Keeta Network 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 effectively describes key traits: the tool generates a random seed, which is foundational for deriving accounts and controlling funds, and emphasizes security implications. It also specifies the return format. While it covers critical aspects, it lacks details like rate limits or error handling, but this is sufficient for a high score given the context.

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 in the first sentence, followed by essential context and a security warning, and ends with the return value. Every sentence adds value without waste, making it highly efficient 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 complexity (simple generation with no parameters), no annotations, no output schema, and rich sibling context, the description is complete. It explains what the tool does, its role in the ecosystem, security considerations, and the return format, providing all necessary information for an AI agent to use it correctly.

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 tool has 0 parameters, and the schema description coverage is 100%, so the baseline is 4. The description does not need to add parameter information, and it appropriately focuses on the tool's purpose and output without redundancy.

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 a specific verb ('Generate') and resource ('new random cryptographic seed for the Keeta Network'). It distinguishes this from sibling tools like keeta_derive_account by explaining that the seed is the starting point for deriving accounts, making its role explicit and unique.

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 on when to use this tool: as the 'starting point for all Keeta operations' and to derive accounts via keeta_derive_account. It includes a security warning about storing the seed securely. However, it does not explicitly state when not to use it or name alternatives, which prevents a perfect score.

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