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

Beyond the readOnly and idempotent annotations, the description reveals substantial behavioral details: parallel execution, data sources (SEC EDGAR/XBRL, FAERS), handling of off-calendar fiscal years, sorting by primary metric, and return of paired data with citation URIs. No contradictions with annotations; it adds rich context about how the tool operates.

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 well-structured, starting with query examples then core function, then type-specific details and return behavior. Every sentence adds value, though the paragraph is long. Front-loading the purpose and usage guidance makes it effective, so it earns a 4 rather than 5 only because it could be slightly more compact.

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 there is no output schema, the description explains what the tool returns ('paired data + pipeworx:// citation URIs per entity'), how results are sorted, and the specific metrics for each entity type. It covers all essential aspects for selection and invocation, including examples and edge cases like off-calendar fiscal years, making it highly 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?

Although the schema already covers both parameters at 100%, the description enriches their meaning: 'type' is explained with its enum values and what data each pulls, and 'values' is clarified with examples and constraints (2–5 tickers or names). This goes beyond the schema's basic descriptions, giving the agent a deeper understanding of how to populate them.

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's function: 'side-by-side comparison of 2–5 companies or drugs in ONE parallel call.' It includes concrete query examples and specific data pulled for each type, and distinguishes itself from siblings by explicitly saying 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.'

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?

Provides explicit guidance on when to use: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' This directly contrasts with likely alternatives like entity_profile, making it clear this tool is for multi-entity comparisons, not single-entity lookups. The 'Replaces 8–15 sequential lookups' further reinforces its use case.

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