Upcoming and recent earnings dates for a specific stock — scheduled report dates with EPS/revenue estimates where available. Read-only, no side effects.
Use this to find when a company reports. For past actual-vs-estimate
results use get_earnings_history; for a cross-market schedule use
get_earnings_calendar.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | Stock ticker symbol, e.g. 'NVDA'. |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -{
- "properties": {
- "result": {
- "title": "Result",
- "type": "string"
- }
- },
- "required": [
- "result"
- ],
- "title": "get_ticker_earningsOutput",
- "type": "object"
-}New value: +nullInput schema / properties / ticker / descriptionAdded value: +"Stock ticker symbol, e.g. 'NVDA'."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false; the description reinforces 'Read-only, no side effects' and adds useful semantic detail: 'scheduled report dates with EPS/revenue estimates where available' clarifies content and conditional availability.
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?
Two brief sentences plus a usage line. Front-loaded with purpose, no fluff, and every sentence contributes.
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 single-parameter tool with strong annotations and no output schema, the description covers purpose, usage, alternatives, and data semantics. It is complete enough for an agent to select and invoke 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?
Schema coverage is 100% with a clear ticker description. The description adds no additional parameter semantics beyond the schema, so baseline 3 applies.
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?
Description clearly states it returns 'Upcoming and recent earnings dates for a specific stock' with estimates where available. Distinguishes from siblings by naming get_earnings_history and get_earnings_calendar.
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 this to find when a company reports' and provides alternatives for past results (get_earnings_history) and cross-market schedules (get_earnings_calendar), giving clear when-to-use and when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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