
ae-dataops
Use ae-cli for DataOps warehouse tables/views and fields, recycling, workflow configuration and release, execution troubleshooting, backfill, SQL queries, and data integration.
- Installs
- 870
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/thinkingaiagenticengine/ae-cli --skill ae-dataops- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads ae-dataops automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
ae-dataops
Cross-skill collaboration
When remaining work is outside this skill's scope, or a necessary prerequisite needs another capability, follow the collaboration protocol. Choose from the skills available in this run by capability, preserve verified context, and continue the remaining task. Reuse this protocol if already loaded.
CRITICAL - This skill is self-contained. Use the Global AE CLI Rules below; do not require a separate shared skill for DataOps-side tasks.
Start with the user's intended outcome, then read only the matching reference below. These are files in this skill, not separately installed skills. Use the installed command's --help for exact flags; if it differs from this reference, report the version mismatch instead of inventing aliases.
Global AE CLI Rules
Use ae-cli and these references for DataOps tasks. Preserve an explicitly selected host and space across a workflow.
Global parameters:
| Parameter | Description |
|---|---|
--format <json|table> | Output format. Default is JSON. |
--jq <expr> | jq over the command payload before wrapping; use .flowInstance.status, not .data.flowInstance.status. External jq over default CLI JSON includes .data. |
--host <url> | Override the active AE host. Available on every command and may be placed after the subcommand, e.g. ae-cli dataops_ide +<command> --host <url>. |
Output and errors:
- JSON results use an outer
okanddata; command errors useok:falsewitherror.type/message/hinton stderr and exit non-zero. Inspect both streams. ok:trueis not a business completion check. Legacy commands can returnREJECTED,FAILED, orCHECK_FAILEDinsidedata. Check the specific result fields described by the reference before proceeding. Reading a failed task's status successfully is different from successfully executing that task.- For asynchronous work, preserve the returned ID and query that same operation. Submission is not completion; do not submit again because it is still running. Use bounded polling with backoff; when the wait budget is exhausted, report the ID and current state rather than claiming success or restarting work.
- For an actual
_notice.host_compator explicit version-compatibility warning, briefly report it and quote the supplied upgrade commands accurately. Unrelated stderr output is not a version warning.
Preview semantics:
- Table-field mutations and entity recycle/delete use server semantic
--dry-run; inspect the returned blockers and planned changes. - Other current DataOps
--dry-runimplementations show a local request only. They do not validate server permissions, connections, SQL, or business state. For flow release differences use+preview_release_flow. - Current DataOps commands do not implement the global
--validateserver check. Do not treat its informational response as successful validation.
Safety constraints:
- Read commands can execute directly after required IDs and references are verified.
- Ordinary
writecommands execute without--yes; use--yesonly for ahigh-risk-writecommand after explicit user confirmation. - Reuse trusted IDs and context already provided; otherwise discover the exact resource using the matching reference. Refine searches or paginate when truncated; an incomplete list cannot prove absence. Ask only when the target or a consequential choice remains ambiguous.
- For existing resources, never invent IDs, fields, or parameter values. For creation, a new name is expected: use the requested name or propose one, check collisions, and do not mistake its absence for a blocker.
- Stop at the requested outcome: saving DEV does not authorize release, release does not authorize a manual run, and recycling does not authorize permanent deletion. Do not substitute a broader operation for an unsupported narrower request.
Domains for DataOps: dataops_repo, dataops_datatable, dataops_flow, dataops_operations, dataops_ide, dataops_integration
Core Concepts and Rules
You must understand the following key concepts before use, otherwise errors are highly likely.
Environment and Defaults
| Scenario | Default Environment | Description |
|---|---|---|
| Table creation/field edits and workflow definitions | DEV | Release separately when requested |
dataops_datatable +entity_recycle / +recycle_bin_delete | Existing DEV and PRODUCT mappings | Entity lifecycle operations; not DEV-only edits awaiting release |
| Manual flow execution, operations and backfill | PROD | Inspect the exact flow/job/instance |
| SQL query | Determined by the SQL's discovered tables | Do not choose DEV or PROD solely from a sample query |
Responsibility Boundaries
| Operation | Correct Tool | Prohibited |
|---|---|---|
| Execute SELECT queries | dataops_ide | — |
| Create tables/views or mutate table fields | dataops_datatable | dataops_ide |
| Recycle or permanently delete a table/view | dataops_datatable +entity_recycle / +recycle_bin_delete | dataops_ide |
Flow Lifecycle
Create DEV Flow → Configure Parameters/Tasks/Dependencies/Schedule → Preview and Release to PROD when requested → Manual Execution / Operations Troubleshooting when requested
Custom flow parameters: use +get_flow_params, +create_flow_param, +update_flow_param, and +delete_flow_param in dataops_flow; see the flow reference. Writes configure DEV definitions and may stop DEV debug executions. Value, type, name, and deletion changes require release for PROD; a remark update without renaming also synchronizes an existing PROD parameter remark.
