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generate_figure

Generate publication-ready figures from PMIDs, preprints, or freeform briefs. Choose from multiple figure types and output formats for academic papers.

Instructions

Generate a publication-ready visual asset.

Single high-level entrypoint: callers may provide planned_payload directly, or pass a PMID / generic source brief and let the use case plan internally before rendering.

output_format: Optional final raster delivery type such as png, gif, jpeg, or webp. MCP applies the conversion internally after generation when possible.

figure_type: auto | flowchart | mechanism | comparison | infographic | anatomical | timeline | data_visualization

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pmidNo
languageNozh-TW
output_dirNo
figure_typeNoauto
output_sizeNo1024x1536
source_kindNopaper
source_titleNo
output_formatNo
source_summaryNo
target_journalNo
planned_payloadNo
source_identifierNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description adds some behavioral context: internal planning when a source brief is provided, and internal output_format conversion 'when possible.' However, it omits side effects like file overwriting, permission needs, or failure modes, which are important for a generation tool.

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?

The description is under 100 words and front-loaded with the core purpose. The phrase 'Single high-level entrypoint' is slightly redundant with 'let the use case plan internally,' but overall every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The high-level workflow is clear, and the output schema exists so return values need not be described. However, many input parameters remain unexplained, and the relationship to sibling tools like plan_figure or edit_figure is only implicit, leaving room for more guidance.

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

Parameters2/5

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

There are 12 parameters with 0% schema description coverage, so the description must compensate. It explains output_format and figure_type in some detail and mentions planned_payload/source brief, but leaves most parameters (language, output_dir, output_size, source_kind, target_journal, etc.) undocumented, providing only partial compensation.

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 generates a publication-ready visual asset, with a specific verb and resource. It distinguishes itself as the 'single high-level entrypoint' among siblings, and lists supported figure types, giving clear scope.

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?

The description explains when to use the tool: as a high-level entrypoint where callers can provide a planned_payload or a source brief. It implicitly differentiates from more granular siblings like plan_figure and edit_figure, but does not explicitly state when not to use it or name alternatives.

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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