audit_mcp_dataset

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 discloses output formats (markdown and/or DOCX) and mentions sections, but does not confirm read-only behavior, prerequisites, error handling, or what happens if the dataset is missing. More behavioral context would be beneficial.

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?

Description is a single, dense sentence that conveys the essential purpose and outputs. It front-loads key terms (executive-ready, orchestrated). While efficient, breaking into structured points could improve scanability.

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 10 optional parameters and no output schema, the description provides a clear overview of what the report includes: health rating, strengths/gaps, recommendations, and specific sections. However, it does not detail return values or structure, leaving some gaps for the agent.

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 100% for all 10 parameters, providing detailed descriptions. The tool description adds a high-level summary of the report contents but does not elaborate on parameters beyond what the schema already offers. Baseline score of 3 is appropriate.

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?

Description clearly states the tool produces an 'executive-ready orchestrated dataset audit' with a narrative assessment, health rating, strengths/gaps, recommendations, and sections on governance, consumption, and settings. This specific verb+resource combination distinguishes it from sibling 'audit_dataset' by emphasizing 'orchestrated' and 'executive-ready'.

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?

Description implies use for a comprehensive, high-level audit but does not explicitly state when to use this vs. simpler alternatives like 'audit_dataset' or other sibling tools. No when-not-to or context exclusions are provided.

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