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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so safety is covered. The description adds critical behavioral context beyond annotations: it fans out across multiple sources in one parallel call, returns specific data fields, and discloses that the USPTO PatentsView API is sunsetting and 'soft-fails until reactivated.' This level of disclosure goes beyond the structured hints.

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 clause adds useful information. Example queries are slightly redundant but serve as natural-language triggers. The single-paragraph structure could be improved with bullet points for readability, but it remains appropriately sized for the tool's complexity. No filler words.

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?

There is no output schema, so the description must explain return values—and it does: cik, company_name, recent_filings with URIs, fundamentals (LATEST 10-K Revenues, NetIncomeLoss, Cash), patents, news mentions, LEI. It also covers source details, fallback behavior, and accepted input formats. This is fully complete for a complex tool with no output schema.

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 adds meaningful semantics beyond the schema: it gives concrete examples ('AAPL', '0000320193'), clarifies the zero-padding requirement for CIKs, and explicitly warns that names are not supported. It also explains the enum constraint for type ('Only company supported today'), which reinforces the schema but also adds context about future plans.

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 states a specific verb+resource: 'full cross-source profile of a US public company in ONE parallel call.' It also distinguishes from siblings by explicitly saying 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups' and lists concrete example queries. This makes the tool's purpose unambiguous and differentiated.

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 when-to-use guidance: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also states a clear exclusion: 'names not supported (use resolve_entity first if you only have a name).' This is exactly the kind of alternative/fallback guidance needed.

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