ae-team

Original：🇺🇸 English

Translated

AE/TE/ThinkingEngine/ThinkingAI ae-cli manual for AI Agent Team tasks: managing teams (list, create, update, delete, AI-generate, templates) and executing TeamRuns (start, chat, cancel, reply, result, artifacts). Use when the user asks to find a team, run a team task, check run status, retrieve results or artifacts, or set up multi-agent workflows. Must use ae-cli, read the matching references/<command>.md before composing commands, and never guess team IDs, run IDs, config structures, or parameter formats.

2installs

Sourcethinkingaiagenticengine/ae-cli

Added on2026-08-13

NPX Install

npx skill4agent add thinkingaiagenticengine/ae-cli ae-team

SKILL.md Content

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ae-team

CRITICAL — Before running any
+<command>
command, you MUST first read the corresponding
references/<command>.md
. The reference filename equals the command name without the leading
+
, for example
+run-start
→
references/run-start.md
. CRITICAL — Never guess team IDs, run IDs, or config JSON structures. Always use
+list
or
+list-templates
to discover real resources first. CRITICAL — For the core Agent workflow (find → start → poll → artifacts), follow Workflow A in the Typical Workflows section below.

Global AE CLI Rules

AE CLI (

ae-cli

) is the command-line tool for the AE / TE / ThinkingEngine analysis platform.

Global parameters:

Parameter	Description
`--format <json\|table>`	Output format. Default is JSON.
`--jq <expr>`	jq filter expression for JSON output.
`--host <url>`	Override the active AE host. Available on every command and may be placed after the subcommand, e.g. `ae-cli team +<command> --host <url>` .
`--yes`	Skip confirmation for `high-risk-write` (delete) operations.
`--dry-run`	Show request details without executing.

Output and errors:

Successful commands return machine-readable JSON by default. Envelope may include optional
```
_notice.host_compat
```
.

Failed commands return

{ "ok": false, "error": { "type": "...", "message": "...", "hint": "..." } }

and exit non-zero.

CRITICAL — Host compat (do this first): If stderr or
```
_notice.host_compat
```
has a version warning, open the user reply with ⚠️ and quote
npm i -g
/
npx skills add
(or update-cluster) lines verbatim, then list projects/results. Never omit when summarizing. Soft tip;
```
ok: true
```
may still include the notice.

Safety constraints:

Read commands (

+list

,

+list-templates

,

+list-projects

,

+run-result

,

+run-artifacts

,

+ai-generate

) can execute directly once required IDs are known.

Ordinary
```
write
```
commands require explicit user intent but no CLI confirmation. Only
```
high-risk-write
```
commands use the confirmation gate and may receive
```
--yes
```
after explicit user authorization.
Never invent team IDs, run IDs,
```
agentId
```
values,
```
mcpServerIds
```
,
```
skillIds
```
,
```
knowledgeBaseIds
```
, project IDs, or any resource identifiers. Discover them with list commands or accept them from the user.

When to Use

Use

ae-team

for all AI Agent Team work:

Team management: list available teams, create/update/delete a team, generate a team config draft with AI, browse templates.
TeamRun execution: start a run, interact in chat mode, cancel a run, reply to a waiting run, poll result until completion, retrieve artifacts.

If the user's intent is data analysis, audience management, metadata governance, or DataOps, switch to

ae-analysis

/

ae-dataops

/

ae-engage

.

Command Format

bash

ae-cli team +<command> [options]

All commands live under the

team

service. Quick help:

bash

ae-cli team --help
ae-cli team +list --help
ae-cli team +run-start --help

Tool Groups (13)

Team Management (7)

```
+list
```
(doc) — list all visible teams
```
+create
```
(doc) — create a new team with a TeamConfig
```
+update
```
(doc) — patch one or more fields of an existing team
```
+delete
```
(doc) — delete a team (409 if runs are active)
```
+ai-generate
```
(doc) — AI-generate a team config draft from a goal description
```
+list-templates
```
(doc) — browse built-in team templates
```
+list-projects
```
(doc) — list projects available to the current user

TeamRun Execution (7)

```
+run-start
```
(doc) — start a new TeamRun
```
+run-watch
```
(doc) — stream a TeamRun via SSE (preferred over polling)
```
+run-chat
```
(doc) — chat with a team (multi-turn, auto-resume)
```
+run-cancel
```
(doc) — cancel a running TeamRun
```
+run-reply
```
(doc) — reply to a run in
```
waiting_user
```
state
```
+run-result
```
(doc) — get the full result of a TeamRun (fallback polling)
```
+run-artifacts
```
(doc) — list artifacts produced by a TeamRun

TeamRun Status Reference

Status	Description
`pending`	Queued, waiting to start
`running`	Actively executing
`waiting_user`	Paused — `+run-watch` exits with code 2; read `pendingQuestion` from stdout, present to user, then call `+run-reply`
`waiting_approval`	Paused — waiting for approval
`paused`	Manually paused
`completed`	Finished successfully
`failed`	Execution failed
`cancelled`	Cancelled by user

Terminal statuses:

completed

,

failed

,

cancelled

. Poll

+run-result

until one of these is reached.

Typical Workflows

Workflow A — Start an existing team and wait for results

bash

# 1. Discover available teams
ae-cli team +list

# 2. (Optional) Discover project IDs if needed
ae-cli team +list-projects

# 3. Start a run
ae-cli team +run-start --team-id <team_id> --input "分析上周用户留存数据"

# 4. Stream until done (blocks; no polling needed)
ae-cli team +run-watch --id <run_id>
# exit 0 → completed/partial_success → go to step 5
# exit 1 → failed/cancelled → inspect errorMessage in output, report to user
# exit 2 → waiting_user → go to step 4a

# 4a. Handle waiting_user: read pendingQuestion from stdout, get user's answer, reply, re-watch
ae-cli team +run-reply --id <run_id> --input "<user_answer>"
ae-cli team +run-watch --id <run_id>   # repeat until exit 0 or 1

# 5. Retrieve artifacts
ae-cli team +run-artifacts --id <run_id> --include-content true

Workflow B — AI-generate a config, then create and run

bash

# 1. Generate a draft config
ae-cli team +ai-generate --prompt "需要一个分析用户行为并自动生成留存报告的团队"

# 2. Create the team (paste / adjust the returned config)
ae-cli team +create --name "留存分析团队" --config '<config_json>'

# 3. Start a run
ae-cli team +run-start --team-id <new_team_id> --input "分析本月留存"

Workflow C — Multi-turn chat

bash

# First turn
ae-cli team +run-chat --team-id <team_id> --input "帮我分析DAU趋势"

# If run status is waiting_user, reply:
ae-cli team +run-reply --id <run_id> --input "请重点分析周末下降原因"

# Continue same session
ae-cli team +run-chat --team-id <team_id> --session-id <session_id> --input "给出优化建议"

Workflow D — Use a template to create a team

bash

# 1. Browse templates
ae-cli team +list-templates --locale zh

# 2. Create from a template's config
ae-cli team +create --name "我的分析团队" --config '<template_config>'

Quick Verification

bash

ae-cli team --help

ae-team

NPX Install

Tags

SKILL.md Content

ae-team

Global AE CLI Rules

When to Use

Command Format

Tool Groups (13)

Team Management (7)

TeamRun Execution (7)

TeamRun Status Reference

Typical Workflows

Workflow A — Start an existing team and wait for results

Workflow B — AI-generate a config, then create and run

Workflow C — Multi-turn chat

Workflow D — Use a template to create a team

Quick Verification