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

Beyond the read-only, open-world, idempotent annotations, the description discloses data sources (SEC EDGAR/XBRL for companies, FAERS/FDA for drugs), sorting by primary metric, handling of off-calendar fiscal years, and return format with citation URIs. This adds substantial behavioral context 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 efficiently organized: it opens with usage triggers, states the core action and scope, then details type-specific data sources, sorting, and return format, ending with an efficiency note. Every sentence earns its place; no filler.

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?

Despite having no output schema, the description fully covers return format (paired data + pipeworx:// URIs), sorting behavior, data sources, and the efficiency benefit over sequential lookups. It provides all necessary context for an agent to select and invoke this tool 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?

Though the schema documents both parameters (type and values) with 100% coverage, the description enriches this by explaining what each type pulls (10-K financials vs adverse-event counts), providing value examples, and clarifying the 2–5 entity limit. This goes far beyond the schema's basic 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 clearly defines a side-by-side comparison tool for 2–5 entities, with specific verbs like 'compare' and 'rank'. It distinguishes itself from sequential lookups and sibling tools like entity_profile by explicitly stating '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?

Explicitly lists trigger phrases such as 'Compare X and Y', 'X vs Y', 'which is bigger', and 'rank these companies', and states when to prefer this tool over alternatives. It also gives concrete examples for both company and drug types, making the appropriate use case unmistakable.

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