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

The description goes well beyond the readOnly/openWorld/idempotent annotations by disclosing key behaviors: it cascades through multiple lookup endpoints, returns figi_candidates when a name matches multiple instruments, labels each identifier by source, explicitly lists unresolved identifiers, and degrades gracefully when LEI/FIGI enrichment is unavailable. This gives the agent a rich model of how the tool behaves.

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 and somewhat run-on, but it is front-loaded with user-phrase examples and a crisp purpose statement. Nearly every clause adds distinct information—supported types, ambiguity handling, fallback behavior, and source labeling—so it earns its length, though it would benefit from clearer segmentation.

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 input variants, ambiguity resolution, degraded enrichment, unresolved identifiers, and source attribution. An agent has enough information to decide when to invoke it and to interpret the likely outcome, even without a formal 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?

The schema already provides strong descriptions for both parameters (100% coverage), so the baseline is 3. The description adds extra semantic value by introducing ISIN as an accepted company input, explaining how an ISIN resolves to the issuing legal entity, and clarifying that non-equity instruments resolve here. This goes beyond the schema's parameter text.

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 names a specific verb ('resolve') and a specific resource (user-spoken NAME to canonical/official identifiers), reinforced by concrete query examples at the start. It also differentiates itself from sibling tools by instructing 'Use FIRST whenever you have a name but need an ID', making its role as the identity-lookup tool unmistakable.

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 gives explicit when-to-use guidance ('Use FIRST whenever you have a name but need an ID') and detailed context for supported entity types and input formats. It also provides a strong negative instruction for bonds ('never the question's full noun phrase'), but it does not explicitly name alternative tools or state when not to use resolve_entity.

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