CKAN 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 'intelligent discovery' and 'relevance scoring', which hints at advanced search capabilities, but fails to describe critical behaviors like whether this is a read-only operation, what the output format looks like, pagination handling, rate limits, authentication requirements, or how relevance scoring is calculated. The description is too vague to adequately inform an agent.

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 phrase that front-loads the core concept ('Intelligent dataset discovery with relevance scoring'). There's no wasted space or redundant information. However, it could be more structured by explicitly separating purpose from behavioral details, but given its brevity, it scores well for conciseness.

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 (10 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, output format, error handling, and differentiation from siblings. While the schema covers parameters well, the description fails to provide the contextual guidance needed for an agent to use this tool effectively, especially compared to similar tools in the server.

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 already documents all 10 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema (e.g., it doesn't explain how 'query' interacts with 'intelligent discovery' or what 'relevance scoring' means in practice). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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 'Intelligent dataset discovery with relevance scoring' states the general purpose (discovering datasets with scoring) but is vague about the specific action and resource. It mentions 'relevance scoring' which differentiates it from basic search tools, but doesn't clearly distinguish it from sibling tools like 'search_datasets' or 'list_datasets' in terms of scope or methodology.

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. With multiple sibling tools like 'search_datasets', 'list_datasets', and 'get_package', there's no indication of when this 'intelligent discovery' approach is preferred, what prerequisites exist, or any exclusions. Usage is implied by the name but not explicitly stated.

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