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 mentions the tool is 'domain-agnostic' and that patterns are provided 'dynamically,' but fails to disclose critical behavioral traits such as whether this is a read-only analysis, potential side effects, performance characteristics, or error handling. The description adds minimal context beyond the basic operation.

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 the core purpose stated first, followed by domain context and parameter details. Each sentence adds value, though the parameter section could be more structured. There's minimal waste, but it's not perfectly optimized for quick scanning.

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 complexity of pattern detection, no annotations, and an output schema (which reduces the need to explain returns), the description is moderately complete. It covers the purpose and parameters at a high level but lacks details on behavioral traits and deeper parameter semantics, leaving gaps for an AI agent to infer usage correctly.

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 lists the three parameters ('claimed_output,' 'segment_id,' 'patterns') and briefly explains 'patterns' as 'Optional: Pattern definitions with trigger/expectedCompletion,' but doesn't clarify the meaning of 'claimed_output' or 'segment_id,' nor provide examples or constraints. This is insufficient for a 3-parameter tool with no schema documentation.

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: 'Detect when output may be completing a known pattern not in source.' It specifies the verb 'detect' and the resource 'pattern contamination,' but doesn't explicitly differentiate from sibling tools like 'detect_narrative_voice' or 'detect_semantic_frames' beyond mentioning it's 'domain-agnostic.'

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 by stating it's 'domain-agnostic' and that 'Agent provides patterns dynamically based on document genre,' suggesting it's for pattern detection across genres. However, it lacks explicit guidance on when to use this tool versus alternatives like 'detect_inference_violations' or 'validate_claim,' and doesn't specify exclusions or prerequisites.

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