alicloud-observability-sls-log-query

cinience/alicloud-skills · updated Apr 8, 2026

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$npx skills add https://github.com/cinience/alicloud-skills --skill alicloud-observability-sls-log-query
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Category: service

skill.md

Category: service

SLS Log Query and Troubleshooting

Use SLS query|analysis syntax and Python SDK for log search, filtering, and analytics.

Prerequisites

  • Install SDK (virtual environment recommended to avoid PEP 668 restrictions):
python3 -m venv .venv
. .venv/bin/activate
python -m pip install -U aliyun-log-python-sdk
  • Configure environment variables:
    • ALIBABA_CLOUD_ACCESS_KEY_ID
    • ALIBABA_CLOUD_ACCESS_KEY_SECRET
    • SLS_ENDPOINT (e.g. cn-hangzhou.log.aliyuncs.com)
    • SLS_PROJECT
    • SLS_LOGSTORE(supports a single value or comma-separated values)

Query Composition

  • Query clause: filters logs (e.g. status:500).
  • Analysis clause: statistical aggregation, format query|analysis.
  • Example: * | SELECT status, count(*) AS pv GROUP BY status

See references/query-syntax.md for full syntax.

Quickstart (Python SDK)

import os
import time
from aliyun.log import LogClient, GetLogsRequest

client = LogClient(
    os.environ["SLS_ENDPOINT"],
    os.environ["ALIBABA_CLOUD_ACCESS_KEY_ID"],
    os.environ["ALIBABA_CLOUD_ACCESS_KEY_SECRET"],
)

project = os.environ["SLS_PROJECT"]
logstore = os.environ["SLS_LOGSTORE"]

query = "status:500"
start_time = int(time.time()) - 15 * 60
end_time = int(time.time())

request = GetLogsRequest(project, logstore, start_time, end_time, query=query)
response = client.get_logs(request)
for log in response.get_logs():
    print(log.contents)

Script quickstart

python skills/observability/sls/alicloud-observability-sls-log-query/scripts/query_logs.py \
  --query "status:500" \
  --last-minutes 15

Optional args: --project, --logstore(repeatable, or comma-separated values), --endpoint, --start, --end, --last-minutes, --limit, --parallel.

Troubleshooting script

python skills/observability/sls/alicloud-observability-sls-log-query/scripts/troubleshoot.py \
  --group-field status \
  --last-minutes 30 \
  --limit 20

Optional args: --error-query, --group-field, --limit, --logstore(repeatable, or comma-separated values), --parallel, plus the time range args above.

Workflow

  1. Ensure Logstore indexing is enabled (queries/analysis fail without index).
  2. Write query clause and append analysis clause when needed.
  3. Execute with SDK/script and inspect results.
  4. Control returned rows with limit; narrow time range when needed.

Validation

mkdir -p output/alicloud-observability-sls-log-query
for f in skills/observability/sls/alicloud-observability-sls-log-query/scripts/*.py; do
  python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/alicloud-observability-sls-log-query/validate.txt

Pass criteria: command exits 0 and output/alicloud-observability-sls-log-query/validate.txt is generated.

Output And Evidence

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

References

  • Syntax and examples:references/query-syntax.md

  • Python SDK initialization and queries:references/python-sdk.md

  • Troubleshooting templates:references/templates.md

  • Source list: references/sources.md

how to use alicloud-observability-sls-log-query

How to use alicloud-observability-sls-log-query on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add alicloud-observability-sls-log-query
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/cinience/alicloud-skills --skill alicloud-observability-sls-log-query

The skills CLI fetches alicloud-observability-sls-log-query from GitHub repository cinience/alicloud-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/alicloud-observability-sls-log-query

Reload or restart Cursor to activate alicloud-observability-sls-log-query. Access the skill through slash commands (e.g., /alicloud-observability-sls-log-query) or your agent's skill management interface.

Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

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

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate 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

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.748 reviews
  • Xiao Patel· Dec 24, 2024

    alicloud-observability-sls-log-query reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • William Flores· Dec 20, 2024

    alicloud-observability-sls-log-query has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Dec 8, 2024

    alicloud-observability-sls-log-query reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Neel Agarwal· Dec 8, 2024

    Useful defaults in alicloud-observability-sls-log-query — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Rahul Santra· Nov 27, 2024

    I recommend alicloud-observability-sls-log-query for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Michael Smith· Nov 27, 2024

    Registry listing for alicloud-observability-sls-log-query matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Luis Nasser· Nov 15, 2024

    I recommend alicloud-observability-sls-log-query for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Isabella Chen· Nov 11, 2024

    alicloud-observability-sls-log-query fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ava Iyer· Nov 3, 2024

    Keeps context tight: alicloud-observability-sls-log-query is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Henry Dixit· Oct 22, 2024

    alicloud-observability-sls-log-query is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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