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

Annotations already declare read-only, open-world, idempotent, and non-destructive behavior, so the description adds value by disclosing graceful degradation of LEI/FIGI enrichment, explicit `unresolved` fields, non-assertion on ambiguous FIGI matches, and the ISIN-to-LEI fallback path. There is no contradiction with the annotations.

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, front-loaded with examples and the 'Use FIRST' rule, and most parentheticals carry real behavioral detail. However, it is long and contains some asides that could be tightened without losing essential guidance, so it falls just short of model conciseness.

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?

With no output schema, the description takes on the burden of explaining return values, and it does so thoroughly: it names the identifiers returned for each type, covers ambiguous matches via `figi_candidates`, explicitly mentions unresolved identifiers, and notes graceful degradation. An agent has enough context to invoke the tool and interpret its result.

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?

Input schema covers 100% of parameters, providing a baseline of 3, but the description adds substantial meaning: accepted input forms include ticker, CIK, ISIN, or company name, and it warns that bond lookups require the exact issuer name rather than the full noun phrase. This goes well beyond the schema's enum and field 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 states the core operation explicitly: 'resolve a user-spoken NAME to canonical/official identifiers other tools require as input.' It enumerates supported entity types and concrete outputs (CIK, ticker, LEI, FIGI, RxCUI), making the tool's scope unmistakable and differentiating it from sibling tools that do profiling, comparison, or search.

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 provides an explicit decision rule: 'Use FIRST whenever you have a name but need an ID.' It also gives representative user phrasings and explains that using resolve_entity replaces 2-3 manual lookups, which clarifies the intended role versus multi-step alternatives.

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