NDI-MCP-Server

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 effectively describes the output format ('AI-scored deals with cap rates, pricing, green/red flags, and sell signals') and geographic scope ('across the Northeast'), but lacks details on permissions, rate limits, pagination, or error handling. It adds value beyond the schema but does not fully compensate for the absence of annotations.

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 efficiently structured in two sentences: the first states the purpose and output, and the second provides usage guidelines. Every sentence earns its place with no wasted words, and key information is front-loaded.

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 (9 parameters, no output schema, no annotations), the description is reasonably complete. It covers purpose, output format, and usage scenarios, but could benefit from more behavioral details (e.g., response format, limitations) to fully compensate for the lack of structured metadata. It is adequate but has minor gaps.

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 schema description coverage is 100%, so the schema already documents all 9 parameters thoroughly. The description does not add any parameter-specific information beyond what the schema provides, such as explaining interactions between parameters or default behaviors. The baseline score of 3 is appropriate when the schema does the heavy lifting.

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 ('Search active commercial real estate listings'), resource ('across the Northeast'), and output ('Returns AI-scored deals with cap rates, pricing, green/red flags, and sell signals'). It distinguishes this tool from siblings like 'find_1031_candidates' by explicitly mentioning 1031 exchanges as one use case among others.

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 ('to find deals matching an investor's criteria, scout a submarket, or identify opportunities for a 1031 exchange'), which helps differentiate it from siblings like 'get_market_summary' or 'search_comps'. However, it does not explicitly state when NOT to use it or name specific alternatives for overlapping functions.

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