Microsoft Azure · OpenAPI Overlay 1.0.0
API Evangelist conversational phrasing for Microsoft Azure Anomaly Detector Multivariate API
8 actions
8 updates
phrasing
extends
openapi/microsoft-azure-multivariate-api-openapi.yml
Generated by API Evangelist
Written by API Evangelist tooling for Microsoft Azure's API. It is a proposal applied on top of the contract, not a document Microsoft Azure publishes.
What the actions change
x-apievangelist-phrasing
Targets 8
$.info
$.paths['/multivariate/detect-batch/{resultId}'].get
$.paths['/multivariate/models'].get
$.paths['/multivariate/models'].post
$.paths['/multivariate/models/{modelId}'].get
$.paths['/multivariate/models/{modelId}'].delete
$.paths['/multivariate/models/{modelId}:detect-batch'].post
$.paths['/multivariate/models/{modelId}:detect-last'].post
OpenAPI Overlay
# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
title: API Evangelist conversational phrasing for Microsoft Azure Anomaly Detector Multivariate API
version: 1.0.0
extends: openapi/microsoft-azure-multivariate-api-openapi.yml
actions:
- target: $.info
update:
x-apievangelist-phrasing:
method: generated
generated: '2026-09-26'
generator: build-phrasing.py
label: Generated by API Evangelist
operations: 7
- target: $.paths['/multivariate/detect-batch/{resultId}'].get
update:
x-apievangelist-phrasing:
intent: Get a batch anomaly detection result
effect: read
questions:
- How do I get the results of an asynchronous multivariate anomaly detection?
- Is my batch detection result ready yet?
instructions:
- text: Get batch detection result {result}.
slots:
result: path.resultId
- text: Show the anomalies found in detection result {result}.
slots:
result: path.resultId
method: generated
generated: '2026-09-26'
- target: $.paths['/multivariate/models'].get
update:
x-apievangelist-phrasing:
intent: List multivariate anomaly models
effect: read
questions:
- Which multivariate anomaly detection models have I trained?
- Can I page through my anomaly detector models?
instructions:
- text: List my multivariate anomaly models.
- text: Show {top} anomaly models, skipping the first {skip}.
slots:
top: query.top
skip: query.skip
method: generated
generated: '2026-09-26'
- target: $.paths['/multivariate/models'].post
update:
x-apievangelist-phrasing:
intent: Train a multivariate anomaly model
effect: write
questions:
- How do I train a multivariate anomaly detection model from data in Blob Storage?
- Can I set the sliding window when training an anomaly model?
instructions:
- text: Train an anomaly model on {source} from {start} to {end}.
slots:
source: requestBody.dataSource
start: requestBody.startTime
end: requestBody.endTime
- text: Train model {name} on {source} between {start} and {end} with sliding window {window}.
slots:
name: requestBody.displayName
source: requestBody.dataSource
start: requestBody.startTime
end: requestBody.endTime
window: requestBody.slidingWindow
method: generated
generated: '2026-09-26'
- target: $.paths['/multivariate/models/{modelId}'].get
update:
x-apievangelist-phrasing:
intent: Get a multivariate anomaly model
effect: read
questions:
- Has my multivariate anomaly model finished training?
- Which variables does a trained anomaly model use?
instructions:
- text: Get multivariate model {model}.
slots:
model: path.modelId
- text: Show the training status and variables of model {model}.
slots:
model: path.modelId
method: generated
generated: '2026-09-26'
- target: $.paths['/multivariate/models/{modelId}'].delete
update:
x-apievangelist-phrasing:
intent: Delete a multivariate anomaly model
effect: destructive
questions:
- Can I delete an anomaly detection model I no longer need?
- What happens to a model's detection results after I delete it?
instructions:
- text: Delete multivariate model {model}.
slots:
model: path.modelId
- text: Remove anomaly model {model} permanently.
slots:
model: path.modelId
method: generated
generated: '2026-09-26'
- target: $.paths['/multivariate/models/{modelId}:detect-batch'].post
update:
x-apievangelist-phrasing:
intent: Run batch multivariate anomaly detection
effect: write
questions:
- How do I detect anomalies across a whole time range of stored data?
- Can I ask for the top contributing variables per anomaly in a batch run?
instructions:
- text: Run batch detection with model {model} on {source} from {start} to {end}.
slots:
model: path.modelId
source: requestBody.dataSource
start: requestBody.startTime
end: requestBody.endTime
- text: Detect batch anomalies using model {model} on {source}, {start} to {end}, top {count} contributors.
slots:
model: path.modelId
source: requestBody.dataSource
start: requestBody.startTime
end: requestBody.endTime
count: requestBody.topContributorCount
method: generated
generated: '2026-09-26'
- target: $.paths['/multivariate/models/{modelId}:detect-last'].post
update:
x-apievangelist-phrasing:
intent: Detect anomalies in the latest data point
effect: read
questions:
- Can I check whether my newest data point is anomalous right away?
- How do I get synchronous anomaly detection with inline variables?
instructions:
- text: Check the last point of {variables} for anomalies with model {model}.
slots:
variables: requestBody.variables
model: path.modelId
- text: Score the latest timestamp with model {model} and return the top {count} contributors.
slots:
model: path.modelId
count: requestBody.topContributorCount
method: generated
generated: '2026-09-26'
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