gerbil-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 states the tool evaluates an expression and returns a result, but lacks critical details such as execution environment constraints, error handling, security implications, or performance characteristics. This is insufficient for a tool that executes code, leaving significant gaps in understanding its behavior.

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 concise and well-structured in two sentences: the first states the core functionality, and the second provides usage guidance with a concrete example. Every sentence adds value, and it's front-loaded with the main purpose. A slight deduction because the example could be more efficiently integrated.

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 a code evaluation tool with no annotations and no output schema, the description is incomplete. It doesn't cover important aspects like return value format, error responses, execution limits, or safety considerations. For a tool that executes arbitrary code, this lack of context is a significant shortfall.

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 fully documents both parameters (expression and imports). The description adds minimal value beyond the schema: it reiterates the purpose of imports ('to make module bindings available') and provides an example, but doesn't explain parameter interactions or edge cases. This meets the baseline for high schema coverage.

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: 'Evaluate a Gerbil Scheme expression using gxi and return the result.' It specifies the verb ('evaluate'), resource ('Gerbil Scheme expression'), and method ('using gxi'), but doesn't explicitly differentiate it from sibling tools like gerbil_check_syntax or gerbil_expand_macro, which prevents 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 minimal guidance on when to use this tool. It mentions the imports parameter to make module bindings available and gives an example, but doesn't explain when to choose this tool over alternatives like gerbil_check_syntax for syntax validation or gerbil_expand_macro for macro expansion. No explicit when-not-to-use or prerequisite information is included.

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