DataWorks Data Quality (Read-Only)#

Query and investigate Rule Templates, Data Quality Monitors, Alert Rules, and Scan Run Records in Alibaba Cloud DataWorks.

Coverage: All Get/List read-only OpenAPIs under DataWorks Data Quality, totaling 9: ListDataQualityTemplates / GetDataQualityTemplate · ListDataQualityScans / GetDataQualityScan · ListDataQualityAlertRules / GetDataQualityAlertRule · ListDataQualityScanRuns / GetDataQualityScanRun / GetDataQualityScanRunLog Excludes write operations: Create / Update / Delete / CreateDataQualityScanRun.

Read-Only Skill: This skill supports query operations only. Any write operation request must be blocked immediately — direct the user to the DataWorks console.

Architecture#

text

DataWorks Data Quality
├── Rule Templates ─── Reusable metric logic definitions (built-in & custom)
│
├── Data Quality Monitors (Scans) ─── Monitor tasks bound to tables, with rules and trigger config
│   └── Alert Rules ─── Notification rules tied to a monitor (channels, recipients, conditions)
│
└── Scan Runs ─── Execution records each time a monitor runs
    └── Scan Run Logs ─── Detailed execution logs for a run

---

Global Rules#

Prerequisites#

1. Aliyun CLI >= 3.3.3: aliyun version (If not installed or version too low, run curl -fsSL https://aliyuncli.alicdn.com/setup.sh | bash to install/update. See references/cli-installation-guide.md)

2. First-time use: aliyun configure set --auto-plugin-install true

3. Plugin update: [MUST] run aliyun plugin update to ensure that any existing plugins on your local machine are always up-to-date.

4. AI-Mode Configuration: [MUST] Before using aliyun CLI commands, configure AI-Mode:

   • aliyun configure ai-mode enable
   • aliyun configure ai-mode set-user-agent --user-agent "AlibabaCloud-Agent-Skills/alibabacloud-dataworks-data-quality"
   • aliyun configure ai-mode disable

5. jq (recommended for output formatting): which jq

6. Credential status: aliyun configure list, verify valid credentials exist

Security Rules: DO NOT read/print/echo AK/SK values. ONLY use aliyun configure list to check credential status.

Command Formatting#

• User-Agent (mandatory): All aliyun CLI commands must include --user-agent AlibabaCloud-Agent-Skills/alibabacloud-dataworks-data-quality.
• Timeout (mandatory): All aliyun CLI commands must include --connect-timeout 5 --read-timeout 10. These match the CLI built-in defaults and make the timeout policy explicit.
• Single-line commands: Construct as a single-line string; do not use \ for line breaks.
• jq step-by-step: First execute the aliyun command to get JSON, then pipe to jq for formatting.
• Endpoint mandatory: When specifying --region, you must also add --endpoint dataworks.<REGION_ID>.aliyuncs.com.

Parameter Confirmation#

Must be explicitly provided by user — do not assume or use defaults:

• ProjectId: Core parameter for every query — must be confirmed
• Id-type resource identifiers: template ID, monitor ID, alert rule ID, scan run ID
• region: Affects endpoint — must be confirmed

Can use default values directly — no user confirmation needed:

• PageNumber: default 1
• PageSize: default 10
• SortBy: default ModifyTime Desc or CreateTime Desc

Ask contextually — only collect when the user has a specific need:

• Name, Table: fuzzy search keywords
• Time range: CreateTimeFrom / CreateTimeTo
• Status: collect only when the user explicitly wants to filter by a specific status

If the user has already provided ProjectId, Id, or region in the conversation, reuse them directly without re-confirmation.

Time Parameter Conversion#

When the user describes time in natural language, convert it to millisecond timestamps automatically. Do not ask the user to provide raw timestamps.

