Featurebase 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 states the tool converts a slug to an ID and gets details, implying a read operation, but doesn't cover critical aspects like error handling (e.g., invalid slugs), authentication needs, rate limits, or the format of returned details. This is a significant gap for a tool with no annotation coverage.

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 and front-loaded, consisting of a single, clear sentence that directly states the tool's function. Every word earns its place, with no redundant or vague language, making it efficient for quick understanding by an AI agent.

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 (a lookup tool with no output schema) and lack of annotations, the description is incomplete. It doesn't explain what 'post details' include, how errors are handled, or any behavioral traits, leaving the agent with insufficient information for reliable invocation. This is inadequate for a tool that retrieves data without structured output documentation.

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 the input schema fully documenting the 'slug' parameter, including an example. The description adds minimal value beyond this, as it only mentions 'post slug' without providing additional context like format constraints or usage tips. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.

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: converting a post slug to a post ID and retrieving post details. It specifies the verb ('convert' and 'get') and resource ('post slug' to 'post ID and post details'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_post_upvoters' or 'list_posts', which might also retrieve post information, 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 prerequisites (e.g., needing a valid slug), exclusions, or compare it to siblings like 'list_posts' or 'get_post_upvoters'. This leaves the agent without context for tool selection, relying solely on the description's implied use case.

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