pyfastmail-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 clearly indicates this is a read operation ('List'), which is helpful. However, it doesn't mention potential behavioral aspects like pagination, rate limits, authentication requirements, error conditions, or what happens if dates are invalid. For a read tool with zero annotation coverage, this leaves gaps in understanding the tool's full behavior.

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 perfectly structured and concise. The first sentence states the core purpose, followed by a clear 'Args:' section that documents each parameter efficiently. Every sentence earns its place with no wasted words, and information is front-loaded with the most important details first.

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 (3 parameters, read operation), no annotations, but with an output schema present, the description is largely complete. It covers purpose, usage context, and parameter semantics well. The output schema will handle return values, so the description doesn't need to explain those. The main gap is lack of behavioral details like pagination or error handling, which prevents a perfect score.

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 must fully compensate. It successfully does this by explaining all three parameters: calendar_href (source, purpose, and where to get it), start_date (format, default), and end_date (format, default calculation). The description adds crucial meaning beyond the bare schema, including format specifications and default behaviors.

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 specific action ('List events'), target resource ('in a CalDAV calendar'), and scope ('within a date range'). It distinguishes itself from siblings like calendar_get_event (single event) and calendar_list_calendars (lists calendars, not events). The verb+resource+scope combination is precise and unambiguous.

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 clear context for when to use this tool: when listing events from a specific calendar within a date range. It references calendar_list_calendars as the source for calendar_href, establishing a prerequisite relationship. However, it doesn't explicitly state when NOT to use it (e.g., vs. calendar_get_event for a single event) or name alternatives, keeping it from a perfect score.

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