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

Beyond the annotations (which already indicate read-only, open-world, idempotent), the description reveals important behavioral details: it makes parallel calls, correctly handles off-calendar fiscal years, sorts results by primary metric, and returns citation URIs. Nothing contradicts the 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 informative but slightly wordy, especially the opening line which mixes many examples. However, it front-loads the key action and contexts. Every sentence adds value, but minor trimming could improve conciseness.

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 moderate complexity (two parameter types, two entity types, no output schema), the description covers what data is returned, cites sources, explains sorting, and quantifies efficiency. It leaves no critical gaps for an agent to understand how to invoke and interpret results.

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 schema already documents type and values, but the description adds critical meaning: it explains what values mean (tickers/CIKs for companies, drug names for drugs), the allowed range (2-5 items), and how each type affects the data pulled. This fully compensates for any schema brevity.

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 that the tool performs side-by-side comparisons of 2–5 companies or drugs in a single parallel call. It specifies the data sources (SEC EDGAR for companies, FAERS/FDA for drugs) and the exact metrics returned, making the purpose unmistakable and distinguishing it from single-entity tools like entity_profile.

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 explicitly says 'ALWAYS PREFER over sequential single-pack lookups' and quantifies the efficiency gain ('Replaces 8–15 sequential lookups'). It gives strong guidance on when to use, though it does not explicitly mention cases where this tool should not be used, leaving room for improvement.

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