Flippa MCP

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

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds valuable behavioral context beyond annotations by specifying it's a 'computed tool' that fetches and calculates metrics, and details the return structure (financial metrics, verdict, risk factors). However, it doesn't mention potential limitations like rate limits or data freshness.

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 appropriately sized and front-loaded with a clear purpose statement. It uses bullet points for returns and examples for readability, but the 'Args' and 'Returns' sections slightly duplicate schema information. Every sentence adds value, though some trimming could improve efficiency.

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 complexity (computational analysis) and lack of output schema, the description provides a complete overview of what the tool does, including specific metrics and verdict categories. It compensates for the missing output schema by detailing return values. However, it doesn't cover all contextual aspects like error handling or data sources.

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 100%, with both parameters well-documented in the schema. The description adds minimal value beyond the schema by restating parameter purposes in the 'Args' section and providing examples. It doesn't explain parameter interactions or edge cases, so it meets the baseline for high schema coverage.

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 with specific verbs ('analyze', 'compute', 'assess') and resources ('Flippa listing's valuation', 'financial metrics', 'risk'). It distinguishes itself from siblings like 'flippa_get_listing' (which likely fetches raw data) and 'flippa_comparable_sales' (which focuses on market comparisons) by emphasizing computed analysis rather than data retrieval.

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 usage context through examples and return values (e.g., analyzing a specific listing ID), but it does not explicitly state when to use this tool versus alternatives like 'flippa_get_listing' (for raw data) or 'flippa_comparable_sales' (for market context). The examples provide practical guidance but lack explicit comparative instructions.

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