/alibabacloud-bailian-managed-agent

name: alibabacloud-bailian-managed-agent
description: |-
  Version v20261015 (date-based release, YYYYMMDD).
  Explain, evaluate, demonstrate, provision, and integrate Alibaba Cloud Bailian
  Managed Agent (CMA / ManagedAgents). Use for Bailian Managed Agent product selection,
  sales pitches, customer solutions, hands-on PoCs, scheduled report agents, managed
  environments, and Python/Java backend integration. Prefer Bailian CLI (bl) for
  quick trials and resource provisioning; use HTTP API or verified SDKs for customer
  system integration, and API fallback when CLI capability remains unavailable after
  an update attempt. Not for generic agent development or unrelated cloud sandboxes.

Bailian Managed Agent Assistant (know the product / recommend / hands-on / deliver / integrate)

This skill is the Bailian Managed Agent knowledge and operations entry point for **sales recommendation**, **pre-sales solutioning**, and **developer integration**. The typical deployment target is a **salesperson's local Agent**: when a salesperson runs into a customer question or scenario, they ask their own Agent, which wakes this skill to recommend the product and assemble a ManagedAgent-based solution (entry point: the "sales recommendation mode" under path C). Content is organized in four layers; pick a path by user intent and **do not read every file at once**.

Before use: check for a newer skill release

At the start of each invocation, before following a product workflow, resolve `SKILL_ROOT` to this skill's installed directory and run:

python3 "$SKILL_ROOT/scripts/check_for_updates.py"

The helper GETs `https://skills.aliyun.com/api/public/skills/alibabacloud-bailian-managed-agent`, reads the `vYYYYMMDD` version from `data.content`'s frontmatter description, and compares it with the local description and [manifest](references/manifest.json). This default check only reports versions; it does not download or replace the installed skill.

On `update_available`, report the local and remote versions, explain that keeping the current version may leave the skill's knowledge outdated, and ask whether the user wants to update. Only run `--apply` after explicit user approval (reuse approval already given for this update); invoking the skill is not approval to update it. If the user declines or has not answered, retain the current version and continue their task. Do not make updating a prerequisite or repeatedly ask about the same release in the conversation. If the local version is newer, report the difference and keep it; do not downgrade.

Run the initial check once per invocation, not per tool call. Reuse the returned `user_agent` for the invocation's cloud requests and any approved update. On `updated`, reread the installed `SKILL.md` and needed references without recursively checking again; tell the user the old/new versions and backup path, and recommend a new conversation to refresh the host's cached skill description. Do not restart or end the conversation automatically. On a check/update failure or missing remote date version, report that briefly and continue the user's task with the existing copy. A Git checkout is check-only and must not be overwritten by the installer. Commands, result handling, and release rules: [skill updates](references/workflows/skill-updates.md).

Required versioned User-Agent

Before any Alibaba Cloud API call, initialize the per-invocation UA as described in [references/workflows/user-agent.md](references/workflows/user-agent.md), reusing the update helper's `user_agent` if it already ran in this invocation. Read the non-empty `version` from [references/manifest.json](references/manifest.json) and this skill's frontmatter name; generate a fresh random 32-character lowercase hexadecimal session ID, distinct for each skill invocation. Reuse it within that invocation only.

Required curl declaration (substitute all placeholders at runtime):

--user-agent "AlibabaCloud-Agent-Skills/{frontmatter-name}/{session-id} skill-version/{skill-version}"

Propagate that complete value to every CLI/SDK/HTTP/Terraform cloud request, including retries and streams. Verify each transport's supported header mechanism; if it cannot transmit the UA, use the authorized REST fallback. Do not invent CLI flags or assume exporting a variable sets headers. These rules also apply to the abbreviated examples in references.

RAM and workspace permissions

Before provisioning or diagnosing authorization failures, read [references/ram-policies.md](references/ram-policies.md). It separates RAM system policies, workspace membership, and MA bearer-key scope. Do not invent per-endpoint RAM actions or assume a read-only RAM policy restricts an existing workspace API key.

Choose CLI or API before execution

| Intent | Execution path | | --- | --- | | Quick experience, demo, one-off resource creation or session run | Prefer `bl`; inspect the installed version and relevant `--help`, then use supported commands or IaC. | | Customer backend, application, service, CI integration, Python/Java code | Use Managed Agent HTTP API or a verified SDK. Do not shell out to `bl` from business code. Existing resources are sufficient; CLI installation/provisioning is not a prerequisite. | | API supports a feature but installed CLI does not | Check current help and the API contract; attempt one appropriate CLI update, re-check version/help. If update fails or support is still absent, use the API. A CLI gap is not a product limitation. | | User explicitly selects CLI or API | Respect that selection. Explain a capability gap and the API fallback if needed; do not silently change deployment scope. |

Read [references/workflows/cli-api-routing.md](references/workflows/cli-api-routing.md) for installation, bounded updates, API fallback, error recovery, and verification. Official installation source: https://bailian.aliyun.com/cli/install.md. Tutorial and cookbook curl examples describ