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

Annotations indicate readOnly, openWorld, and idempotent hints. The description adds context well beyond annotations: it explains the specific financial data pulled for companies (revenue, net income, cash, long-term debt) and drug data (FAERS counts, FDA approvals, trials). It also notes that results are sorted by primary metric and that it replaces 8-15 sequential lookups.

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 concise yet packed with information. It front-loads the purpose with example queries, every sentence adds value, and there is no redundant or irrelevant content.

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?

With no output schema, the description covers what is returned: 'paired data + pipeworx:// citation URIs per entity.' It also details the specific data points for each type, making the tool's behavior fully understandable.

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%, but the description adds significant meaning: for 'type' it explains the data source for each enum value; for 'values' it gives concrete examples (tickers/CIKs for company, drug names for drug) and constraints (2-5 items). This goes beyond the schema's brief 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 starts with natural language triggers like 'Compare X and Y' and clearly states it provides side-by-side comparison of 2-5 companies or drugs in one parallel call. It distinguishes itself from sequential single-pack lookups and details what data is pulled for each entity type.

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 states 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' This provides clear guidance on when to use this tool and implies when not to use other tools. Examples of queries that trigger the tool are given.

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