CKAN 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 mentions 'reviewing' and 'testing', which implies a read-only or diagnostic operation, but doesn't clarify if it's safe, requires authentication, has side effects, or details the output format. This leaves significant gaps in understanding the tool's behavior beyond its basic purpose.

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, efficient sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and every part contributes to understanding, making it highly concise and well-structured for quick comprehension.

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 auditing an API endpoint, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'specification deviations' or 'configuration overrides' entail, how results are returned, or any behavioral traits like error handling. This leaves the agent with incomplete context for effective tool use.

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, fully documenting the two optional parameters. The description adds minimal value by implying the parameters are used for 'testing datastore compatibility' and 'verifying id/alias support', but doesn't provide additional syntax or usage context beyond what the schema already states. This 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 ('Review', 'testing', 'verifying') and resources ('active CKAN endpoint', 'specification deviations', 'configuration overrides'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'ckan_api_availability' or 'analyze_dataset_structure', which might also involve endpoint analysis, so it doesn't reach the highest score.

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 doesn't mention any prerequisites, exclusions, or specific contexts for usage, leaving the agent to infer based on the purpose alone. This lack of explicit guidelines reduces its effectiveness in tool selection.

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