Backfill lifecycle: Discover eligible PROD flow → Create or fully update DRAFT job → Run explicitly → Search / inspect plans → Stop or rerun the complete job; delete only after target inspection
Scenario Routing
| User intent | Command group | Reference | Completion boundary |
|---|---|---|---|
| Discover or select a space | dataops_repo | Space discovery | Resolve the intended spaceCode; reuse trusted context |
| Create tables/views or change a field type/comment | dataops_datatable | Table workflows | Verify DEV state; publish only when requested |
| Delete a table/view; inspect or empty one recycle-bin entry | dataops_datatable | Entity lifecycle | Ordinary deletion stops at recycling; permanent deletion needs separate authorization |
| Create/configure a flow; add/update/delete tasks and parameters; schedule or release | dataops_flow | Flow configuration | Read back the requested DEV or PROD definition; do not add a manual run |
| Execute, inspect, or stop a run; troubleshoot failed work | dataops_flow, dataops_operations | Execution and monitoring | Match the exact instance; whole-flow execution is not failed-node retry |
| Fill multiple historical business dates | dataops_operations | Backfill jobs | Draft creation, job start, and completed plans are different outcomes |
| Create/test a datasource or configure/run a sync | dataops_integration | Data integration | Verify saved config or the exact run, according to the request |
| Schedule a sync and publish it without running now | dataops_integration, dataops_flow | Data integration, then Flow configuration | Confirm the PROD node and schedule; no manual execution |
| Browse schemas/tables or answer a data question | dataops_datatable, dataops_ide | Query workflow | Read the actual result and answer the question, not merely return a download task ID |
1. Space Discovery
dataops_repo exposes only one read command. Use it to discover a valid spaceCode before calling DataOps commands that require one. It returns createTime, spaceCode, and spaceDisplayName.
- If the user already provided a trusted
spaceCode, reuse it. - If
spaceCodeis unknown, run+list_spacesfirst. - If exactly one space is returned, use its
spaceCode. - If multiple spaces are returned and the user intent does not identify one, ask the user which space to use. Do not guess.
# List spaces accessible to the current user
ae-cli dataops_repo +list_spaces
2. Data Table and View Management
Detailed workflow, command flags, examples, and parameter notes live in references/dataops-table.md.
Key constraints:
- Start with
dataops_datatable +dict_search_tablesfor visible DataOps catalog discovery. - Use
dataops_ide +search_tablesonly for raw engine metadata, anddataops_ide +ide_list_tablesonly for known catalog/schema browsing. - Create tables/views with
dataops_datatable, notdataops_ide; creation is DEV-only. Use+publish_entitywhen publication is requested. - Add, modify, or delete one ordinary table field at a time in DEV; preview first, never mutate partition fields, and publish PROD separately.
- An ordinary "delete table/view" request means recycle only with
dataops_datatable +entity_recycle. Permanent deletion is a separate workflow using+recycle_bin_listand+recycle_bin_delete; read the table reference before either workflow. Both writes affect DEV and PRODUCT and require an exact entity ID plus name, semantic--dry-run, and explicit confirmation before--yes. Never automatically delete an old same-name recycled entity to bypassRECYCLE_NAME_CONFLICT. - After confirmed actual recycling, the Agent may ask whether to permanently delete the entity, warning that this is irreversible and may delete internal table data. Stop until a new explicit confirmation. This is an Agent reply, not a CLI prompt or JSON field. A preview,
FAILED,PARTIAL, or unverified state must not trigger this offer; reconcile the same entity ID first. - DDL follows Trino syntax; current-space view DDL should keep the literal
${env}placeholder.
3. Flow Orchestration
Flow references cover creation and configuration, execution and monitoring, and backfill jobs.
Lifecycle: DEV configuration → Requested release → Requested execution or troubleshooting. Stop at the user's boundary.
