add_analytics_line

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

With no annotations provided, the description carries the responsibility for disclosing behavior. It adds a useful caveat: 'Structure matched to the legacy analytics shape - verify the render in Desktop,' which warns about potential rendering issues and legacy compatibility. It also clarifies the meaning of 'label' as 'data-label text,' going beyond the schema. It doesn't discuss other side effects, but for a simple add-line operation this 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?

The description is three sentences with no wasted words. It's front-loaded with the purpose, then provides parameter rules, then adds a legacy caveat. Every sentence conveys unique, useful information.

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 tool with 9 parameters and no output schema, the description covers the purpose, parameter selection logic, and a key behavior caveat. It doesn't explain reportSessionId/page/visual, but those are standard and documented in the schema. The legacy note adds important context that a user might otherwise miss. It's complete enough for most use cases.

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?

The input schema already covers 89% of parameters with descriptions, but the description adds essential cross-parameter semantics by explaining how 'kind' determines which other parameters are needed (constant → value; min/max/average/median → measureTable+measure; trend/forecast → none). This grouping goes beyond individual parameter descriptions and is critical for correct invocation.

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 opens with a specific verb and resource: 'Add an ANALYTICS reference line to a chart.' This clearly states the tool's function and distinguishes it from sibling tools like add_chart or add_visual since it focuses on analytics reference lines specifically.

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 on how to use the tool by explaining which parameters are needed for each 'kind' (constant uses value; min/max/average/median use measureTable+measure; trend/forecast need no value). However, it does not explicitly name alternative tools or state when NOT to use this tool, so it stops short of full exclusions.

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