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

Beyond the annotations (readOnlyHint, openWorldHint), the description discloses meaningful behavior: match ranking order, error handling for no matches, and the constraint that only SEC registrants with a listed ticker are searchable. These details let an agent predict edge cases. No contradiction with annotations exists.

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 well-structured into Args, Returns, Examples, Use when, Don't use, and Errors. Every section carries operational value, the core purpose is front-loaded, and there is no filler or redundant prose.

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 2-parameter, read-only lookup tool with an output schema, the description is complete: accepted input forms, output shape, ranking, error behavior, and routing to alternatives are all covered. An agent has everything needed to decide whether and how to call it correctly.

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?

Input schema coverage is 100%, so the baseline is 3, but the description adds value with concrete example mappings ('find Apple's CIK' -> {query: 'AAPL'}, 'companies named Berkshire' -> {query: 'Berkshire', limit: 5}), accepted ticker formats like BRK-B/BRK.B, and ranking semantics that affect result interpretation. The Args section duplicates the schema, but the examples and context push it 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 states a specific verb and resource: 'Search SEC EDGAR registrants (US-listed companies) by ticker, company name, or CIK' and identifies the key output (the 10-digit zero-padded CIK). It clearly differentiates from sibling search_dart_company by restricting scope to US-listed SEC registrants, so an agent can distinguish it without inspecting other tools.

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 has explicit 'Use when' and 'Don't use for' sections that name exact conditions and alternatives: use it to get a CIK or disambiguate a name before get_edgar_* tools, skip it for exact tickers, and use search_dart_company for Korean companies. This is model guidance for when to invoke the tool vs alternatives.

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