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 of behavioral disclosure. It mentions what the tool detects but lacks details on how it operates (e.g., detection methodology, accuracy, limitations), response format beyond 'Anachronism check result', or any side effects. This is a significant gap for a tool with no annotation coverage.

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 front-loaded with the core purpose, followed by specific detection targets and structured parameter/return sections. Every sentence adds value without redundancy, making it efficient and well-organized for quick understanding.

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 complexity (detection of specific conceptual categories), lack of annotations, and presence of an output schema, the description is moderately complete. It covers purpose and parameter semantics but lacks behavioral details (e.g., how detection works, limitations). The output schema mitigates some gaps, but more context on operation would improve completeness.

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 description adds meaningful context for the single parameter 'query' by specifying it as 'The research question or claim to check', which clarifies its purpose beyond the schema's basic type definition. With 0% schema description coverage and only one parameter, this compensation is effective, though not exhaustive (e.g., no format examples).

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 ('Check') and resource ('research question'), specifying what it detects (Aristotelian causes, Neoplatonic emanation, Trinitarian doctrine). It distinguishes itself from siblings by focusing on anachronisms rather than other analytical tasks like validation or detection of other patterns.

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 checking research questions or claims for specific conceptual categories, but does not explicitly state when to use this tool versus alternatives (e.g., other detection or validation tools). No exclusions or prerequisites are mentioned, leaving usage context somewhat vague.

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