get_promotional_language_check_prompt

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

No annotations are provided, so the description must fully disclose behavior. It describes the review function but does not clarify that the tool returns a prompt (as implied by the name) rather than performing direct analysis. This omission could mislead about the tool's actual output. Data safety note is helpful but insufficient.

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 very concise, with the purpose stated upfront, followed by specific flags and a data safety note. Every sentence adds value without redundancy, making it easy to scan.

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?

The tool has an output schema, reducing the need to describe return values. However, the description misses the critical point that it generates a prompt (not a direct analysis), which is important for understanding the tool's nature. Given the complexity and sibling context, the description is moderately complete but has a key gap.

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 0%, so the description must compensate. It explains the text_excerpt as 'medical document text' and implies the regulatory_framework parameter via 'compliant language' and the default 'FDA'. However, it does not explicitly describe the parameter's role or how different values affect the check, leaving ambiguity.

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 reviews medical document text for promotional or non-compliant language, specifying it flags superlatives, causal claims, off-label implications, and comparative claims. This distinguishes it from sibling tools (e.g., get_manuscript_edit_prompt) which focus on other medical writing tasks.

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 mentions 'Invaluable for MLR pre-review preparation', providing context for when to use. However, it does not explicitly state when not to use or mention alternative tools (e.g., for other compliance checks). The intended use is clear but lacks exclusions.

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