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

The description goes far beyond the readOnly/idempotent annotations by disclosing important behavioral traits: results may contain multiple legitimate issuances of the same company, authority varies by source, aggregated rows lack eligibility/KYC/custody claims, and missing yield/minimum/risk fields should be treated as absent rather than zero. 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 long but every section earns its place: purpose, search coverage, critical usage caveats, and the alternative tool. The 'THREE THINGS MATTER' structure is front-loaded with the most decision-relevant caveats. It could be tightened slightly, but it is structured and purposeful rather than padded.

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 tool with rich semantics, complex source nuances, and an existing output schema, the description covers everything an agent needs: what to search, how to interpret multiple issuances, how to distinguish authoritative sources from observations, what fields are intentionally absent, and which sibling tool to use for rate products. Nothing material is missing.

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%, so the baseline is 3. The description adds meaningful semantics around the query field (company name, ticker, or ISIN) and the conceptual difference between issuer catalogues and aggregated tiers, which clarifies how issuer filtering should be interpreted. It does not deeply explain line, limit, or offset, but those are already well documented in the schema.

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 a specific, answerable question: 'Does a tokenized version of a given company, ETF or bond exist, and from which issuer?' and specifies the search scope (company name, ticker, or ISIN) across named sources. It clearly distinguishes this from sibling tools by saying 'Use this BEFORE saying a stock is not available on-chain' and later routing to search_yield_products for rate comparisons. This is a clear verb+resource+scope definition.

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?

Contains explicit usage direction: 'Use this BEFORE saying a stock is not available on-chain' and 'For instruments that do carry a comparable rate, use search_yield_products instead.' It also gives practical warnings about when results should not be treated as authoritative (aggregated rows are not availability answers) and how to report eligibility. These are concrete when-to-use and when-not-to-use rules.

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