Como usar
- Copie o comando e verifique o pacote antes de instalar no seu ambiente de agente.
- Consulte no original as ferramentas, credenciais e ambientes necessários.
- Descreva os dados de entrada e a entrega esperada; confira a saída com as fontes.
npx skills add https://github.com/thinkingaiagenticengine/ae-cli --skill ae-teamAntes de começar
- A instalação não inclui assinatura de modelo, franquia API ou acesso aos seus arquivos.
- Estrelas e instalações indicam atividade, não um teste independente de qualidade ou segurança.
Documento original do Skill
Renderizado do repositório de origem, preservando títulos, exemplos, código, tabelas, links e imagens.
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+listor+list-templatesto 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 (Agentic Engine) 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_compathas 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: truemay 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
writecommands require explicit user intent but no CLI confirmation. Onlyhigh-risk-writecommands use the confirmation gate and may receive--yesafter explicit user authorization. - Never invent team IDs, run IDs,
agentIdvalues,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 --helpTool 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 inwaiting_userstate+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 trueWorkflow 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
