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tool_meme_splitter

Split an uploaded image into a grid of parts. Set rows and columns to get JSON with each divided section.

Instructions

[image] Meme Splitter

Parameters:

  • file (bytes): File

  • rows (number): Rows

  • cols (number): Cols

Outputs:

  • parts (json): Parts

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
colsNoCols
fileNoFile (base64 file payload)
rowsNoRows
partsNoParts
Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits, but it only states that it splits into parts without explaining the output format, image requirements, grid interpretation, or side effects (e.g., whether the original file is modified). No edge cases, limitations, or error behavior are mentioned, so the agent lacks essential behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short, which is concise, but it is under-specified rather than efficiently complete. It lists parameters and output without any explanatory prose, making it a minimal placeholder rather than a well-structured description. It is not bloated, but it also does not earn its place by adding value beyond the schema.

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

Completeness2/5

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

The tool has no output schema and no annotations, so the description carries full responsibility for completeness. It fails to explain how rows and cols map to the output 'parts', what format the parts take, or any constraints (e.g., image types, maximum grid size). An agent would struggle to correctly configure inputs or interpret results based solely on this description.

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 coverage is 100%, but the schema descriptions are minimal (e.g., 'Rows', 'Cols'). The tool description adds no additional semantics beyond repeating parameter names, so it does not compensate for the schema's lack of detail. Baselines at 3 due to high coverage, but no added value is present.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description indicates 'Meme Splitter' and lists parameters (file, rows, cols) and output (parts), which clearly implies splitting an image into a grid of sub-images. No explicit verb phrase like 'split an image', but the tool name and parameter list make the core purpose evident. It does not strongly distinguish from sibling image tools, but the 'meme' prefix gives specific context.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, nor any conditions or exclusions. It is purely a parameter and output listing with no contextual advice, leaving the agent to infer usage entirely.

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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