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

Beyond the annotations (read-only, idempotent, open-world), the description adds substantial behavioral detail: multi-source resolution across EDGAR/GLEIF/OpenFIGI/RxNorm, graceful degradation when enrichment sources are unavailable, explicit `unresolved` output for missing identifiers, and non-assertion with `figi_candidates` on ambiguous name matches. It also warns that trailing security-class words will fail FIGI lookup. This far exceeds what annotations alone convey.

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 appropriately front-loaded with trigger phrases and the primary instruction 'Use FIRST.' Every clause adds substantive detail, including edge cases and degradation behavior. It is somewhat dense and could be better organized into clearer sections, which keeps it from a perfect conciseness score.

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 two required parameters and no output schema, the description is remarkably complete. It covers supported entity types, source provenance, ambiguity handling, unresolved identifiers, enrichment failures, and the internal multi-endpoint cascade. An agent has enough context to select and invoke the tool correctly and to interpret expected outcomes.

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%, yet the description still adds meaningful parameter semantics beyond the schema. It explains accepted input forms (ticker, CIK, ISIN, name; brand or generic drug), gives concrete examples, and includes the crucial caveat to pass only the entity name for bonds, since 'trailing security-class words match nothing.' The `type` enum is also elaborated with per-type resolution behavior.

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-plus-resource framing: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input.' It also supplies concrete trigger phrases ('What's the ticker for…', 'find the CIK for…') and distinguishes itself from sibling tools by explaining that it maps names to IDs, not profiles or comparisons.

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 when-to-use guidance: 'Use FIRST whenever you have a name but need an ID.' It also clarifies scope through supported types and examples, and notes that one call replaces 2-3 manual lookups. However, it does not name alternatives or state when not to use it, so it lacks explicit exclusions.

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