for most APIs. While the domain is broad (project, assets, characters, animations, jobs, exports, credits), the sheer number creates a heavy surface that may overwhelm agents and suggests the API could be consolidated into higher-level operations.
The tool set covers the full creative pipeline: project creation, asset/character generation, animation (both AI and frame-based), revisions, exports, and job management. Minor gaps include lack of delete operations for assets/characters/projects and no listing of all jobs, but these are not critical for the core workflow and are likely intentional for a generative art platform.