cloudwright-mcp

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 behavioral traits: 'Pure computation — no LLM, no network. Does not touch cloud.' This clarifies that it's a local, non-destructive analysis tool without external dependencies. However, it doesn't mention performance characteristics like execution time or resource usage.

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 efficiently structured and front-loaded: the first sentence states the core purpose, followed by return details, usage guidelines, specific checks, and behavioral notes. Every sentence adds value without redundancy, making it highly concise and well-organized.

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 (security scanning with multiple checks) and lack of annotations/output schema, the description does a good job covering purpose, usage, behavior, and scope. It could be more complete by detailing the report structure or example outputs, but it provides sufficient context for an agent to understand when and how to use it effectively.

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 schema description coverage is 100%, so the schema already documents the single parameter 'spec_json' with details about what it contains. The description adds minimal value beyond the schema by listing specific checks performed (e.g., 'unencrypted data stores'), but doesn't provide additional syntax, format, or constraints for the parameter. Baseline 3 is appropriate when the schema does the heavy lifting.

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 specific verbs ('scan', 'returns') and resources ('architecture', 'security anti-patterns and misconfigurations'). It distinguishes from sibling tools by explicitly contrasting with 'validate_compliance' for regulatory frameworks, making the scope and differentiation explicit.

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 explicit usage guidance by stating when to use this tool ('framework-agnostic') and when to use an alternative ('use `validate_compliance` for specific regulatory frameworks'). This clearly defines the context and exclusions for tool selection.

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