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

Although annotations already declare readOnly/idempotent/non-destructive, the description adds substantial behavioral detail: internal cascading across EDGAR/GLEIF/OpenFIGI, graceful degradation when enrichment sources are unavailable, returning figi_candidates when ambiguous, and reporting unresolved identifiers explicitly rather than silently omitting them. 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 core purpose is front-loaded and every sentence is on-topic, but the description is a single dense run-on block with many nested parenthetical clauses and self-referential annotations (e.g., the long aside about bond issuer matching). Information could be structured into bullets or shorter sentences, making it harder for an agent to parse quickly than it should be.

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 carries the full burden of explaining return behavior, and it succeeds: it details both company and drug outputs, mentions figi_candidates and unresolved lists, explains cross-source enrichment and graceful degradation, and covers edge cases like non-US issuers and non-ticker debt instruments. For a tool with this internal complexity, nothing critical is missing.

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 provides enums and examples, but the description adds essential semantics: accepted input formats for company (ticker, CIK, ISIN, name), ISIN-to-legal-entity mapping, the requirement to pass an entity name only rather than a full noun phrase (e.g., dropping 'revenue bonds'), and how drug brand/generic names map to RxNorm output. This guidance is non-obvious and goes well beyond what the schema alone communicates.

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 utterances and then states a crisp main verb and resource: 'resolve a user-spoken NAME to the canonical/official identifiers.' It explicitly enumerates supported types (company, drug) and what identifiers each returns (CIK, ticker, LEI, FIGI; RxCUI, ingredient, brand), which clearly distinguishes this name-resolution lookup from profiling/comparison siblings.

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?

'Use FIRST whenever you have a name but need an ID' is explicit, actionable guidance, and the quoted user queries make the trigger conditions unmistakable. The description also explains that the call replaces 2-3 manual lookups. It does not, however, explicitly name sibling tools to avoid (e.g., entity_profile vs resolve_entity), leaving some boundary inference to the agent.

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