Amazing Marvin 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 describes what the tool does (retrieves a summary) and parameter interactions, but doesn't address critical behavioral aspects like whether this is a read-only operation, what format the summary returns, if there are rate limits, authentication requirements, or potential side effects. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 well-structured with clear sections (purpose, args with explanations, examples) and uses bullet points for readability. While efficient, the 'Examples' section could be slightly more concise by combining similar cases, but overall it's front-loaded with the core purpose and avoids unnecessary verbiage.

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, no output schema, no annotations), the description is partially complete. It excels at parameter documentation but lacks information about the return format, error conditions, or how the 'productivity summary' is structured. Without an output schema, the agent won't know what data to expect from this tool, which is a significant gap for a summary retrieval function.

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 substantial value beyond the input schema, which has 0% description coverage. It explains the purpose of each parameter ('days: Number of days to analyze from today backwards'), provides defaults, clarifies parameter interactions ('start_date overrides days parameter'), gives format specifications ('YYYY-MM-DD format'), and includes concrete examples. This fully compensates for the schema's lack of 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 clearly states the tool's purpose as 'Get a comprehensive productivity summary for a specified time range', which includes a specific verb ('Get') and resource ('productivity summary') with scope ('for a specified time range'). However, it doesn't explicitly differentiate from sibling tools like 'get_productivity_summary' (without time range) or 'time_tracking_summary', which could cause confusion.

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 implied usage through parameter examples and defaults (e.g., 'default: 7 for weekly summary'), showing when to use days vs. start_date/end_date. However, it lacks explicit guidance on when to choose this tool over similar siblings like 'get_productivity_summary' or 'time_tracking_summary', leaving the agent to infer based on tool names alone.

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