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

Annotations already declare read-only/idempotent behavior, but the description adds substantial behavioral context: data sources (SEC EDGAR/XBRL, FAERS), precise metrics pulled, off-calendar fiscal year handling, sorting by primary metric, and output structure with citation URIs. This significantly exceeds annotation coverage.

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 longer than typical but every clause carries useful information—trigger phrases, data specifics, sorting behavior, and output format. It could be slightly tighter, but there is no fluff or redundancy.

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 fully covers what the caller will receive: paired data, citation URIs, and sorted results. It addresses tool complexity (two entity types, different data sources) and leaves no major gap in understanding.

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 elevates parameter understanding: it explains what type='company' vs 'drug' actually fetch and provides concrete examples for the values array (tickers, drug names). It adds semantic depth well beyond the schema's terse field 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 concrete trigger phrases and states the core function: 'side-by-side comparison of 2–5 companies or drugs in ONE parallel call.' It clearly distinguishes from sequential single-pack lookups and sibling entity_profile, making the tool's purpose unmistakable.

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 when comparing entities' and provides numerous natural-language examples that signal when to invoke. This gives clear when-to-use guidance and names the alternative approach it replaces.

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