• "yesterday" → yesterday 00:00:00 to 23:59:59
• "today" → today 00:00:00 to current time
• "last N days" → current time minus N × 24 hours through current time
• If the time phrase is ambiguous, ask a clarification question and offer a suggested range

Query Result Presentation#

After every query, present the result in a decision-friendly way:

• List queries: use a Markdown table for key fields such as ID, name, status, and time; do not dump raw JSON
• Detail queries: present a short summary first, then expand full Spec only if the user asks
• Abnormal status: highlight Fail / Error / Warn, and proactively recommend the next diagnostic step
• Empty result: explain likely causes such as wrong ProjectId, wrong region, or filters that are too strict

Pagination#

• First query uses the default PageSize of 10
• If the number of returned rows equals PageSize, proactively offer next page or a larger PageSize
• Do not fetch more than 100 records in a single request

⚠️ Read-Only Execution Gate#

MANDATORY: Before responding to ANY request, check whether it involves a write operation. If YES: BLOCK immediately. Do NOT call any API. Respond with: "This skill supports query operations only and cannot perform create/update/delete. Please go to the DataWorks Console for configuration."

Quick Reference — All Blocked Operations：

Operation TypeBlocked APIsCreateCreateDataQualityTemplate, CreateDataQualityScan, CreateDataQualityScanRun, CreateDataQualityAlertRuleUpdateUpdateDataQualityTemplate, UpdateDataQualityScan, UpdateDataQualityAlertRuleDeleteDeleteDataQualityTemplate, DeleteDataQualityScan, DeleteDataQualityAlertRuleTriggerCreateDataQualityScanRun (manual execution trigger)

RAM Permissions#

All operations require dataworks:<APIAction> permissions on the target workspace.

Full permission matrix: references/ram-policies.md

---

Quick Start: Data Quality Investigation#

When the user request is vague, use the following default path:

1. Environment check — Confirm CLI and credentials per Prerequisites. After completion, proactively suggest the workspace confirmation step.
2. Confirm workspace — Confirm ProjectId and region. If either is missing, use Module 0. After completion, proactively suggest listing monitors.
3. List monitors — Call ListDataQualityScans, present a table, and let the user choose a monitor. After completion, proactively suggest monitor detail.
4. Check monitor detail — Call GetDataQualityScan, summarize rules, monitored object, and trigger mode. After completion, proactively suggest recent runs.
5. Check run history — Call ListDataQualityScanRuns, default to the most recent 10 rows, and highlight abnormal status. After completion, proactively suggest drilling into one run.
6. Drill into failed or warned runs — For Fail / Error / Warn, call GetDataQualityScanRun and summarize per-rule results. After completion, proactively suggest log inspection.
7. Fetch execution logs — If Results shows failed rules or runtime errors, call GetDataQualityScanRunLog to locate root cause. After completion, proactively suggest whether further analysis is needed.

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Next Step Guidance#

Completed OperationRecommended Next StepListDataQualityTemplates"Would you like to view the full configuration of a specific template? (GetDataQualityTemplate)"GetDataQualityTemplate"Would you like to view monitors that use this template? (ListDataQualityScans)"ListDataQualityScans"Select a monitor to view its full configuration? (GetDataQualityScan)"GetDataQualityScan"View associated alert rules (ListDataQualityAlertRules) or recent run history (ListDataQualityScanRuns)?"ListDataQualityAlertRules"View details for a specific alert rule? (GetDataQualityAlertRule)"GetDataQualityAlertRule"Return to view run history for the associated monitor? (ListDataQualityScanRuns)"ListDataQualityScanRuns"View detailed results for a specific run? (GetDataQualityScanRun)"GetDataQualityScanRun (Pass)"This run passed. Would you like to view other run records or alert configuration?"GetDataQualityScanRun (Fail/Error/Warn)"Anomaly detected — recommend viewing execution logs to locate the root cause. (GetDataQualityScanRunLog)"GetDataQualityScanRunLog (NextOffset=-1)"Log retrieval complete. Is further analysis needed?"GetDataQualityScanRunLog (NextOffset≠-1)"Log not fully retrieved — continue fetching the next segment. (Retry with Offset)"

---

Trigger Rules#

Trigger scenarios: Query data quality monitors/rules/templates/alerts/scan runs/logs, diagnose data quality check failures, view quality alert notification configuration, list/get quality scan/rule/template/alert/run

Not triggered:

• Creating/updating/deleting data quality configuration → Use DataWorks Console
• Data source/compute resource/resource group management → alibabacloud-dataworks-infra-manage
• Workspace query/member management → alibabacloud-dataworks-workspace-manage
• Data development node/scheduling configuration → alibabacloud-dataworks-datastudio-develop

---

Interaction Flow#

Identify query intent → Environment check → Module 0 (if ProjectId/region missing) → Collect parameters → Execute command → Present results → Guide next step

