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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral context: it pulls latest financial data from SEC EDGAR/XBRL for companies (with off-calendar year handling) and FAERS data for drugs, sorts results by primary metric, and returns citation URIs. No contradictions.

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?

Every sentence in the description serves a purpose. It starts with intuitive query examples, then states the core functionality, gives a usage preference, details each type's output, explains sorting and output format, and ends with efficiency claim. No fluff; information is front-loaded.

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 the tool's moderate complexity (two simple parameters, no output schema), the description is complete. It covers input meaning, output format (paired data + citations), sorting behavior, and data sources. For a comparison tool with clear annotations, nothing essential is missing.

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?

The input schema already provides good descriptions for both parameters (100% coverage). The description adds further meaning by detailing what each 'type' retrieves (company financials vs. drug counts) and providing examples for 'values' per type. This goes beyond the schema, justifying a score above baseline.

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 performs side-by-side comparison of 2-5 companies or drugs. It uses specific verbs like 'compare' and lists concrete query examples. It distinguishes from sibling tools by explicitly preferring this over sequential 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?

The description provides explicit when-to-use guidance with example queries (e.g., 'Compare X and Y', 'which is bigger'). It also states 'ALWAYS PREFER over sequential single-pack lookups', effectively excluding use cases where the agent should not use it (i.e., for single entity queries). No misleading guidance.

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