mcp-cloudron

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 behaviors: it's a read-only check (implied by 'check' and no mutation terms), returns specific data (available/total/used disk space in MB), and includes threshold alerts (warning and critical). However, it doesn't cover potential errors, rate limits, or authentication needs, leaving some gaps in full transparency.

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 highly concise and well-structured, consisting of two sentences that front-load the purpose and context, followed by output details. Every sentence adds essential information without redundancy, making it efficient and easy to parse for an AI agent.

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 moderate complexity (1 optional parameter, no output schema, no annotations), the description is mostly complete. It covers purpose, usage context, output format, and parameter semantics. However, it lacks details on error handling or exact output structure, which could be beneficial for full completeness, but it's adequate for the tool's scope.

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 100% description coverage, so the baseline is 3. The description adds value by explaining the parameter's purpose ('checks if available >= requiredMB') and context ('Optional: Required disk space in MB'), which clarifies the semantics beyond the schema's basic description. This enhances understanding but doesn't fully compensate for missing output schema details, warranting a score above baseline.

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 ('check available disk space') and resources ('disk space in MB'), distinguishing it from siblings like backup or install tools by focusing on pre-operation verification. It explicitly mentions the context ('before operations that create data') and output format ('available/total/used disk space in MB'), making the purpose unambiguous and distinct.

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 guidance on when to use this tool ('before operations that create data (backup, install)'), offering a clear context for its application. It also implies alternatives by specifying it's for pre-checking, suggesting other tools (e.g., cloudron_create_backup) should be used for the actual operations, though it doesn't name specific alternatives, the context is sufficient for effective decision-making.

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