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Sourolio10

servicenow-mcp-agent

by Sourolio10

get_ci_relationships

Traverse CMDB dependencies to find what breaks if a CI fails (downstream) or what it depends on (upstream) for root-cause analysis.

Instructions

Traverse CMDB dependencies to answer impact and root-cause questions.

Args: name: exact CI name. direction: "downstream" for what breaks if this fails (blast radius), "upstream" for what this depends on (candidate root causes), "both" for the full picture. Default both. depth: relationship hops to follow, 1-5. Default 2. Increase when a dependency chain is longer than two links.

Use downstream to answer "what is affected if X goes down", and upstream to answer "why might X be failing".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
depthNo
directionNoboth

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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 explains the traversal semantics (direction, depth) and interpretation for impact/root-cause analysis, but does not mention error handling for missing CIs, authorization requirements, or potential performance implications of large depth values. It omits edge-case behavior that could affect invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficient and well-structured. It opens with a clear purpose, then uses an 'Args' block to detail parameters, and ends with concrete usage examples. Every sentence contributes meaning, with no redundant or filler content. The structure is conventional and easily parsed by an agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema (which covers return format), the description adequately covers the core semantics needed to call the tool correctly: direction interpretation, depth semantics, and exact-name requirement. It does not address error conditions or result limits, but for a traversal tool the key operational details are present. The absence of error-handling notes is a minor gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, so the description fully compensates. It explains 'name' as exact CI name, defines each 'direction' value with concrete meanings, and specifies 'depth' range (1-5), default, and guidance for increasing it. This is thorough parameter documentation that would otherwise be absent.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose ('Traverse CMDB dependencies') and distinguishes it from siblings like get_ci (single CI lookup) and search_cmdb (general search). It specifies a concrete resource type (CMDB dependencies) and defines the operation (traversal).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage scenarios for the 'direction' parameter ('Use downstream to answer... and upstream to answer...') and advises when to increase depth. It establishes clear context for when this tool is appropriate, though it does not explicitly name alternative tools or state when not to use it.

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

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