BigContext 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. It discloses behavioral traits such as scanning for specific terms and returning a detection result, but does not detail aspects like error handling, performance constraints, or what constitutes a 'violation' beyond listing terms. It adds some context but lacks comprehensive behavioral disclosure.

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 appropriately sized and front-loaded, with clear sections: purpose (first sentence), details (second sentence), and parameter/return info. Every sentence adds value without redundancy, making it efficient and well-structured.

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 (single parameter, no annotations, output schema exists), the description is mostly complete. It explains the purpose, parameters, and returns, and the output schema handles return values. However, it could benefit from more behavioral context or usage examples to fully compensate for the lack of annotations.

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 0% description coverage, but the description compensates by explaining the 'text' parameter as 'The text to scan for inference violations.' This adds meaning beyond the schema's type definition, clarifying the parameter's role. However, it does not elaborate on format or constraints, keeping it at a 4.

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 ('scan', 'detects') and resources ('text', 'inferential connectors', 'prohibited abstract nouns'), and distinguishes it from siblings by focusing on inference violations rather than other linguistic or cognitive operations like anachronisms, narrative voice, or semantic frames.

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 implies usage for scanning text to detect specific inference violations, but does not explicitly state when to use this tool versus alternatives (e.g., other detection tools like detect_pattern_contamination or validate_claim). It provides some context but lacks explicit guidance on exclusions or comparisons to sibling tools.

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