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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is known. The description adds valuable behavioral details beyond the annotations: it authenticates fiscal-year handling ('off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan'), explains sorting ('Results sorted by primary metric'), and describes the return shape ('Returns paired data + pipeworx:// citation URIs per entity'). This goes well beyond what the annotations convey.

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 efficient. It front-loads the trigger phrases and core purpose, then breaks into type-specific details. Every sentence adds value, from the fiscal-year handling note to the sorting behavior. It is a bit long, but for a tool that handles two entity types with distinct data sources, the length is justified. No redundancy that wastes the reader's time.

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 needs to convey return values, and it does: 'Returns paired data + pipeworx:// citation URIs per entity.' It also explains data sources, entity count limits, sorting, and the efficiency gain. The only minor gap is that 'primary metric' is not explicitly defined per type (e.g., revenue for companies, adverse-event count for drugs), which could cause ambiguity for some queries. Overall, it is highly complete for the tool's read-only nature.

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 schema already covers both parameters with descriptions and enums, reaching 100% coverage. However, the description adds meaningful context by explaining what data each type retrieves (10-K revenue/net income/cash/debt vs. FAERS/adverse-event/trial counts) and giving concrete examples (['AAPL','MSFT'], ['ozempic','mounjaro']). It clarifies the 2–5 range in plain language. While the schema does the heavy lifting, the description enriches param meaning enough to deserve 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 opens with clear natural-language triggers ('Compare X and Y', 'X vs Y', 'rank these companies') and then states the core function: 'side-by-side comparison of 2–5 companies or drugs in ONE parallel call.' It explicitly distinguishes itself from alternatives by saying 'ALWAYS PREFER over sequential single-pack lookups' and 'Replaces 8–15 sequential lookups,' which clearly separates it from sibling tools 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?

The description provides explicit when-to-use guidance: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It also gives concrete query examples that should trigger this tool, and explains the difference between type='company' (10-K financial data) and type='drug' (FAERS/approval/trial data) so the agent knows which type to choose. This is strong usage direction.

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