Common aliases: DW = DataWorks, DQ = Data Quality, scan = monitor, scan run = execution record

---

Module 0: Workspace / ProjectId / Region Query#

If the alibabacloud-dataworks-workspace-manage skill is available, prefer using it for workspace lookup. The following is only a fallback.

bash

aliyun dataworks-public list-projects --user-agent AlibabaCloud-Agent-Skills/alibabacloud-dataworks-data-quality --status Available --page-size 100

Rules:

• If the user provides only a workspace name, list candidate workspaces and ask the user to confirm the ProjectId
• If ProjectId is unknown, ask for it explicitly and never guess
• If region is unknown, offer common regions for confirmation: cn-hangzhou, cn-shanghai, cn-beijing, cn-shenzhen
• Once ProjectId and region are confirmed in the conversation, reuse them in later steps

Intent guidance:

• "there's a data quality issue" → ask whether the user wants monitor configuration, run records, or alert settings
• "show me this table" → start with list-data-quality-scans --table <TABLE_NAME>
• If the intent is still unclear, ask the user to choose one of four modules: rule templates, monitors, alert rules, or scan runs

---

Module 1: Rule Templates#

Rule templates define reusable metric logic such as null rate, duplicate rate, row count, and custom SQL checks. Use this module when the user wants to know what a template checks, whether it is built-in or workspace-specific, and how its threshold logic is defined.

Task 1.1: List Rule Templates (ListDataQualityTemplates)#

Always call ListDataQualityTemplates whenever the user asks about quality rule templates in their workspace. Never answer without invoking the API.

Scope: This API only returns workspace custom templates. It does not support querying system built-in templates. --project-id is required — if the user has not provided ProjectId, collect it first via Module 0.

bash

aliyun dataworks-public list-data-quality-templates --user-agent AlibabaCloud-Agent-Skills/alibabacloud-dataworks-data-quality [--region <REGION_ID> --endpoint dataworks.<REGION_ID>.aliyuncs.com] --project-id <PROJECT_ID> [--name <FUZZY_NAME>] [--catalog <CATALOG_PATH>] [--page-number 1] [--page-size 10]

How to interpret the result:

• PageInfo.DataQualityTemplates[] is the working set for user selection
• Present a Markdown table of Id, template name (from Spec), Catalog/category, and description — do not dump raw JSON
• Use Catalog and template naming patterns to tell the user what class of checks is available
• After listing, proactively suggest the user pick a template ID to view full configuration via GetDataQualityTemplate
• If the user asks about system built-in templates, explain this API only covers workspace custom templates and direct them to the DataWorks console

Task 1.2: Get Rule Template Details (GetDataQualityTemplate)#

bash

aliyun dataworks-public get-data-quality-template --user-agent AlibabaCloud-Agent-Skills/alibabacloud-dataworks-data-quality [--region <REGION_ID> --endpoint dataworks.<REGION_ID>.aliyuncs.com] --id <TEMPLATE_ID>

How to interpret the result:

• Focus on Spec: summarize the metric logic, parameter definitions, and threshold expression
• Tell the user what this template checks and how pass/fail is decided
• Mention whether the template belongs to a workspace ( ProjectId present) or is reused as a generic template
• Expand full Spec only when the user explicitly asks for raw detail

---

Module 2: Data Quality Monitors#

A data quality monitor (scan) is a concrete monitoring task bound to a table or field. Use this module to locate monitors, explain what they check, and understand how they are triggered.

Task 2.1: List Data Quality Monitors (ListDataQualityScans)#

bash

aliyun dataworks-public list-data-quality-scans --user-agent AlibabaCloud-Agent-Skills/alibabacloud-dataworks-data-quality [--region <REGION_ID> --endpoint dataworks.<REGION_ID>.aliyuncs.com] --project-id <PROJECT_ID> --page-number 1 --page-size 10 [--name <FUZZY_NAME>] [--table <FUZZY_TABLE_NAME>] [--sort-by "ModifyTime Desc"]

How to interpret the result:

• PageInfo.DataQualityScans[] is the candidate monitor list; show Id, Name, Description, owner, and latest update time
• When --Table is used, explicitly tell the user these monitors are the likely matches for that table
• Use the table to help the user choose one target monitor before moving to detail query
• When the list is empty, suggest checking ProjectId, region, or relaxing Name / Table

