Category: test
Works with
DataLake Minimal Viable Test
Prerequisites
AK/SK and region are configured.
GoalsSkill: skills/data-lake/alicloud-data-lake-dlf/ 。
Test Steps
Run python scripts/list_openapi_meta_apis.py .
Select one read-only API and run a minimal request.
Save outputs under output/alicloud-data-lake-dlf-test/ 。
Expected Results
Metadata retrieval succeeds.
No content available.
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionalicloud-data-lake-dlf-testExecute the skills CLI command in your project's root directory to begin installation:
Fetches alicloud-data-lake-dlf-test from cinience/alicloud-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate alicloud-data-lake-dlf-test. Access via /alicloud-data-lake-dlf-test in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Read-only API returns success or an explicit permission error.
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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I recommend alicloud-data-lake-dlf-test for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
alicloud-data-lake-dlf-test fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for alicloud-data-lake-dlf-test matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: alicloud-data-lake-dlf-test is the kind of skill you can hand to a new teammate without a long onboarding doc.
Useful defaults in alicloud-data-lake-dlf-test — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added alicloud-data-lake-dlf-test from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for alicloud-data-lake-dlf-test matched our evaluation — installs cleanly and behaves as described in the markdown.
alicloud-data-lake-dlf-test reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend alicloud-data-lake-dlf-test for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
alicloud-data-lake-dlf-test is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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