atxp-mcp

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

Annotations cover read-only, non-destructive, non-idempotent, and open-world hints, but the description adds valuable context beyond this: it specifies that results are 'clean, structured' with details like titles, URLs, and snippets, and mentions it's 'AI-powered' and 'great for' specific use cases. This enhances understanding without contradicting annotations.

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 front-loaded with the core purpose and key features, followed by use cases, all in two efficient sentences. Every sentence adds value without redundancy, making it appropriately sized and well-structured.

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 moderate complexity, rich annotations, and 100% schema coverage, the description is largely complete. However, without an output schema, it could benefit from more detail on return values (e.g., result format or pagination), though it does mention 'structured results with titles, URLs, and snippets' which helps.

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 the 'query' and 'limit' parameters. The description does not add any specific meaning or details beyond what the schema provides (e.g., it doesn't explain query formatting or result structure further), meeting the baseline for high 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 specific action ('Search the web') and resource ('ATXP's AI-powered search engine'), distinguishing it from sibling tools like email or content generation. It provides concrete examples of use cases (researching topics, finding current information, etc.), making the purpose explicit and differentiated.

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 clear context for when to use this tool (e.g., researching topics, finding current information, checking facts, discovering resources), but it does not explicitly state when not to use it or name alternatives among sibling tools. This gives good guidance but lacks explicit exclusions or comparisons.

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