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open_incident

Open an incident on a DataHub asset to surface data breaks to humans for quick resolution.

Instructions

Open an incident on an asset in DataHub, so the break is visible to humans.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
dataset_urnYes
descriptionYes
incident_typeNoOPERATIONAL

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description alone must disclose behavioral traits. It only says the action makes a break visible, but does not explain mutation effects, idempotency, permission requirements, or what happens to existing incidents. This is insufficient for a mutation tool.

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 a single, front-loaded sentence that avoids unnecessary words. It efficiently conveys the core function and purpose without redundancy.

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

Completeness2/5

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

With no annotations and 0% parameter description coverage, the tool requires more context than provided. The output schema exists, so return values need not be described, but the description leaves gaps in usage guidance, parameter semantics, and behavioral transparency. Sibling tools like resolve_incident suggest a lifecycle, but the description does not position itself within it.

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

Parameters1/5

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

Schema description coverage is 0% and the description adds no parameter-level detail. The phrases 'on an asset' and 'the break' loosely map to dataset_urn and description, but there is no explicit explanation of what each parameter means, how they relate, or the expected format for incident_type.

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 action ('Open an incident') and the resource ('an asset in DataHub'), with a specific purpose ('so the break is visible to humans'). This distinguishes it from siblings like resolve_incident, which handles closing incidents.

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

Usage Guidelines3/5

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

The description implies the usage context (surfacing a break for human visibility), but it does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. No sibling distinctions are drawn.

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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