AI FileSystem MCP

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. While 'suggest' implies a read-only, advisory operation rather than actual code modification, the description doesn't clarify whether this requires specific permissions, what format the suggestions come in, whether it analyzes the entire file or specific sections, or any limitations on file types or sizes. For a 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 extremely concise at just three words, with zero wasted language. It's front-loaded with the core purpose and contains no unnecessary elaboration. Every word earns its place in communicating the essential function.

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 complexity of code analysis/refactoring tools, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what kind of suggestions are provided, in what format, whether they include examples or justifications, or any limitations. For a tool that presumably analyzes code structure and provides recommendations, this leaves too much undefined for effective agent use.

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 both parameters ('path' and 'type') with descriptions and enum values. The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining what 'all' versus specific refactoring types mean in practice or providing examples of valid paths. This meets the baseline expectation when schema coverage is complete.

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 a specific verb ('suggest') and resource ('code refactoring improvements'), making it immediately understandable. However, it doesn't distinguish this tool from potential siblings like 'analyze_code' or 'modify_code' that might also relate to code analysis or transformation.

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. With siblings like 'analyze_code', 'format_code', 'modify_code', and 'security_audit' that might overlap in code analysis contexts, there's no indication of when this specific refactoring suggestion tool is appropriate versus those other options.

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