CKAN MCP Server

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

No annotations are provided, so the description carries full burden for behavioral disclosure. The description mentions 'analysis' and 'categorization' but doesn't explain what the tool actually does behaviorally—whether it performs read-only queries, modifies data, requires authentication, has rate limits, or what the output looks like. For a tool with 10 parameters and no annotations, this is a significant gap.

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 extremely concise at 5 words with no wasted language. It's front-loaded with the core purpose. However, this conciseness comes at the cost of completeness for a complex tool.

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 (10 parameters, no annotations, no output schema), the description is inadequate. It doesn't explain what the tool returns, how the analysis works, what 'categorization' entails, or behavioral aspects. The agent must rely entirely on the schema and guesswork for a non-trivial analysis tool.

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%, so the schema fully documents all 10 parameters. The description adds no parameter-specific information beyond what's in the schema—it doesn't explain how parameters interact (e.g., query vs packageIds), what 'categorization' means in relation to parameters like groupByFrequency, or provide usage examples. Baseline 3 is appropriate when schema does all the work.

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 'Update frequency analysis with categorization' states the general purpose (analyzing update frequency with categorization) but is vague about the specific action and resource. It mentions 'analysis' but doesn't specify what exactly is analyzed (datasets) or how the categorization works. It doesn't clearly distinguish from siblings like 'analyze_dataset_structure' or 'get_dataset_insights'.

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 compare it to sibling tools like 'analyze_dataset_structure' or 'get_dataset_insights'. The agent must infer usage from the tool name and parameters alone.

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