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

The description goes well beyond the annotations by disclosing behavioral nuances: cross-source enrichment from SEC EDGAR, GLEIF, OpenFIGI, and RxNorm; graceful degradation when GLEIF/OpenFIGI are unavailable; explicit `unresolved` reporting; the `figi_candidates` behavior when a name matches multiple instruments; and the fact that ISINs resolve to the issuing legal entity. These details substantially inform an agent about side effects, edge cases, and output semantics.

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 information-dense and front-loaded with examples and a usage directive, but it is sprawling and repetitive in places, mixing behavioral details, supported types, caveats, and degradation behavior into a single wall of text. It could be split into clearer sections or trimmed without losing meaning, so it only earns a mid-range score.

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's complexity and the absence of an output schema, the description is remarkably complete. It covers supported input formats, output identifiers, source provenance, ambiguity handling, unresolved fields, and failure/degradation behavior. An agent has enough context to invoke the tool correctly and anticipate what results may look like.

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 value beyond the schema by giving concrete input examples, clarifying that the value should be the entity name only, and warning against including trailing security-class words for bonds. This caveat is crucial and not fully captured by the schema descriptions.

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 a specific verb and resource: it resolves a user-spoken name to canonical/official identifiers, with concrete examples like ticker, CIK, LEI, and RxCUI. It also differentiates itself from sibling tools by emphasizing that other tools require these identifiers as inputs, and it enumerates supported entity types. This gives an agent a precise understanding of what the tool does.

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 contains an explicit when-to-use directive: 'Use FIRST whenever you have a name but need an ID.' It also explains that a single call replaces 2-3 manual lookups, which helps an agent decide to use it. It does not, however, explicitly name alternative tools to use when conditions differ, such as entity_profile or search_within, so it falls short of full when-not-to-use guidance.

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