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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints, and the description adds substantial behavioral detail beyond that: multi-source cascading, graceful degradation when GLEIF/OpenFIGI is unavailable, ambiguous matches returning figi_candidates, source-labeled identifiers, and explicit unresolved fields. Edge cases like non-equity instruments and ISIN-to-LEI mapping are disclosed thoroughly.

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 densely informative, organized into trigger phrases, a primary directive, and supported types with parenthetical clarifications. Every clause adds operational value, and the most important guidance ('Use FIRST whenever you have a name but need an ID') is front-loaded. No redundant or filler content is present.

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 covers essential return behavior: identifier labels, unresolved fields, figi_candidates for ambiguous matches, and drug citation format. It addresses failure modes, input nuance, and cross-source enrichment, making it complete enough for an agent to select and invoke the tool correctly without additional context.

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%, but the description still adds crucial semantic guidance: 'Pass the ENTITY NAME ONLY' with a concrete counterexample about bond issuers and trailing security-class words. It also explains how the value is interpreted differently for company vs. drug, and gives examples like 'ozempic' and 'metformin'. This goes well beyond the schema's basic definitions.

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: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input.' It clearly differentiates from siblings like entity_profile and compare_entities by focusing on name-to-ID resolution and listing concrete trigger phrases. Supported entity types and identifier outputs are explicitly enumerated.

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 direct usage guidance: 'Use FIRST whenever you have a name but need an ID.' It also clarifies what inputs to pass for each type and provides acceptance criteria (ticker, CIK, ISIN, brand, generic). It does not explicitly state when NOT to use this tool versus specific alternatives, so it misses the full when-not/alternatives bar.

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