Detailed creation/configuration commands live in references/dataops-flow-create.md. Detailed execution, monitoring, operation instance, task log, and stop commands live in references/dataops-flow-monitor.md. Persistent multi-date backfill jobs live in references/dataops-backfill.md.
Key constraints:
- Create and update tasks in DEV, preview/release before PROD execution.
- Use
+get_flow_overviewfor customflowParamsand each task'sdag.tasks[].taskParams; DEV is the default, PROD is supported, and both requiredwWorkflowEdit. Definitions preserve expression text and code-parsed references whose source/value fields are null or omitted. - Instance details require
dwOMInstanceView; inspect historical values inflowInstance.instanceParamMapor tasklog.paramswith--includeLog true. - Treat
+delete_taskas high-risk: verify the target with+get_flow_overview, preview with--dry-run, and use--yesonly after explicit user confirmation. Deletion affects DEV; release the flow to apply it to PROD. +execute_flowalways runs PROD; it returnsexecuteIdfor early stop.- Prefer
flowInstanceIdfrom operations search for stable inspection and troubleshooting. - A backfill job is persistent and batches multiple base dates; do not emulate it by looping
+execute_flow. - Create a draft with
+create_backfill_joband run it as a separate step.+rerun_backfill_jobreruns the complete job, not only failed plans. +update_backfill_jobreplaces a DRAFT job's complete configuration; inspect the job first and do not treat it as a partial patch. Treat+delete_backfill_jobas high-risk and preview it with--dry-runbefore confirmation.- Reference flow or workspace parameters in task SQL as
${paramKey}. Inspect parameter sources in the overview before release.
4. IDE SQL Queries
Detailed metadata browsing, SQL query, async download, and cancel workflows live in references/dataops-query.md.
Key constraints:
- IDE is query-only; create/modify tables and recycle/delete entities with
dataops_datatable. - Prefer
dataops_datatable +dict_search_tablesfor table discovery unless raw engine metadata or schema browsing is required. - Submit exactly one read-only SQL query. It creates a platform-bounded download task; rows are not returned inline and the result is not an unlimited or full export.
5. Data Integration
Detailed datasource, metadata browsing, sync solution, execution, and monitoring workflows live in references/dataops-integration.md.
Key constraints:
- Generate
sourceConfig,sinkConfig,channelConfig, andfieldsMappingfrom the reference templates; do not invent keys. - MySQL Source read partitioning uses
sourceConfig.splitColumn;fieldsMapping.shardingKeyis column metadata and must not be used for it. +save_sync_solutionis not a partial patch. Current+get_sync_detail --withParams truereturns a summary plus used parameters, not complete editable configs. Do not reconstruct missing settings from it; see the integration reference's update boundary.syncNameis accepted for compatibility but ignored.- Preset repository sync uses
te_etl@TASK_ENGINE_TRINO; the server supplies gateway routing from the selected space. Do not copy sample company or space IDs into configuration. - Use
+list_sync_runsto gettaskIdbefore stopping a running sync.
Reference Documentation
For detailed command flags and usage, please refer to the command documentation in the references/ directory.
FAQ
What does the ae-dataops skill do?
Use ae-cli for DataOps warehouse tables/views and fields, recycling, workflow configuration and release, execution troubleshooting, backfill, SQL queries, and data integration.
How do I install ae-dataops?
Run npx skills add https://github.com/thinkingaiagenticengine/ae-cli --skill ae-dataops in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/ae-dataops/ (personal) or .claude/skills/ae-dataops/ (project).
Which AI agents can use ae-dataops?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is ae-dataops safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains ae-dataops?
It is published by thinkingaiagenticengine in thinkingaiagenticengine/ae-cli. It has 870 recorded installs.
More from thinkingaiagenticengine/ae-cli
ae-analysis
thinkingaiagenticengine/ae-cli
Use ae-cli for AE analysis-side data questions, asset operations, and asset governance: reports, analysis boards, BI dashboards, ad-hoc models, drilldown, detail data, alerts, clusters, tags, metrics, metadata discovery, project configuration, tracking plans, local input-file upload, governance asset lists/rules/lineage/impact/dependency, batch asset operations, projects, and resource links. Use when the user asks to query data, explain a change, export evidence, inspect/create/update/govern analysis assets, recommend project assets for certification/authentication, review asset-certification recommendations, review metric recommendations, or build/update/refresh/sync a project semantic knowledge base from a governed asset package.
