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

Beyond the read-only/idempotent annotations, the description discloses data sources (SEC EDGAR/XBRL, FAERS), handles edge cases (off-calendar fiscal years), sort order by primary metric, and the return of paired data with citation URIs. It also states the efficiency gain ('Replaces 8–15 sequential lookups'), giving a complete behavioral picture without contradicting 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 but every sentence earns its place: trigger examples, preference rule, data source details for both types, sort behavior, return format, and efficiency claim. It is front-loaded with core purpose and structured to separate company vs drug specifics.

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 return style (paired data + citation URIs) and sorting, but does not fully specify the response schema (e.g., exact field names, metric definitions). Minor gap for a tool with two entity types and a ranking output, but sufficient for an agent to select and invoke it.

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?

Even with 100% schema coverage, the description adds significant meaning to the `type` parameter by explaining what data each type fetches and how results are ordered. It also provides concrete examples for `values` (tickers/CIKs, drug names), enriching the schema's enum and array 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 opens with explicit example queries and states 'side-by-side comparison of 2–5 companies or drugs in ONE parallel call.' It clearly identifies the resource (companies/drugs) and distinguishes from sibling single-entity lookups by adding 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.'

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?

It provides concrete trigger phrases ('Compare X and Y', 'X vs Y', 'rank these companies') and explicitly directs preference over sequential lookups. The description also differentiates behavior by type (company vs drug), giving users clear guidance on when each mode is appropriate.

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