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

Annotations already declare readOnly/openWorld/idempotent, but the description goes beyond them: it reveals that company data comes from SEC EDGAR/XBRL with correct off-calendar fiscal year handling, that results are sorted by the primary metric, and that output includes paired data plus citation URIs. 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 dense but every sentence earns its place: trigger phrases, preference instruction, type-specific data sources, fiscal-year handling, sorting behavior, and return format. It is front-loaded with usage intent and contains no filler.

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?

Even without an output schema, the description fully specifies return contents (paired data + pipeworx:// citation URIs), result ordering, and per-type data sources. For a two-parameter comparison tool, it covers all necessary operational context.

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%, but the description enriches both parameters: 'type' is explained with what data each enum value pulls (10-K financials vs FAERS/trial counts), and 'values' is clarified with examples like tickers ([AAPL, MSFT]) and drug names ([ozempic, mounjaro]). This adds meaning beyond the bare schema definitions.

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 concrete trigger phrases ('Compare X and Y', 'X vs Y', 'which is bigger') and clearly states the tool's function: side-by-side comparison of 2-5 companies or drugs in one parallel call. It distinguishes itself from sibling tools by explicitly naming the alternative ('sequential single-pack lookups') and detailing the exact data sources per entity type.

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 instructs agents to 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', providing clear usage guidance. It also explains the two modes (company vs drug) and gives example queries, making it obvious when to invoke this tool versus alternatives.

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