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

The description goes far beyond the readOnly/openWorld/idempotent annotations by explaining graceful degradation when GLEIF/OpenFIGI are unavailable, multi-endpoint cascading, ambiguous-name behavior returning figi_candidates without asserting a match, explicit unresolved identifiers, and the ISIN-to-LEI mapping path. This is rich behavioral disclosure that helps an agent anticipate edge cases.

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 and densely packed, but front-loads the core purpose and usage directive before diving into per-type details. Nearly every clause adds unique information, though the heavy use of nested parentheticals makes it less scannable than ideal.

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 two-parameter tool with no output schema, the description explains what each type returns, how identifiers are sourced, how failures and ambiguities are represented, and what inputs are accepted. It is sufficiently complete for an agent to invoke it correctly without additional external knowledge.

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 has 100% coverage, so baseline is 3, but the description adds substantial value: it explains that 'value' should be the entity name only, warns against including trailing security-class words for bonds, gives per-type examples, and clarifies how the same parameter behaves differently for company versus drug. This is meaningful semantic guidance beyond 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 states a specific action—resolving a user-spoken name to canonical identifiers—and explicitly names the identifier types (CIK, ticker, LEI, FIGI, RxCUI) and supported entity types (company, drug). It also distinguishes itself from other tools by noting it supplies IDs that 'other tools require as input' and instructs to 'Use FIRST' when a name but not an ID is available.

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 clear context on when to use the tool ('Use FIRST whenever you have a name but need an ID') and describes the scope of supported lookups. It does not name explicit alternative tools or when-not-to-use conditions, but the guidance is concrete enough for an agent to select it appropriately.

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