reject_change
Reject a ServiceNow change request by providing the change ID and rejection reason to prevent implementation of unwanted modifications.
Instructions
Reject a change request
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Reject a ServiceNow change request by providing the change ID and rejection reason to prevent implementation of unwanted modifications.
Reject a change request
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure but offers none. It doesn't indicate whether this is a destructive/mutative operation (implied by 'reject' but not explicit), what permissions are required, what happens after rejection (e.g., status change, notifications), or any error conditions. For a tool that likely modifies system state, this is critically inadequate.
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 maximally concise at just four words. While this represents severe under-specification rather than ideal conciseness, from a pure structural perspective it's front-loaded with the core action and contains no wasted words. Every word earns its place, even though that place is insufficient.
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 a state-changing operation like rejecting a change request, no annotations, no output schema, and 0% schema description coverage, the description is completely inadequate. It doesn't explain what the tool does beyond the name, when to use it, what parameters mean, what happens after rejection, or what the response contains. This leaves the agent with minimal actionable information.
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 description provides zero information about parameters, while the schema description coverage is 0% (parameter descriptions like 'Change request ID or sys_id' come from the schema, not the tool description). With 1 required parameter (a nested object with 3 fields) and no parameter guidance in the description, the agent must rely entirely on the schema without any contextual explanation of what 'rejecting' actually requires.
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 'Reject a change request' is a tautology that essentially restates the tool name 'reject_change' without adding meaningful specificity. While it identifies the verb ('reject') and resource ('change request'), it doesn't distinguish this from sibling tools like 'approve_change' or provide any context about what rejecting entails beyond the obvious meaning of the name.
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 absolutely no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., that a change request must be in a specific state), exclusions, or relationships to sibling tools like 'approve_change', 'submit_change_for_approval', or 'update_change_request'. This leaves the agent guessing about proper context.
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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