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

Annotations cover readOnly/idempotent/non-destructive, but the description goes far beyond: it discloses the cascading internal lookups, graceful degradation when upstream services are unavailable, explicit output structure (unresolved identifiers, figi_candidates on ambiguity), and source labelling. There is no contradiction with annotations — readOnlyHint is consistent with a pure resolution tool.

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 every sentence adds information — it is front-loaded with the primary instruction and example queries, then systematically covers supported types, edge cases, and fallbacks. Structure mirrors the hierarchy of entity types, making it scannable despite its length.

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?

Given the tool's complexity (two entity types, multiple identifier sources, ambiguous matches, service degradation, no output schema), the description is exceptionally complete. It explains return value semantics (source-labelled identifiers, explicit `unresolved` list, `figi_candidates`), covers non-equity instruments, and addresses international issuers via ISIN-to-LEI mapping. Nothing material is missing for an agent to call it correctly.

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 value: for `type` it elaborates on the two enum values and their associated identifier systems; for `value` it explains the exact string formats for companies vs drugs, and specifically how to format bond issuer names (exclude trailing security-class words). This goes well beyond the schema's one-liner 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 states a specific action — resolve user-spoken names to canonical/official identifiers — and enumerates the exact identifier types (CIK, ticker, LEI, FIGI, RxCUI) and sources (SEC EDGAR, GLEIF, OpenFIGI, RxNorm). It also explicitly contrasts itself with sibling tools by stating 'Use FIRST whenever you have a name but need an ID', which differentiates it from tools that operate on existing IDs (e.g., entity_profile, 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 when-to-use guidance ('Use FIRST whenever you have a name but need an ID'), includes example user phrasings, and provides detailed input-format instructions (e.g., pass the entity name only, not the noun phrase for bonds). It explains graceful degradation and fallback behavior, and notes that it replaces multiple manual lookups — all contextual usage guidance.

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