Fetches alicloud-network-esa from cinience/alicloud-skills and configures it for Cursor.
3
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/alicloud-network-esa
Restart Cursor to activate alicloud-network-esa. Access via /alicloud-network-esa in your agent's command palette.
⚠
Security Notice
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.
ESA OpenAPI is RPC style; prefer SDK or OpenAPI Explorer to avoid manual signing.
SDK quickstart
from alibabacloud_esa20240910.client import Client as Esa20240910Client
from alibabacloud_esa20240910 import models as esa_models
from alibabacloud_tea_openapi import models as open_api_models
defcreate_client(region_id:str="cn-hangzhou")-> Esa20240910Client: config = open_api_models.Config( region_id=region_id, endpoint="esa.cn-hangzhou.aliyuncs.com",)return Esa20240910Client(config)
Pages — Edge Page Deployment
Pages is a quick deployment flow based on Edge Routine, deploying HTML or static directories to the edge.
CreateRoutine → CreateRoutineWithAssetsCodeVersion → Package zip and upload to OSS
→ Poll GetRoutineCodeVersionInfo(wait for available)
→ CreateRoutineCodeDeployment(staging) → CreateRoutineCodeDeployment(production)
→ GetRoutine(get access URL)
Zip Package Structure
The zip package structure depends on EDGE_ROUTINE_TYPE (automatically determined by checkEdgeRoutineType based on whether entry file and assets directory exist):
JS_ONLY: routine/index.js (bundled with esbuild or --no-bundle to read source files directly)
ASSETS_ONLY: All static files under assets/, maintaining original directory structure
Use Python SDK to manage ESA sites, DNS records, cache rules, etc.
API behavior notes
Most list APIs support pagination via PageNumber + PageSize.
ListSites returns sites across all regions; no need to iterate regions.
Newly created sites start as pending; complete access verification via VerifySite to activate.
Deleting a site removes all associated configuration.
UpdateSiteAccessType can switch between CNAME and NS, but switching to CNAME may fail if incompatible DNS records exist.
DNS record APIs (CreateRecord, ListRecords, etc.) work for both NS and CNAME connected sites. CNAME sites are limited to CNAME and A/AAAA types only, and records cannot disable acceleration (proxy must stay enabled).
DNS record Type parameter must be exact: use A/AAAA (not A), CNAME, MX, TXT, NS, SRV, CAA.
CreateCacheRule supports two config types: global (site-wide default) and rule (conditional rule with match expression).
Workflow
Confirm target site ID, access type (CNAME/NS), and desired action.
Find API group and exact operation name in references/api_overview.md.
Call API with Python SDK (preferred) or OpenAPI Explorer.
Verify results with describe/list APIs.
If you need repeatable inventory or summaries, use scripts/ and write outputs under output/alicloud-network-esa/.
SDK priority
Python SDK (preferred)
OpenAPI Explorer
Other SDKs (only if Python is not feasible)
Python SDK scripts (recommended for inventory)
List all ESA sites: scripts/list_sites.py
Summarize sites by plan: scripts/summary_sites_by_plan.py
Check site status: scripts/check_site_status.py
List DNS records for a site: scripts/list_dns_records.py
Analytics — Traffic Analysis
Query and analyze ESA site traffic data using DescribeSiteTimeSeriesData and DescribeSiteTopData APIs.
Core Features
Time-Series Data: Query traffic trends with configurable time granularity
Top-N Rankings: Get rankings by country/IP/host/path/status code dimensions
# Match file extension--Rule'(http.request.uri.path.extension eq "html")'# Match multiple extensions--Rule'(http.request.uri.path.extension in {"js" "css" "png" "jpg"})'# Match URL prefix--Rule'(starts_with(http.request.uri, "/api/"))'# Match URL suffix
Implementation Guide
Prerequisites
›Claude Desktop or compatible AI client with skill support
›Clear understanding of task or problem to solve
›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
1Install skill using provided installation command
2Test with simple use case relevant to your work
3Evaluate output quality and relevance
4Iterate on prompts to improve results
5Integrate into regular workflow if valuable
Common Pitfalls
⚠Expecting perfect results without iteration
⚠Not providing enough context in prompts
⚠Using skill for tasks outside its intended scope
⚠Accepting outputs without review and validation
Best Practices
✓ Do
+Start with clear, specific prompts
+Provide relevant context and constraints
+Review and refine all outputs before using
+Iterate to improve output quality
+Document successful prompt patterns
✗ Don't
−Don't use without understanding skill limitations
−Don't skip validation of outputs
−Don't share sensitive information in prompts
−Don't expect skill to replace human judgment
💡 Pro Tips
★Be specific about desired format and style
★Ask for multiple options to choose from
★Request explanations to understand reasoning
★Combine AI efficiency with human expertise
When to Use This
✓ 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.
Learning Path
1Familiarize yourself with skill capabilities and limitations
2Start with low-risk, non-critical tasks
3Progress to more complex and valuable use cases
4Build expertise through regular use and experimentation
