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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds substantial behavior details beyond these: pulls latest 10-K data from SEC EDGAR/XBRL, handles off-calendar fiscal years, sorts by primary metric, returns paired data with pipeworx:// citation URIs, and notes the parallel call optimization. This is rich, non-redundant context.

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 longer than typical but every sentence contributes value—trigger examples, core function, type details, and output behavior are all relevant. It is front-loaded with user-intent phrases and structured logically. While somewhat dense, it earns its length given the tool's complexity.

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?

For a tool with no output schema and moderate complexity, the description covers key contextual aspects: data sources, edge cases (off-calendar fiscal years), result sorting, output format (paired data + citation URIs), and the performance benefit. It could elaborate on potential error scenarios or exact return structure, but for a comparison tool this is sufficiently complete.

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 coverage is 100% for both parameters, so the baseline is 3. The description adds meaning beyond the schema by clarifying what each type ('company' vs 'drug') retrieves, the expected format of values (tickers/CIKs vs drug names), and the sorting behavior. This enhances the agent's understanding of parameter usage beyond the schema's simple 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 the tool's purpose: 'side-by-side comparison of 2–5 companies or drugs in ONE parallel call.' It provides specific trigger phrases ('X vs Y', 'rank these companies') and distinguishes itself from sequential lookups by stating it replaces 8–15 sequential calls, differentiating 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 explicitly states 'ALWAYS PREFER over sequential single-pack lookups when comparing entities,' providing clear when-to-use guidance. It also explains the two type-specific behaviors (company vs drug). However, it does not name a specific alternative tool or explicitly state when not to use it beyond the comparison context, so a small gap remains.

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