BigContext MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it explains the three possible confidence outcomes ('textual', 'partial', 'not_found'), describes the fuzzy matching mechanism with threshold parameter context, and clarifies the preventive purpose against hallucination. It doesn't mention rate limits, authentication needs, or performance characteristics, but covers the core operational behavior adequately.

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 perfectly structured and concise. The first sentence states the core purpose, followed by usage timing, return values explanation, and preventive benefit. The Args and Returns sections are clearly labeled and provide essential information without redundancy. Every sentence earns its place with no wasted words.

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, 1 required), no annotations, but with an output schema present, the description provides excellent contextual completeness. It covers purpose, usage timing, behavioral outcomes, parameter semantics, and the preventive rationale. The existence of an output schema means the description doesn't need to detail return structure, allowing it to focus on operational context, which it does comprehensively.

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?

With 0% schema description coverage, the description must compensate and does so effectively for most parameters. It explains 'quote' as 'exact quote to validate', clarifies that document_id and segment_id are optional search scopes, and provides meaningful context for 'fuzzy_threshold' as 'similarity threshold for partial matches (0-1)'. The description doesn't explicitly mention the default value for fuzzy_threshold or the null handling for optional parameters, but provides substantial 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 clearly states the tool's purpose with specific verbs ('verify', 'validate') and resources ('quoted string', 'segment or document'). It distinguishes itself from siblings by focusing on exact quote validation rather than broader analysis or search operations, with explicit mention of preventing 'pattern completion hallucination' which sets it apart from tools like 'search_segment' or 'validate_claim'.

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: 'Use BEFORE claiming any text appears in the source.' This creates clear context for application and distinguishes it from reactive validation tools. While it doesn't name specific alternatives, the 'before' timing guidance effectively positions this as a preventive measure against hallucination.

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