Ludus FastMCP

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns a 'curated list' with 'descriptions and example usage' and a 'Dictionary of common roles organized by category,' which adds useful behavioral context. However, it doesn't mention potential limitations such as whether the list is static or updated, any rate limits, or error conditions, leaving gaps for a mutation-free tool.

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 well-structured and appropriately sized. It starts with the core purpose, adds details about the return value, and includes a practical example. Each sentence adds value, and there's no redundant information. However, it could be slightly more front-loaded by integrating the example more seamlessly, but it remains efficient.

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 has 0 parameters, no annotations, and no output schema, the description provides sufficient context for its purpose and behavior. It explains what the tool does, what it returns, and includes an example usage. For a simple read-only tool, this is complete enough, though it could benefit from mentioning any dependencies or constraints to reach a score of 5.

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 input schema has 0 parameters with 100% coverage, so no parameter information is needed. The description appropriately focuses on output semantics, explaining the return structure. It adds value by detailing the return format beyond what the schema provides, earning a score above the baseline of 3 for zero-parameter tools.

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: 'Get a list of commonly used Ansible Galaxy roles for Ludus scenarios.' It specifies the verb ('Get'), resource ('list of commonly used Ansible Galaxy roles'), and context ('for Ludus scenarios'). However, it doesn't explicitly differentiate from sibling tools like 'get_required_roles_for_scenario' or 'list_installed_roles', which might serve related but distinct purposes.

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 implies usage by mentioning 'commonly used' roles for 'security lab scenarios,' suggesting it's for discovery or reference. The example shows it being used before 'install_galaxy_role,' indicating a workflow. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_required_roles_for_scenario' or 'list_role_repositories,' and doesn't specify prerequisites or exclusions.

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