ae-engage
thinkingaiagenticengine/ae-cli
AE Engage capability gateway: config center, flows, push/config channels, strategies, templates, task management, operation activities, and query lifecycle. Trigger words: config center, scene config, push channel, config channel, operation strategy, operation task, operation activity, query lifecycle, template, config item, Engage, Hermes, engage-scene, engage-setting, engage-flow, engage-task, engage-activity, engage-query.
ae-community
thinkingaiagenticengine/ae-cli
AE community analysis and data reporting for posts, comments, topics, livestreams, customer-service chats, WeCom after-sales groups, and in-game chat. Use for community content insight, sentiment, intent, evidence drill-down, community data ingestion/import/submission, and WeCom chat data integration (社区数据上报、导入、提交社区数据、企微聊天数据接入).
ae-agent
thinkingaiagenticengine/ae-cli
AE Agent platform CLI for Agent, resource package import and export, notification, approval, archived conversation, model, MCP, Skill, attachment, and user-memory work. Use when managing these resources, browsing Agent markets, handling approval requests and tasks, restoring archived conversations, persisting user memory, or answering from user preferences, background, stable workflows, or historical conventions.
ae-kb
thinkingaiagenticengine/ae-cli
AE knowledge base CLI manual for creating, importing read-only compiled snapshots, querying, LLM-powered ask, listing accessible knowledge bases and their sources, deterministic index/grep/read retrieval, checking status, ZIP source upload and directory management, raw child-file reading, revision-checked child updates and deletion, compiling, schema generation, URL sources, source deletion, ordinary text source creation, full reads and revision-checked editing, file/ZIP source draft replacement and restoration, and knowledge base deletion. Use when the user asks to manage AE (Agentic Engine) knowledge bases, import a compiled Markdown ZIP snapshot, upload documents or URLs to a knowledge base, query knowledge, ask knowledge bases with an LLM, list accessible knowledge bases or source metadata, inspect knowledge base indexes, search knowledge base pages, read a specific knowledge base page, check knowledge base status, generate schemas, compile knowledge, remove sources, create or edit
cli-self-check
thinkingaiagenticengine/ae-cli
检测新合并到 te-cli 的 CLI 功能是否合理。从命令注册、业务域↔skill 配对、skill 文档覆盖、skill 内部一致性、用户文档同步、工程健壮性六个维度扫描,定位会导致命令加载失败、AI agent 读空文档瞎猜参数、用户文档滞后等问题。当合并了新命令域/命令、新增或修改 skill、做发版前自检、或需要评估 CLI 功能完整性时使用。
Popular data & databases skills
supabase-postgres-best-practices
supabase/agent-skills
Postgres best practices maintained by Supabase, for Postgres running anywhere. Load this skill BEFORE writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and the tests that verify them, indexes, triggers, database functions, queues and scheduled jobs (pgcron, pgmq), vector/semantic search (pgvector), and restoring dumps (pgrestore) or importing data. Also load it when diagnosing slow queries, high CPU, timeouts, EXPLAIN plans, connection exhaustion, locking, bloat, or rows visible to the wrong user or tenant. This is not just a performance guide — schema, migration, security, and SQL authoring tasks need these rules too, even for a one-column change or a single query.
prisma-client-api
prisma/skills
Prisma Client API reference covering model queries, filters, operators, and client methods. Use when writing database queries, using CRUD operations, filtering data, or configuring Prisma Client. Triggers on "prisma query", "findMany", "create", "update", "delete", "$transaction".
prisma-database-setup
prisma/skills
Deprecated compatibility name for prisma-orm-setup. Use only when a user or existing integration explicitly invokes prisma-database-setup; otherwise select prisma-orm-setup.
prisma-cli
prisma/skills
Prisma ORM 7 CLI reference for existing Prisma 7 applications or explicitly selected Prisma 7 workflows. Covers prisma init, generate, migrate, db, dev, studio, and mcp. For setup, connection repair, or Prisma 8, use prisma-orm-setup; not the Prisma Platform CLI.
prisma-postgres
prisma/skills
Deprecated compatibility name for prisma-postgres-setup. Use only when a user or existing integration explicitly invokes prisma-postgres; otherwise select prisma-postgres-setup.
prisma-driver-adapter-implementation
prisma/skills
Required reference for Prisma ORM 7 SQL driver adapter work. Use when implementing or modifying adapters, adding database drivers, or touching SqlDriverAdapter, Transaction, savepoint, result mapping, or DriverAdapterError behavior. Covers current transaction lifecycle, optional savepoint hooks, original database-error preservation, and verification.