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

Beyond the readOnly/idempotent annotations, the description discloses substantial behavior: the call cascades through multiple lookup endpoints, unresolved identifiers are returned under an `unresolved` field rather than omitted, ambiguous matches assert nothing and return `figi_candidates`, and LEI/FIGI enrichment degrades gracefully when upstream services are unavailable. This gives the agent a reliable mental model of execution behavior.

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 almost every clause adds necessary nuance for a complex multi-source resolver. It is front-loaded with examples and the 'Use FIRST' directive, then organized around supported types and edge cases. The heavy parenthetical in the company section is dense but earns its place; a slightly tighter structure would be 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 tool with no output schema and two heterogeneous entity types, the description is remarkably complete. It covers input canonicalization, source attribution, unresolved-identifier behavior, ambiguous-match handling, cross-entity ISIN mapping, non-US issuer coverage, and failure degradation. An agent has enough information to decide when to call it and what to expect back.

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 adds significant meaning beyond the schema's terse type/value fields. It enumerates accepted input formats (ticker, CIK, ISIN, name; brand or generic drug name), provides explicit examples like 'CH0038863350' and 'ozempic'/'metformin', and explains how ISINs resolve to legal entities via GLEIF. This strongly compensates for any thinness in the schema itself.

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 concrete user-phrase examples ('What's the ticker for…' / 'find the CIK for…') and states a specific verb+resource: resolve a user-spoken NAME to canonical/official identifiers other tools require as input. It clearly separates itself from siblings like entity_profile by framing this as the first step whenever a name needs to become an ID, rather than profiling or comparing entities.

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?

It explicitly instructs 'Use FIRST whenever you have a name but need an ID,' which tells the agent when to select this tool over alternatives. It also gives rich selection guidance per type, including the critical negative example that users should pass the issuer name only, never the full noun phrase like 'revenue bonds,' because the FIGI lookup matches instrument names.

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