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 states the tool 'Get's metadata, implying a read-only operation, but doesn't clarify permissions, rate limits, or error handling. The mention of 'top terms by TF-IDF' adds some context, but key behavioral traits like whether it's idempotent or safe are missing, leaving gaps for a tool with parameters.

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 with a purpose statement, bullet-pointed arguments, and a returns section. It's appropriately sized at four sentences, with each sentence adding value (e.g., specifying TF-IDF, explaining parameters). Minor improvements could include front-loading key details more, but overall it's efficient with minimal waste.

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 (4 parameters, no annotations, but with an output schema), the description is fairly complete. It covers purpose, parameters, and return values, and the output schema reduces the need to detail response structure. However, it lacks behavioral context (e.g., error cases) and sibling differentiation, which holds it back from a perfect score.

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 0%, so the description must compensate. It provides a clear 'Args' section explaining all four parameters: 'document_id' and 'segment_id' for targeting, 'include_structure' for optional structure inclusion, and 'top_terms' for term count with a default. This adds significant meaning beyond the bare schema, though it could detail parameter interactions (e.g., using both IDs).

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 retrieves 'metadata, structure, and statistics for a document or segment' and specifically mentions 'top terms by TF-IDF.' This provides a specific verb ('Get') and resource ('document or segment') with additional details about what metadata includes. However, it doesn't explicitly differentiate from sibling tools like 'list_documents' or 'get_adjacent_segments' beyond the metadata focus.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing an existing document ID from 'list_documents' or 'ingest_document,' or contrast it with siblings like 'analyze_subdetermination' or 'get_epistemological_report' that might handle different aspects of document analysis. Usage is implied by the purpose but not explicitly stated.

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