CloudForge MCP Server

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

No annotations are provided, so the description carries full burden. It mentions the output ('ready-to-use .tf files') but lacks details on behavioral traits such as error handling, rate limits, authentication needs, or whether the generation is idempotent. For a generation tool with zero annotation coverage, this is a significant gap.

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 and concise with two sentences that efficiently convey the tool's function and output without unnecessary details. Every sentence earns its place by specifying input type, output format, and provider scope.

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 (generating Terraform code from natural language) and lack of annotations or output schema, the description is moderately complete but could improve by addressing behavioral aspects like error cases or output structure. It covers the basic purpose and parameters but leaves gaps in operational context.

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 already documents all parameters thoroughly. The description adds minimal value beyond the schema by implying the 'description' parameter should include details like region and SKU preferences, but does not provide additional syntax or format details. Baseline 3 is appropriate when 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 ('Generate Terraform HCL') and resources ('.tf files for Azure, AWS, or GCP'), distinguishing it from siblings like 'cloudforge_export_terraform_from_diagram' by focusing on natural-language input rather than diagram-based generation.

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 context by specifying it generates from 'natural-language architecture description' and targets specific cloud providers, but does not explicitly state when to use this tool versus alternatives like 'cloudforge_export_terraform_from_diagram' or 'cloudforge_import_terraform', which are related but distinct tools.

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