BigContext 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 communicates that this is an analysis tool (not a mutation) and specifies what it returns (detected languages, original text presence, etc.). However, it doesn't mention potential limitations like rate limits, authentication requirements, or error conditions, leaving some behavioral aspects uncovered.

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 efficiently structured with a clear purpose statement, specific capabilities listed, critical usage guideline, and separate Args/Returns sections. Every sentence earns its place, with no redundant information, making it easy to parse while being comprehensive.

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 analytical nature, single parameter, and presence of an output schema (which handles return value documentation), the description provides complete context. It covers purpose, usage prerequisites, parameter meaning, and behavioral expectations without needing to duplicate what the output schema will specify about the analysis results.

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 has 0% description coverage for its single parameter 'document_id'. The description compensates by explaining that this is 'ID of the document to analyze,' providing essential context about what this parameter represents. While it doesn't specify format constraints or examples, it adds meaningful semantic value beyond the bare schema.

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 explicitly states the tool's purpose: 'Analyze what a document CAN and CANNOT support' with specific details about detecting languages, original text presence, variant availability, and epistemological limitations. It clearly distinguishes this analysis tool from siblings like 'get_metadata' or 'get_epistemological_report' by focusing on source capabilities rather than general metadata or epistemological assessments.

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: 'MUST be called before making claims about morphology, etymology, or textual criticism.' This creates clear prerequisites for using other tools and distinguishes it from alternatives like 'validate_claim' or 'detect_text_genre' by establishing it as a foundational analysis step.

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