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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, but the description goes far beyond them. It discloses that it cascades through multiple endpoints, asserts nothing on ambiguity (returns figi_candidates), labels identifiers by source, explicitly lists unresolved identifiers, handles non-US issuers, and degrades gracefully if GLEIF/OpenFIGI is down. This rich behavioral detail is exactly what agents need to set expectations for idempotent read operations. No contradiction with 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 long but densely packed with actionable information. It front-loads purpose with examples, then organizes details by type and behavior. Every paragraph adds new value (graceful degradation, ambiguity handling, input format). It could be trimmed slightly (e.g., the exhaustive list of identifier sources is useful but verbose), but the structure is logical and content is not redundant. High information density justifies a 4.

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 2 parameters and no output schema, this description is exceptionally complete. It explains what identifiers are returned for each type, how ambiguity is resolved (figi_candidates), how unresolved identifiers are handled (unresolved field), input format edge cases, and graceful degradation. It covers all the 'unknown unknowns' an agent might have when calling this tool, leaving nothing 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?

Schema description coverage is 100%, so the baseline is 3, but the description adds substantial semantic depth. For 'type' it explains each enum value's full retrieval pipeline (SEC EDGAR, GLEIF, OpenFIGI, RxNorm). For 'value' it gives precise formatting rules, examples ('AAPL', '0000320193', 'NEW YORK ST DORM AUTH'), and explicitly warns against including trailing security-class words. This goes well beyond the schema's simple parameter 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 opens with concrete example queries, then states the core purpose: resolving user-spoken names to canonical identifiers. It names the supported types (company, drug) and explains the cross-source identity spine. This clearly distinguishes it from sibling tools like search, entity_profile, and compare_entities — it's specifically about getting an ID, not general search or profiling.

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?

Explicitly says 'Use FIRST whenever you have a name but need an ID.' It also details when to use company vs drug, how to handle bonds (pass issuer as printed, not the full noun phrase), and gracefully degradation. It even notes it replaces 2-3 manual lookups, giving clear when-to-use context beyond just the tool's own description. No alternatives are left ambiguous.

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