servicenow-mcp

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

No annotations are provided, so the description carries full burden. It mentions what gets analyzed (completeness, duplicates, stale records) but doesn't disclose behavioral traits like whether this is a read-only operation, what permissions are required, how long it takes, whether it modifies data, what the output format looks like, or any rate limits. For a data analysis tool with zero annotation coverage, this is a significant gap.

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 extremely concise and front-loaded with essential information in a single, efficient sentence. Every word earns its place by specifying the action, target, and key analysis dimensions without any fluff or redundancy.

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 data quality analysis (multiple dimensions, potential for large datasets), no annotations, and no output schema, the description is inadequate. It doesn't explain what the analysis returns, how results are structured, whether it's a lightweight check or resource-intensive scan, or any error conditions. For a tool that likely produces rich output, this leaves too much undefined.

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%, so the schema already documents all three parameters thoroughly. The description adds marginal value by implying the 'days_stale' parameter relates to 'stale records' analysis, but doesn't provide additional syntax, format details, or examples beyond what the schema provides. Baseline 3 is appropriate when schema does the heavy lifting.

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: 'Analyse data quality for a table — completeness, duplicates, stale records'. It specifies the verb ('Analyse'), resource ('data quality for a table'), and key quality dimensions. However, it doesn't explicitly distinguish this from sibling tools like 'check_table_completeness' or 'compare_record_counts', which appear to be related but more specific.

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. With many sibling tools that might overlap (e.g., 'check_table_completeness', 'compare_record_counts', 'query_records'), there's no indication of when this comprehensive analysis is preferred over more targeted tools or what prerequisites might be needed.

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