curistat-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal that the tool returns 'upcoming events with historical volatility impact estimates' and has a date range constraint (1-30 days), which adds useful context beyond basic functionality. However, it doesn't disclose important behavioral aspects like whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or pagination behavior. The description provides some behavioral context but leaves significant gaps.

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 exceptionally concise and well-structured. The first sentence immediately states the core functionality with key constraints. The second sentence adds valuable context about what's returned and why it matters to agents. Every word earns its place, with zero redundant information or fluff. The description is appropriately sized for a single-parameter tool with straightforward functionality.

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 moderate complexity (economic calendar data), no annotations, no output schema, and 0% schema description coverage, the description is minimally adequate but has clear gaps. It explains what the tool does and provides parameter semantics, but doesn't describe the return format, error conditions, or how to interpret the 'historical volatility impact estimates.' For a tool that presumably returns structured economic event data, more detail about the output would be helpful, especially without an output schema.

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?

The description adds meaningful context about the 'days' parameter that the schema doesn't provide. While the schema only shows it's an integer with default 7, the description specifies it represents 'the next N days' with a valid range of '1-30' and explains its purpose ('for the next N days'). With 0% schema description coverage and only 1 parameter, the description effectively compensates by providing the semantic meaning and constraints that the schema lacks.

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's purpose: 'Get the economic calendar for the next N days (1-30)' - this specifies both the verb ('Get') and resource ('economic calendar') with a clear scope constraint. It distinguishes itself from siblings like 'get_forecast_today' or 'get_event_impact' by focusing on a forward-looking calendar rather than specific forecasts or impact analyses. However, it doesn't explicitly contrast with all siblings, keeping it at a 4 rather than a 5.

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 provides no guidance on when to use this tool versus alternatives. While it mentions the tool returns 'upcoming events with historical volatility impact estimates,' it doesn't explain when an agent should choose this over 'get_event_impact' (which might analyze specific events) or 'get_forecast_today/week' (which might provide different forecast data). There's no mention of prerequisites, exclusions, or comparative use cases with sibling tools.

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