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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses data sources (SEC EDGAR/XBRL, FAERS), specific metrics (revenue, net income, adverse-event counts), sorting behavior, and output format (paired data + pipeworx:// citation URIs). It even notes efficiency ('Replaces 8–15 sequential lookups'). 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?

The description is information-dense but remains relevant and efficiently phrased. It front-loads example queries and core purpose, then adds specifics. Slightly longer than ideal, but every clause contributes value, so it earns a high score.

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 fully compensates by explaining the return data (paired data, citations), sorting logic, and entity-specific attributes. It also anchors usage within the tool ecosystem by referencing alternatives. This is a comprehensive description for a 2-parameter tool.

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 though the schema covers 100% of parameters, the description adds significant meaning: it defines what type='company' retrieves (latest 10-K financials) versus type='drug' (FAERS, FDA, trial counts), and provides concrete examples for values (tickers/CIKs, drug names). This goes well beyond the schema's minimal descriptions and aids correct invocation.

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 states the tool's function: 'side-by-side comparison of 2–5 companies or drugs in ONE parallel call.' It gives specific example user phrasings ('Compare X and Y', 'which is bigger') and distinguishes from sequential single-pack lookups, making the purpose unmistakable and differentiating it 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?

Explicit usage guidance is provided: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It also clarifies when to use company vs drug types and mentions off-calendar fiscal year handling, giving clear context for both selection and expected behavior.

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