Task 2.2: Get Monitor Details (GetDataQualityScan)#

bash

aliyun dataworks-public get-data-quality-scan --user-agent AlibabaCloud-Agent-Skills/alibabacloud-dataworks-data-quality [--region <REGION_ID> --endpoint dataworks.<REGION_ID>.aliyuncs.com] --id <SCAN_ID>

How to interpret the result:

• Spec: summarize monitored object, rule count, core metrics, and threshold settings
• Trigger: explain whether the monitor is ByManual or BySchedule
• ComputeResource and RuntimeResource: mention them only when they help explain execution behavior
• Parameters and Hooks: summarize only if they affect how the run is triggered or analyzed
• Present a concise monitor summary first, then suggest alert-rule or run-history follow-up

---

Module 3: Alert Rules#

Alert rules define when notifications are sent and to whom. Use this module when the user asks who gets notified, through which channel, and under what condition.

Receiver Type Quick Reference

ReceiverTypeDescriptionAliUidSpecific Alibaba Cloud account UIDDataQualityScanOwnerOwner of the data quality monitor taskTaskOwnerOwner of the associated scheduling taskDingdingUrlDingTalk custom robot WebhookFeishuUrlFeishu custom robot WebhookWeixinUrlWeCom WebhookWebhookUrlGeneric Webhook URLShiftScheduleOn-call schedule (notify by shift)

Task 3.1: List Alert Rules (ListDataQualityAlertRules)#

bash

aliyun dataworks-public list-data-quality-alert-rules --user-agent AlibabaCloud-Agent-Skills/alibabacloud-dataworks-data-quality [--region <REGION_ID> --endpoint dataworks.<REGION_ID>.aliyuncs.com] --project-id <PROJECT_ID> --page-number 1 --page-size 10 [--data-quality-scan-id <SCAN_ID>] [--sort-by "CreateTime Desc"]

How to interpret the result:

• PageInfo.DataQualityAlertRules[] should be summarized as: rule ID, condition, channels, receivers, and associated monitor IDs
• Translate Notification.Channels into user-friendly channel names such as DingTalk, email, Feishu, SMS, or Webhook
• Summarize Notification.Receivers by receiver type instead of showing nested raw JSON
• If DataQualityScanId is provided, explicitly state these are the alert rules attached to that monitor

Task 3.2: Get Alert Rule Details (GetDataQualityAlertRule)#

bash

aliyun dataworks-public get-data-quality-alert-rule --user-agent AlibabaCloud-Agent-Skills/alibabacloud-dataworks-data-quality [--region <REGION_ID> --endpoint dataworks.<REGION_ID>.aliyuncs.com] --id <ALERT_RULE_ID>

How to interpret the result:

• Explain the alert condition in plain language
• Summarize notification channels and recipients with emphasis on who will be notified and how
• Call out whether the rule targets one monitor or multiple monitors
• If the user is diagnosing missing alerts, suggest returning to recent run history for the associated monitor

---

Module 4: Scan Runs#

A scan run is created every time a monitor executes. Use this module to inspect run history, diagnose failed checks, and read execution logs.

Status Quick Reference

StatusMeaningRecommended PathPassAll rules passedNo action neededFailAt least one rule failed to meet the thresholdGetDataQualityScanRun → Results → GetDataQualityScanRunLogErrorExecution error (engine error, insufficient resources)GetDataQualityScanRunLog to view error detailsWarnWarning triggered but did not reach the blocking thresholdGetDataQualityScanRun → Results to view metric valuesRunningExecution in progressWait for completion before querying

Task 4.1: List Scan Runs (ListDataQualityScanRuns)#

bash

aliyun dataworks-public list-data-quality-scan-runs --user-agent AlibabaCloud-Agent-Skills/alibabacloud-dataworks-data-quality [--region <REGION_ID> --endpoint dataworks.<REGION_ID>.aliyuncs.com] --project-id <PROJECT_ID> [--data-quality-scan-id <SCAN_ID>] [--status <Pass|Running|Error|Fail|Warn>] [--create-time-from <TIMESTAMP_MS>] [--create-time-to <TIMESTAMP_MS>] [--filter '{"TaskInstanceId":"<INSTANCE_ID>"}'] [--sort-by "CreateTime Desc"] [--page-number 1] [--page-size 20]

