create_datashader_plot

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

With no annotations provided, the description explains the rasterization behavior and scalability to millions of points. Does not disclose potential side effects, but as a creation tool, behavioral transparency is adequate.

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?

Two concise sentences that front-load the purpose and key usage guidance. Every sentence adds value; no waste.

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?

Given the presence of an output schema and full parameter coverage, the description covers the core purpose, use case, and method (hvPlot integration). It does not mention aggregation options or colormaps but these are in schema; overall sufficient.

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%, so baseline 3 is appropriate. The description does not add individual parameter details beyond the schema but provides context for x and y columns. No additional value beyond the schema.

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?

Description clearly states it creates a datashader-powered plot for large datasets (10K+ points). It specifies the technique (rasterization into pixel-density heatmap) and distinguishes from sibling tools like create_plot (for small data).

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?

Explicitly states 'for large datasets (10K+ points)' and 'works with millions of points where scatter plots would be unusable', providing clear guidance on when to use. Lacks explicit mention of when not to use but implies alternatives (scatter plots).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.