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

Despite annotations already declaring readOnly, idempotent, and non-destructive, the description adds substantial behavioral context: parallel execution, SEC EDGAR/XBRL data sourcing, off-calendar fiscal year handling, sorting by primary metric, and citation URI returns. No contradiction with 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?

Description is dense but well-structured: trigger phrases lead, followed by usage rule, type-specific data details, and return info. Minor redundancy in repeating the benefit over sequential lookups, but every sentence earns its place.

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?

Covers both entity types, sorting behavior, return format (paired data + citation URIs), and performance benefit. Without an output schema, it could be more explicit about exact return fields for each type, but it is complete enough for a complex tool with two modes.

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% with clear descriptions for type and values. The description enriches semantics by specifying what type='company' pulls (revenue, net income, cash, long-term debt) and type='drug' pulls (FAERS, FDA approvals, trials), adding value beyond the schema.

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?

Description explicitly states side-by-side comparison of 2–5 companies or drugs in ONE parallel call, with trigger phrases like 'X vs Y' and 'rank these companies.' It clearly distinguishes itself from sequential lookups and sibling tools by emphasizing entity comparison versus single-entity 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?

Provides explicit when-to-use rule: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' Also lists natural-language triggers and differentiates behavior by type ('company' vs 'drug'), giving concrete guidance for selecting the tool.

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