Filter quick reference:

ScenarioFilter JSON ExampleFilter by scheduling instance{"TaskInstanceId":"123456"}Filter by run number{"RunNumber":"2"}

How to interpret the result:

• PageInfo.DataQualityScanRuns[] should be shown as a table with Id, Status, CreateTime, FinishTime, and key runtime parameters
• Sort by recent time first so phrases like "most recent" map naturally to the first row
• Highlight Fail, Error, and Warn, then recommend drilling into GetDataQualityScanRun
• If the user asks for recent failures, combine Status=Fail with a converted time range instead of asking for timestamps

Task 4.2: Get Scan Run Details (GetDataQualityScanRun)#

bash

aliyun dataworks-public get-data-quality-scan-run --user-agent AlibabaCloud-Agent-Skills/alibabacloud-dataworks-data-quality [--region <REGION_ID> --endpoint dataworks.<REGION_ID>.aliyuncs.com] --id <SCAN_RUN_ID>

How to interpret the result:

• Status: state clearly whether the run passed, failed, warned, errored, or is still running
• Results: extract each rule's status, actual metric value, threshold, and whether it caused the overall failure; present this as a table instead of raw JSON
• Scan: use it as configuration snapshot context only when it helps explain the failure
• Parameters: mention runtime parameters when they may have influenced the result
• If any rule is abnormal, proactively suggest GetDataQualityScanRunLog

Task 4.3: Get Scan Run Log (GetDataQualityScanRunLog)#

bash

aliyun dataworks-public get-data-quality-scan-run-log --user-agent AlibabaCloud-Agent-Skills/alibabacloud-dataworks-data-quality [--region <REGION_ID> --endpoint dataworks.<REGION_ID>.aliyuncs.com] --id <SCAN_RUN_ID> [--offset <BYTE_OFFSET>]

How to interpret the result:

• Log is the raw execution trace; summarize the root cause first, then provide key excerpts if needed
• NextOffset = -1 means log retrieval is complete
• If NextOffset != -1, continue querying with the returned offset until completion when the user asks for the full log
• When logs are long, explain the main error path instead of pasting everything by default

---

Best Practices#

1. List before detail — Do not guess IDs. Use list queries first, then drill into a selected resource.
2. Diagnose failures in order — For Fail, check GetDataQualityScanRun results first, then read GetDataQualityScanRunLog.
3. Templates scope — ListDataQualityTemplates returns workspace custom templates only; ProjectId is required. Built-in templates must be viewed in the DataWorks console.
4. Use a bounded time window — For run-history queries, default to recent 24 hours or recent 10 rows to avoid oversized result sets.
5. Proactively guide the next step — After every query, suggest the most likely follow-up instead of waiting for the user to ask.
6. Expand Spec on demand — Spec is often verbose. Summarize first, expand only on request.

Query Result Guidance#

• Empty list result: Explain likely causes including wrong ProjectId, wrong region, or overly strict filters — suggest confirming parameters or relaxing filter conditions.
• Spec field handling: First extract monitored object, rule count, key thresholds, and trigger mode; expand full JSON only when the user requests it.
• Abnormal status handling: When encountering Fail / Error / Warn, do not just display the status — proactively provide the next diagnostic path.
• Results field handling: Present status, actual value, threshold, and conclusion per rule in a table — do not dump the raw array.

Common Errors#

Error CodeSolutionForbidden.Access / PermissionDeniedCheck RAM permissions, see references/ram-policies.mdInvalidParameterVerify parameter names, JSON shape, and required fieldsEntityNotExistsCheck whether the ID, ProjectId, and region match the target resourceInvalidPageSizePageSize must be within the API-supported range, usually 1-100

Region and Endpoint#

Common: cn-hangzhou, cn-shanghai, cn-beijing, cn-shenzhen. Endpoint format: dataworks.<REGION_ID>.aliyuncs.com

Full region and endpoint list: references/related-apis.md

Reference Links#

ReferenceDescriptionreferences/ram-policies.mdRAM permission configuration and policy examplesreferences/related-apis.mdAPI parameter details and Region Endpointsreferences/cli-installation-guide.mdAliyun CLI installation guide