servicenow-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 of behavioral disclosure. While 'analyze' and 'recommend' imply a read-only, non-destructive operation, the description doesn't explicitly confirm this or address other behavioral aspects like permissions needed, rate limits, or what the output looks like (especially since there's no output schema). This leaves significant gaps for a tool that likely returns complex recommendations.

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 a single, efficient sentence that front-loads the core purpose. Every word earns its place: 'analyze' (action), 'software license usage' (resource), and 'recommend optimizations' (outcome). There's no wasted verbiage 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 license optimization analysis and the lack of both annotations and an output schema, the description is insufficient. It doesn't explain what the output contains (e.g., recommendations format, metrics), behavioral constraints, or error conditions. For a tool that likely returns structured insights, this leaves the agent poorly equipped to use it effectively.

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 fully documents both parameters. The description doesn't add any meaning beyond what the schema provides—it doesn't explain how 'software_name' filtering affects the analysis or what 'threshold_pct' actually thresholds (e.g., usage above which triggers optimization). With high schema coverage, the 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?

The description clearly states the tool's purpose with a specific verb ('analyze') and resource ('software license usage'), and specifies the outcome ('recommend optimizations'). It distinguishes itself from sibling tools like 'get_license_compliance' by focusing on optimization rather than compliance, though the distinction isn't explicitly stated in the description.

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. It doesn't mention prerequisites, typical use cases, or differentiate from similar tools like 'get_license_compliance' or 'list_software_licenses'. The agent must infer usage from the tool name and description alone.

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