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

The description goes far beyond the annotations: it explains that unresolved identifiers appear under `unresolved` rather than being omitted, that ambiguous instrument matches return `figi_candidates`, and that LEI/FIGI enrichment degrades gracefully when external sources are unavailable. It also reveals the internal cascading lookup behavior. These are exactly the non-obvious behaviors an agent needs to know.

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 dense, but it is front-loaded with the core purpose and usage rule, and it is organized into clear SUPPORTED TYPES blocks. Some parenthetical stretches are heavy, and a few details could be trimmed, but most sentences earn their place given the tool's complexity.

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 must explain what the caller can expect back, and it does: source-labelled identifiers, explicit `unresolved` entries, `figi_candidates` for ambiguous matches, and graceful degradation. Combined with the parameter semantics and annotations, the description gives an agent enough context to invoke this tool correctly in nearly all supported cases.

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?

Although schema coverage is 100%, the description adds substantial meaning: it clarifies accepted formats for `value` (ticker, CIK, ISIN, or name), warns against including trailing security-class words like 'revenue bonds', and explains that an ISIN resolves to the issuing legal entity. This is practical semantic detail that the schema alone does not convey.

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 uses a specific verb and resource: it resolves user-spoken names to canonical/official identifiers required by other tools. It includes concrete example queries ('What's the ticker for...', 'find the CIK for...'), which makes the purpose unmistakable and differentiates it from less lookup-oriented siblings like entity_profile or compare_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?

The description gives explicit guidance: 'Use FIRST whenever you have a name but need an ID.' It also enumerates supported entity types and the kinds of inputs accepted for each. It does not explicitly name sibling tools as alternatives or say when not to use it, but the trigger condition is clear and actionable.

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