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. It mentions the tool is 'AI-powered' and uses 'similar past incidents,' which adds some context about how it works. However, it lacks critical details such as whether this is a read-only operation, what permissions are required, how the suggestions are formatted, or if there are rate limits. The description does not contradict annotations, but it is insufficient for a mutation-like tool with no annotation coverage.

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 directly states the tool's purpose without unnecessary words. It is front-loaded with the core functionality ('Get AI-powered resolution suggestion'), making it easy to understand quickly. There is no wasted verbiage or redundant information.

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 moderate complexity (AI-powered suggestion based on past incidents), no annotations, and no output schema, the description is minimally adequate. It explains what the tool does but lacks details on behavior, output format, and usage context. The high schema coverage helps, but the description does not fully compensate for the missing annotations and output schema, leaving gaps in understanding how to effectively use the tool.

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?

The input schema has 100% description coverage, with one parameter ('incident_sys_id') clearly documented. The description does not add any additional meaning beyond the schema, such as explaining what an 'incident_sys_id' is or providing examples. Since schema coverage is high, the baseline score of 3 is appropriate, as the schema already provides adequate parameter 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: 'Get AI-powered resolution suggestion for an incident based on similar past incidents.' It specifies the verb ('Get'), resource ('resolution suggestion'), and mechanism ('AI-powered...based on similar past incidents'). However, it does not explicitly differentiate from sibling tools like 'resolve_incident' or 'generate_summary,' which could provide alternative resolution-related functions.

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 does not mention prerequisites, such as requiring an existing incident, or compare it to other tools like 'resolve_incident' (which might directly resolve incidents) or 'generate_summary' (which could generate summaries without resolution suggestions). Usage is implied but not explicitly stated.

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