Verda Cloud MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves script details or a message if none exists, which covers basic output behavior. However, it lacks critical details: whether this is a read-only operation (implied but not stated), authentication requirements, error handling (e.g., invalid instance_id), rate limits, or data freshness. For a tool with no annotation coverage, this leaves significant gaps in understanding its operational traits.

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 structured 'Args' and 'Returns' sections. Each sentence adds value: the purpose, parameter meaning, and return details. It avoids redundancy and is appropriately sized for a simple retrieval tool, though the 'Args' and 'Returns' labels could be integrated more smoothly into prose.

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 low complexity (1 parameter, no nested objects) and the presence of an output schema (which handles return value documentation), the description is reasonably complete. It covers purpose, parameter semantics, and high-level return behavior. However, it lacks context on authentication, errors, and sibling tool relationships, which are minor gaps in an otherwise straightforward tool.

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% description coverage, with only a title 'Instance Id' for the parameter. The description compensates by explaining that 'instance_id' is 'The ID of the instance', adding essential semantic context beyond the schema. It doesn't specify format (e.g., numeric vs. string) or sourcing (e.g., from 'list_instances'), but given the single parameter and low schema coverage, this is adequate for baseline understanding.

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 verb 'Get' and the resource 'startup script attached to a specific Verda Cloud instance', making the purpose evident. It distinguishes from siblings like 'list_scripts' (which lists all scripts) and 'create_startup_script' (which creates new scripts) by focusing on retrieval for a specific instance. However, it doesn't explicitly contrast with 'show_config' or other instance-related tools, keeping it from a perfect score.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., instance must exist), compare to 'list_scripts' for broader script discovery, or specify scenarios like debugging instance startup issues. Without such context, users must infer usage from the purpose alone.

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