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

The description adds significant behavioral context beyond annotations: it explains data sources (SEC EDGAR/XBRL for companies, FAERS for drugs), handles fiscal year offsets, sorts by primary metric, and returns citation URIs. This is valuable information not captured in annotations.

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 dense and front-loaded with common trigger phrases, making it efficient. However, it is a single paragraph without separators, slightly reducing readability. Still concise, as every sentence adds value.

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 complexity of the tool (two entity types, multiple data sources, sorting), the description is complete. It explains data pulled for each type, sorting behavior, and output format (paired data + URIs). No output schema, but the description provides sufficient detail.

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%, and the description adds meaning by specifying what data is pulled for each type (company vs drug) and giving examples for values (tickers/CIKs for companies, drug names for drugs). This enhances the schema descriptions.

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 explicitly states the tool does side-by-side comparison of 2-5 companies or drugs, with trigger phrases like 'compare X and Y', 'X vs Y', etc. It distinguishes from siblings by stating it should be preferred over sequential single-pack lookups.

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 clearly says to prefer this tool over sequential lookups when comparing entities, providing clear context for when to use. It implicitly suggests that for single entity lookups other tools like entity_profile are appropriate, but does not explicitly name those alternatives.

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