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

The description adds substantial behavioral context beyond the annotations: it explains that multiple lookup endpoints cascade internally, that LEI/FIGI enrichment degrades gracefully when upstream sources are unavailable, that unresolved identifiers are stated explicitly, that multi-match cases return `figi_candidates` rather than asserting incorrectly, and that ISIN inputs resolve through GLEIF mapping. This is rich, non-obvious behavior an agent needs to predict outcomes.

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 quite long, but it is front-loaded with realistic user phrases and a clear 'Use FIRST' directive, and nearly every sentence carries operational information. Some nested parentheticals and repetitive caveats make it denser than necessary, but the structure remains scannable by supported type.

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 polymorphic entity types, the description is remarkably complete. It covers accepted inputs, source databases (SEC EDGAR, GLEIF, OpenFIGI, RxNorm), ambiguity behavior, failure/degradation behavior, unresolved identifiers, and the internal multi-call benefit. An agent has enough context to invoke it correctly and interpret unexpected results.

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 input schema already documents both parameters well, so the baseline is 3. The description adds extra semantic guidance: company input may be a ticker, CIK, ISIN, or name; ISINs resolve to the legal entity issuers; and non-equity instruments without tickers are explicitly supported. It also gives the important warning to pass the issuer name exactly and not the full noun phrase, which prevents a common invocation mistake.

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: it resolves a user-spoken name to canonical/official identifiers needed as input by other tools. The examples cover multiple concrete question phrasings, and the routing instruction 'Use FIRST whenever you have a name but need an ID' clearly separates it from the broader entity/analysis tools in the sibling list.

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 explicitly says when to use the tool: 'Use FIRST whenever you have a name but need an ID.' It also enumerates supported entity types and input formats. It does not explicitly name alternative tools or state when not to use it, but the condition and supported-type scoping are clear enough for an agent to route correctly.

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