generate_liquid_chart

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

Annotations already declare readOnlyHint=true, indicating this is a safe read operation that generates a chart without modifying data. The description adds value by specifying the output is a visualization (liquid chart) and providing example use cases, but it does not disclose additional behavioral traits like performance considerations, error handling, or format of the generated chart (e.g., image file, URL).

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 a single, well-structured sentence that efficiently conveys the tool's purpose and usage with zero waste. It is front-loaded with the core function and includes illustrative examples, making it easy to understand quickly without unnecessary details.

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 tool's complexity (7 parameters, nested objects) and rich schema coverage (100%), the description is complete enough for its purpose. It clarifies the tool's niche among siblings and provides usage context. However, without an output schema, it does not explain the return value (e.g., chart image or data), leaving a minor gap in completeness.

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 description coverage is 100%, so the schema fully documents all 7 parameters, including their types, defaults, and constraints. The description adds minimal semantic context by mentioning 'percentage' and examples like occupancy rate, which aligns with the 'percent' parameter, but does not provide additional meaning beyond what the schema already covers.

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's purpose with a specific verb ('generate') and resource ('liquid chart'), and explicitly distinguishes it from sibling tools by specifying it visualizes 'a single value as a percentage' (e.g., occupancy rate, completion percentage), unlike other chart types like bar, line, or pie charts that typically show multiple data points or categories.

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 provides clear context for when to use this tool—for visualizing a single percentage value—with examples like occupancy rate or project completion. However, it does not explicitly state when not to use it or name alternatives among the sibling tools, such as using a pie chart for parts of a whole or a bar chart for comparisons.

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