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

The description adds significant behavioral details beyond the annotations: ranking logic ('prefix-hit first, then name length'), result limit ('up to 5 matches'), and market suffix formatting (e.g., Japan `.T`, Hong Kong 00700.HK). This goes beyond the readOnlyHint/destructiveHint annotations to explain real output behavior.

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: a one-sentence purpose, a concise input breakdown, and an output explanation. Every sentence adds necessary information—no filler, no repetition of schema details. It is front-loaded with the most important instruction ('Use this FIRST') and remains 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 the tool is a simple lookup with no output schema, the description covers all essential aspects: what it accepts, what it returns, ranking behavior, and output format. It even explains market suffixes which is crucial for interpreting results. The description is complete for an agent to use the tool 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?

The schema already documents both parameters fully (100% coverage), including examples and market enum. The description adds value with concrete examples (e.g., 'Apple', '苹果', 'OpenAI') and clarifies that the market parameter can be omitted for global search. Since the schema carries most of the semantic weight, the description's extra examples and emphasis on the search scope earn a 4, not a 5.

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 uses a specific verb 'Resolve' with a clear resource ('company name, brand, or ticker substring to canonical ticker(s)'). It distinguishes itself from siblings by stating it is the first step before ticker-keyed tools, and it defines the scope of the query (company name/brand/nickname), making its purpose unambiguous.

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 when to use the tool: 'Use this FIRST when the user mentions a company by name/brand/nickname before running any ticker-keyed tool.' This also implies when not to use it (when you already have a canonical ticker), and names the alternative category (ticker-keyed tools). This is clear, actionable guidance.

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