ABAP-ADT-API 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 but offers minimal insight. It states the tool 'evaluates', implying a read-only or analysis operation, but does not clarify if it modifies data, requires specific permissions, has side effects, or details output behavior (e.g., returns evaluation results or errors). For a tool with zero annotation coverage, this is inadequate, though not contradictory.

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 a single sentence, 'Evaluates an extract method refactoring.', which is concise but under-specified rather than efficiently informative. It lacks front-loaded critical details (e.g., purpose differentiation or usage context), making it feel sparse rather than optimally structured. While not verbose, it fails to earn its place by adding sufficient value.

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 (involving refactoring evaluation with 2 parameters), no annotations, and no output schema, the description is incomplete. It does not explain what the evaluation entails, what results to expect, or how it fits into a workflow with sibling tools. This leaves significant gaps for an AI agent to understand and use the tool effectively in context.

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 input schema has 100% description coverage, with parameters 'uri' and 'range' clearly documented in the schema. The description adds no additional meaning about these parameters, such as format examples or constraints beyond the schema. According to the rules, when schema coverage is high (>80%), the baseline score is 3, as the schema adequately handles parameter documentation without need for description enhancement.

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 'Evaluates an extract method refactoring' is a tautology that essentially restates the tool name 'extractMethodEvaluate' with minimal added value. It specifies the verb 'evaluates' and the resource 'extract method refactoring', but lacks specificity about what evaluation entails (e.g., feasibility, impact, or preview) and does not differentiate from sibling tools like 'extractMethodExecute' or 'extractMethodPreview', leaving the agent unclear about distinct purposes.

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 no guidance on when to use this tool versus alternatives. It does not mention prerequisites, context (e.g., before executing a refactoring), or refer to sibling tools like 'extractMethodExecute' or 'extractMethodPreview' for comparison. This absence leaves the agent without explicit or implied direction on appropriate usage scenarios.

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