Ops MCP Server

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 the tool's behavior: it's a read-only metadata operation (implied by 'without downloading'), it's performance-optimized ('fast'), and it returns specific metadata fields. However, it doesn't mention potential errors (e.g., if the object doesn't exist), authentication requirements, or rate limits, which would be helpful for a production S3 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 front-loaded: the first sentence states the core purpose, followed by usage guidelines, parameter details, and return values. Every sentence adds value with no redundancy. The formatting with clear sections (Args, Returns) enhances readability without being verbose.

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 (2 parameters, no annotations, but with output schema), the description is complete. It covers purpose, usage, parameters, and return values. Since an output schema exists, the description doesn't need to detail the return structure beyond listing the metadata fields. It provides all necessary context for an agent to correctly invoke this 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?

Schema description coverage is 0%, so the description must fully compensate. It provides excellent parameter semantics: it explains 's3_uri' format with an example ('s3://bucket-name/path/to/file.csv'), defines 'env' as 'Target environment' with explicit valid values ('dev', 'uat', 'test', or 'prod'), and includes an IMPORTANT warning about not guessing/defaulting. This adds crucial context beyond the bare schema.

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 specific action ('Get detailed metadata for a single S3 object without downloading it') and distinguishes it from sibling tools like 'read_s3_file' (which downloads content) and 'browse_s3' (which lists objects). It explicitly mentions the resource type (S3 object) and scope (single object metadata only).

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 with 'USE THIS TOOL when the user asks about a specific file's size, modification time, type, or other details.' It also distinguishes this from content-reading alternatives by stating 'This is fast because it only reads the metadata header, not the file content.' This gives clear when-to-use criteria and contrasts with sibling tools that handle content.

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