sharplens-mcp

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 detects reflection usage, outputs a list with API used, context, and location, and implies it performs analysis across projects (via the projectName parameter). However, it doesn't mention potential limitations like performance impact or analysis depth, which could be useful for a scanning 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 with the core purpose, followed by usage examples and specific use cases. Every sentence earns its place: the first defines the tool, the examples show how to call it, and the 'Use for' section provides critical context. No wasted words.

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?

For a tool with no annotations, no output schema, and 2 parameters, the description provides good contextual completeness. It explains what the tool does, when to use it, what it returns, and includes usage examples. The main gap is the lack of output schema details (e.g., structure of the 'List of reflection API calls'), but the description partially compensates by describing the output content.

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 schema description coverage is 100%, so the schema already fully documents both parameters (projectName and maxResults). The description adds minimal value beyond the schema by showing usage examples with these parameters, but doesn't provide additional semantic context like what 'projectName' refers to in the solution structure or how 'maxResults' affects performance.

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 ('detect dynamic/reflection-based type and method usage') and resources ('reflection API calls'), and explicitly distinguishes it from sibling tools by noting it finds usage 'invisible to static reference searches' (unlike tools like 'find_references' or 'find_callers' that likely perform static analysis).

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 ('Use for: finding hidden dependencies before refactoring, security audits, understanding dynamic behavior'), which clearly differentiates it from alternatives like static analysis tools in the sibling list. It also includes usage examples that show both default and parameterized invocations.

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