AGR MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool returns 'schema information' but doesn't clarify what that entails (e.g., structure, format, or limitations). It also omits details like error handling, performance characteristics, or any constraints on the natural language processing, leaving significant gaps in understanding how the tool behaves.

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 concise and front-loaded, with two sentences that directly state the tool's purpose and outcome. There's no unnecessary information, and it efficiently communicates the core functionality without waste, though it could be slightly more structured for clarity.

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 complexity of processing natural language queries and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'schema information' is returned, how it should be used with 'mine_query_builder,' or any behavioral traits. This leaves the agent with insufficient context to effectively invoke the tool or interpret results.

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 ('query' and 'limit') well-documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, such as examples or constraints on the 'query' input. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but the description doesn't compensate or enhance parameter understanding.

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: 'Process a natural language query and return schema information to construct a structured AllianceMine query.' It specifies the verb ('process'), resource ('natural language query'), and outcome ('return schema information'). However, it doesn't explicitly differentiate from sibling tools like 'mine_query_builder' or 'mine_search' beyond mentioning the latter as a follow-up step.

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 by stating it helps 'convert the user's natural language into a mine_query_builder call,' suggesting this is a preparatory step. However, it lacks explicit guidance on when to use this tool versus alternatives like 'mine_query' or 'mine_search,' and doesn't specify prerequisites or exclusions for its use.

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