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

Annotations already indicate readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds critical behavioral context: for 'company', it pulls 'LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL' and handles 'off-calendar fiscal years correctly (AAPL Sep, NVDA Jan).' For 'drug', it pulls 'FAERS adverse-event counts, FDA approval counts, active trial counts.' It also states 'Results sorted by primary metric' and returns 'paired data + pipeworx:// citation URIs per entity.' No contradictions 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 well-structured and front-loaded with trigger phrases and core purpose. Every sentence adds value (trigger examples, use-case preference, data details, sorting, return format, efficiency claim). It is slightly long but efficient for the information density. A minor trim could be possible, but overall excellent.

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 2 parameters and no output schema, the description is remarkably complete. It covers both entity types with data sources, sorting behavior, return format (paired data + citation URIs), edge cases (off-calendar fiscal years), and an efficiency comparison (replaces 8-15 lookups). No gaps for an agent to decide to invoke or interpret results.

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 description coverage is 100%, with clear enum for 'type' and array constraints for 'values'. The description adds context beyond schema: for 'company', it specifies 'tickers/CIKs' and gives examples; for 'drug', specifies 'names' and examples. It also explains what data each type returns, aiding agent understanding.

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 starts with user query examples ('Compare X and Y', 'which is bigger') and explicitly states 'side-by-side comparison of 2–5 companies or drugs in ONE parallel call.' It distinguishes from sibling tools by noting 'ALWAYS PREFER over sequential single-pack lookups' and that it replaces '8–15 sequential 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 lists trigger phrases ('compare', 'X vs Y', 'rank these', 'head to head') and explicitly says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It provides clear when-to-use guidance and implies when not to use (avoid single-entity lookups).

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