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

Annotations declare readOnly, openWorld, idempotent, and non-destructive. The description adds valuable context: data sources (SEC EDGAR/XBRL, FAERS), handling of off-calendar fiscal years, sorting by primary metric, and output format with pipeworx:// citation URIs. This goes well beyond annotations and enriches understanding of tool behavior.

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 but every sentence provides unique value. It front-loads common query phrasing, then states core function, then provides type-specific details, output behavior, and benefits. No fluff, well-structured, and appropriately sized for a tool with two entity types.

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 no output schema, the description adequately explains what the tool returns: paired data, sorted by primary metric, with citation URIs. It covers scope, data sources, edge cases (off-calendar fiscal years), and performance (replaces 8-15 lookups). Completely sufficient for an agent to select and invoke correctly.

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?

Although schema coverage is 100%, the description adds significant meaning to parameters. It explains what 'type' specifies in terms of data pulled (10-K financials for company, adverse events/approvals/trials for drug), and what 'values' accepts (tickers/CIKs vs names). It also notes max of 5 and min of 2 implicitly. This goes beyond 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?

Clearly states the tool performs side-by-side comparison of 2-5 companies or drugs in a single parallel call. The description is specific with verb 'compare' and resource 'entities', and it distinguishes itself from sequential single-pack lookups, making it distinct from siblings 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?

Explicitly says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', providing clear when-to-use guidance. It also gives trigger phrases and example queries, and differentiates between company and drug types, which informs the user on appropriate invocation.

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