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

Annotations declare readOnlyHint=true, and the description adds valuable behavioral context: data is served from their own store with no vendor call on the request path, reported quarters are 'confirmed' vs upcoming 'estimated', and actuals for the next report are null until it reports. This goes beyond the annotation by explaining data provenance and null behavior. No contradiction.

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?

Three sentences, dense with information, no fluff. The key output (per-quarter earnings, newest first) is front-loaded, followed by status semantics, reconciliation, and data source. Every sentence earns its place.

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?

The output schema exists, so return values are covered. The description explains the data model (confirmed vs estimated, null actuals), data source, and reconciliation. It doesn't explicitly state pagination or limit behavior, but for a read-only list tool with an output schema, this is nearly complete. Minor gap: no explicit statement about what 'entity' refers to (ticker, ID, etc.), but resolve_entity sibling likely handles that.

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 0%, so the description carries the burden. It explains the entity concept implicitly (earnings for an entity) and the limit parameter is not described. The description adds meaning about the data shape but doesn't explain what 'entity' means or how limit behaves. Baseline 3 is appropriate because the description partially compensates but leaves parameter details to the schema.

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 clearly states the tool returns per-quarter earnings data, newest first, with specific fields (reported EPS/revenue vs consensus, next report date/estimate). It distinguishes itself from get_fundamentals by noting the reported actuals reconcile with SEC filings, and the estimate is licensed analyst consensus. This is a specific verb+resource with clear scope.

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 implies when to use this tool: when you need earnings vs consensus and upcoming report dates. It mentions reconciliation with get_fundamentals, which hints at an alternative for SEC-filing-based data. However, it doesn't explicitly state when NOT to use it or name a direct sibling alternative like get_calendar for upcoming dates. Clear context but no explicit exclusions.

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