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alicloud-ai-chatbot

alicloud-ai-chatbot

github.com/cinienceCloud & DevOps396279 installsUpdated 11w ago
Repository

About alicloud-ai-chatbot

A skill for managing Alibaba Cloud Chatbot (beebot) resources through OpenAPI. It uses API discovery and list, change, and status-check workflows to support resource administration and troubleshooting.

Key features

  1. 01Manage beebot resources through OpenAPI
  2. 02Discover API operations and parameters
  3. 03List and inspect resources
  4. 04Create or update configuration
  5. 05Query status for troubleshooting

Use cases

  1. 01Discover available Chatbot APIs
  2. 02Review current Chatbot resources
  3. 03Change resource configuration
  4. 04Check service status during troubleshooting

MCP support

The input does not describe MCP integration or expose an MCP interface.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/cinience/alicloud-skills --skill alicloud-ai-chatbot

After installing, type/alicloud-ai-chatbotin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

agents/
openai.yaml
references/
sources.md
scripts/
list_openapi_meta_apis.py

Details

From the project README

Category: service

Chatbot (beebot)

Use Alibaba Cloud OpenAPI (RPC) with official SDKs or OpenAPI Explorer to manage resources for beebot.

Workflow

  1. Confirm region, resource identifiers, and desired action.
  2. Discover API list and required parameters (see references).
  3. Call API with SDK or OpenAPI Explorer.
  4. Verify results with describe/list APIs.

AccessKey priority (must follow)

  1. Environment variables: ALICLOUD_ACCESS_KEY_ID / ALICLOUD_ACCESS_KEY_SECRET / ALICLOUD_REGION_ID Region policy: ALICLOUD_REGION_ID is an optional default. If unset, decide the most reasonable region for the task; if unclear, ask the user.
  2. Shared config file: ~/.alibabacloud/credentials

API discovery

  • Product code: Chatbot
  • Default API version: 2022-04-08
  • Use OpenAPI metadata endpoints to list APIs and get schemas (see references).

High-frequency operation patterns

  1. Inventory/list: prefer List* / Describe* APIs to get current resources.
  2. Change/configure: prefer Create* / Update* / Modify* / Set* APIs for mutations.
  3. Status/troubleshoot: prefer Get* / Query* / Describe*Status APIs for diagnosis.

Minimal executable quickstart

Use metadata-first discovery before calling business APIs:

python scripts/list_openapi_meta_apis.py

Optional overrides:

python scripts/list_openapi_meta_apis.py --product-code <ProductCode> --version <Version>

The script writes API inventory artifacts under the skill output directory.

Output policy

If you need to save responses or generated artifacts, write them under: output/alicloud-ai-chatbot/

Validation

mkdir -p output/alicloud-ai-chatbot
for f in skills/ai/service/alicloud-ai-chatbot/scripts/*.py; do
  python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/alicloud-ai-chatbot/validate.txt

Pass criteria: command exits 0 and output/alicloud-ai-chatbot/validate.txt is generated.

Output And Evidence

  • Save artifacts, command outputs, and API response summaries under output/alicloud-ai-chatbot/.
  • Include key parameters (region/resource id/time range) in evidence files for reproducibility.

Prerequisites

  • Configure least-privilege Alibaba Cloud credentials before execution.
  • Prefer environment variables: ALICLOUD_ACCESS_KEY_ID, ALICLOUD_ACCESS_KEY_SECRET, optional ALICLOUD_REGION_ID.
  • If region is unclear, ask the user before running mutating operations.

References

  • Sources: references/sources.md

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