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 describes key traits: it's a validation tool that detects specific unauthorized operations (synthesis, explanation, causality inference), returns compliance status, and provides safe fallbacks. However, it lacks details on error handling, performance implications, or system dependencies, which are important for a critical pre-response tool.

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: the first sentence states the critical purpose, followed by key functions and return details. Every sentence earns its place by adding essential information without redundancy, and the structured 'Args' and 'Returns' sections enhance clarity without verbosity.

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 (critical pre-response validation), no annotations, and an output schema present, the description is mostly complete. It covers purpose, usage, and behavioral aspects well, but could improve by detailing parameter semantics more thoroughly to compensate for low schema coverage, ensuring full agent understanding.

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 (document_id, query, planned_output) and implies their roles in validation, but does not provide detailed semantics (e.g., format of document_id, scope of query). The description adds some meaning by linking parameters to the audit process, but falls short of fully compensating for the schema gap.

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 ('validates cognitive constraint compliance', 'detects unauthorized operations') and resources ('document', 'query', 'planned output'). It distinguishes itself from siblings by focusing on pre-response validation rather than analysis or detection of specific violations like other tools (e.g., detect_inference_violations, validate_agency_execution).

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 usage guidance: 'CRITICAL: Run before ANY response' specifies when to use it (pre-response), and the focus on 'cognitive constraint compliance' and 'unauthorized operations' implies when not to use it (e.g., for post-analysis or non-cognitive tasks). It distinguishes from siblings by its preemptive, compliance-oriented role versus their specific analytical functions.

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