← Back to Skills Marketplace
cinience

Aliyun Dlf Manage Next

by cinience · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
85
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install aliyun-dlf-manage-next
Description
Use when managing Alibaba Cloud Data Lake Formation (DlfNext) via OpenAPI/SDK, including the user needs DLF Next catalog/governance resource operations, incl...
README (SKILL.md)

Category: service

Data Lake Formation (Next)

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

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: DlfNext
  • Default API version: 2025-03-10
  • 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 \x3CProductCode> --version \x3CVersion>

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/aliyun-dlf-manage-next/

Validation

mkdir -p output/aliyun-dlf-manage-next
for f in skills/data-lake/aliyun-dlf-manage-next/scripts/*.py; do
  python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/aliyun-dlf-manage-next/validate.txt

Pass criteria: command exits 0 and output/aliyun-dlf-manage-next/validate.txt is generated.

Output And Evidence

  • Save artifacts, command outputs, and API response summaries under output/aliyun-dlf-manage-next/.
  • 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
Usage Guidance
This skill's purpose and code (fetching DlfNext OpenAPI metadata) look legitimate and benign, but the SKILL.md expects Alibaba Cloud access keys and a shared credentials file while the skill manifest declares none—an important mismatch. Before installing or enabling autonomous use: (1) Confirm whether the skill will need your ALICLOUD_ACCESS_KEY_ID and ALICLOUD_ACCESS_KEY_SECRET (and for which operations). (2) If you must provide credentials, use least-privilege keys and consider an isolated environment or temporary keys. (3) Ask the publisher to update the manifest to declare required env vars/primary credential and to clarify whether the agent will transmit artifacts externally. (4) Review/run the included script locally first to verify it only calls the documented api.aliyun.com endpoints. If you cannot get these clarifications, treat the skill with caution (do not supply long-lived or high-privilege credentials, and avoid enabling autonomous invocation).
Capability Analysis
Type: OpenClaw Skill Name: aliyun-dlf-manage-next Version: 1.0.0 The skill bundle is a legitimate tool for managing Alibaba Cloud Data Lake Formation (DlfNext) resources. The included script, scripts/list_openapi_meta_apis.py, safely fetches API metadata from official Alibaba Cloud endpoints (api.aliyun.com) to assist the agent in discovering available operations. There is no evidence of data exfiltration, credential theft, or malicious execution.
Capability Assessment
Purpose & Capability
Name/description (manage Alibaba Cloud DlfNext) match the included files and behavior: the script and SKILL.md focus on DlfNext OpenAPI discovery and API calls. Asking for Alibaba Cloud credentials would be appropriate for the stated purpose, but those credentials are not declared in the skill metadata/requirements — this is an inconsistency.
Instruction Scope
SKILL.md explicitly instructs the agent to use environment variables ALICLOUD_ACCESS_KEY_ID / ALICLOUD_ACCESS_KEY_SECRET / ALICLOUD_REGION_ID and/or the shared credentials file. The included Python helper only fetches public OpenAPI metadata, but the instructions also tell the agent to call SDK/OpenAPI Explorer to perform mutations and status checks. The manifest does not declare that these environment variables or credential file access are required, which is a scope/documentation mismatch.
Install Mechanism
This is instruction-only with a small Python script that fetches JSON from api.aliyun.com (an expected, documented Alibaba endpoint). There is no download-from-arbitrary-URL, no extract step, and no third-party package install specified.
Credentials
The SKILL.md asks for sensitive credentials (ALICLOUD_ACCESS_KEY_ID/SECRET and optional REGION or shared credentials file) but the skill registry metadata lists no required environment variables or primary credential. Requiring cloud access keys for a cloud-management skill is reasonable, but the omission from the manifest is a problem: users may not be warned what secrets the skill will use or expose to the agent runtime.
Persistence & Privilege
The skill does not request permanent/always-included privileges, has no install step that modifies other skills or system-wide settings, and uses the platform default for autonomous invocation. This is normal for an agent skill; combine with credential concerns before enabling autonomous runs.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install aliyun-dlf-manage-next
  3. After installation, invoke the skill by name or use /aliyun-dlf-manage-next
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of aliyun-dlf-manage-next - Provides management of Alibaba Cloud Data Lake Formation (DlfNext) via OpenAPI/SDK. - Supports catalog/governance resource operations, including listing, creating, updating, status checks, and troubleshooting metadata workflows. - Details priority for AccessKey sourcing and credentials configuration. - Includes quickstart scripts for OpenAPI metadata discovery. - Specifies output directory and validation methods for command execution and artifacts. - Prerequisites and reproducibility guidelines are documented.
Metadata
Slug aliyun-dlf-manage-next
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Aliyun Dlf Manage Next?

Use when managing Alibaba Cloud Data Lake Formation (DlfNext) via OpenAPI/SDK, including the user needs DLF Next catalog/governance resource operations, incl... It is an AI Agent Skill for Claude Code / OpenClaw, with 85 downloads so far.

How do I install Aliyun Dlf Manage Next?

Run "/install aliyun-dlf-manage-next" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Aliyun Dlf Manage Next free?

Yes, Aliyun Dlf Manage Next is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Aliyun Dlf Manage Next support?

Aliyun Dlf Manage Next is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Aliyun Dlf Manage Next?

It is built and maintained by cinience (@cinience); the current version is v1.0.0.

💬 Comments