Community藝術與設計github.com

aws-samples/sample-code-for-devops-agent-skills

Open-source skills for AWS DevOps Agent - extend DevOps Agent with ready-to-use skills for incident response, root cause analysis, and operational troubleshooting. Use as-is or as a reference for writing your own skills.

相容平台~Claude Code~Codex CLI~Cursor
npx skills add aws-samples/sample-code-for-devops-agent-skills

Ask in your favorite AI

Open a new chat with this agent skill pre-loaded.

說明文件

Support Case Review

Use this skill when investigating an incident and you need to review AWS Support cases — either the current case associated with the incident or historical cases that may contain relevant context, similar symptoms, or proven remediation steps.

When to Use This Skill

  • An active incident shares symptoms with previously resolved issues.
  • You need to check if a similar support case was filed in the past 24 months.
  • You want to correlate the current incident with known AWS service events.
  • You need to retrieve communications and resolution details from a prior case.
  • You want to identify recurring patterns across multiple support cases.

Prerequisites

  • The AWS account must have a Business Support+, Enterprise Support, or Unified Operations plan (required for the AWS Support API).
  • The agent must have permissions to call support:DescribeCases and support:DescribeCommunications in the target account.
  • Support case data is available for 24 months after creation. Cases older than 24 months cannot be retrieved via the API.

Step 1: Identify the Current Incident Context

Before searching support cases, gather key details from the current incident:

  1. Affected AWS services (e.g., EC2, RDS, Lambda, ELB).
  2. Error messages or error codes observed in logs or alarms.
  3. Timeframe of the incident (start time, duration).
  4. Affected resources (instance IDs, ARNs, endpoint names).
  5. Symptoms (latency spikes, 5xx errors, connection timeouts, throttling).

Use these details as search criteria when filtering support cases.


Step 2: Search for Related Support Cases

Use the AWS Support API to retrieve cases that may be relevant.

Retrieve all recent cases (open and resolved)

aws support describe-cases \
  --include-resolved-cases \
  --include-communications \
  --after-time "<ISO-8601-start>" \
  --before-time "<ISO-8601-end>" \
  --language "en"

Filter by specific case IDs (if known)

aws support describe-cases \
  --case-id-list "case-123456789010-muen-2024" \
  --include-communications

Key filtering strategies

StrategyHow to Apply
By time windowUse --after-time and --before-time to scope cases to the relevant period (e.g., past 30 days, or around a previous incident date), because recent cases are more likely to reflect current infrastructure state.
By serviceReview the serviceCode field in returned cases to match the affected service (e.g., amazon-elastic-compute-cloud, amazon-rds), because the same service often exhibits recurring failure patterns.
By severityCheck the severityCode field — focus on urgent and critical cases for major incidents, because higher-severity cases tend to have more detailed root cause analysis from AWS Support.
By statusUse --include-resolved-cases to include closed cases, because resolved cases contain the root cause and remediation steps that are most valuable for correlating with the current incident.
By subject keywordsScan the subject field of returned cases for keywords matching the current incident symptoms, because similar symptoms often share underlying causes.

Step 3: Review Case Communications

The describe-cases response with includeCommunications: true returns the most recent communications for each case in the recentCommunications field (up to 5 messages). Since root cause analysis and resolution steps are typically in the final messages of a resolved case, this is usually sufficient.

If the recentCommunications field includes a nextToken, the case has additional older messages. Only paginate using describe-communications if the recent messages do not contain a clear root cause or resolution — for example, if the last messages are follow-up questions rather than a final answer.

aws support describe-communications \
  --case-id "case-123456789010-muen-2024" \
  --max-results 10 \
  --next-token "<nextToken-from-recentCommunications>"

When reviewing communications, look for:

  1. Root cause statements — AWS Support engineers often summarize the root cause in their final response.
  2. Remediation steps — Specific actions taken to resolve the issue (e.g., "increased max_connections", "applied security group rule", "scaled up instance type").
  3. Configuration recommendations — Best practices or tuning suggestions provided by AWS.
  4. Escalation notes — If the case was escalated, check for deeper technical analysis from specialized teams.

Step 4: Correlate Findings with Current Incident

After reviewing relevant cases, correlate the findings:

Pattern matching checklist

  • Do past cases share the same affected service and resource type?
  • Are the error messages or codes identical or similar?
  • Did past incidents occur at a similar time of day or day of week (indicating load patterns)?
  • Was the root cause a configuration issue that may still be present?
  • Was the resolution a temporary workaround that has since expired or been reverted?
  • Did AWS identify a service-side issue that may be recurring?

Relevance scoring

Rate each historical case on relevance to the current incident:

ScoreCriteria
HighSame service, same error, same resource type, similar timeframe
MediumSame service, different error but related symptoms
LowDifferent service but similar architectural pattern or failure mode

Step 5: Summarize Findings

Provide a structured summary including:

  1. Number of related cases found — How many past cases matched the search criteria.
  2. Most relevant case(s) — Case ID, subject, status, and creation date of the top matches.
  3. Historical root causes — What caused similar issues in the past.
  4. Past resolutions — What remediation steps were applied and whether they were permanent fixes or temporary workarounds.
  5. Recommendations — Based on historical patterns, suggest investigation paths or remediation steps for the current incident.
  6. Recurring pattern alert — If the same issue has occurred multiple times, flag it as a recurring problem requiring a permanent fix or architectural change.

Decision Tree: Case Search Strategy

Is there a known case ID associated with the current incident?
├── YES → Retrieve that specific case and its communications (Step 2, filter by case ID)
└── NO → Continue below

Is the affected AWS service known?
├── YES → Search cases in the past 90 days for that service, then expand to 12 months if needed
└── NO → Search all cases in the past 30 days and filter by error keywords

Were relevant historical cases found?
├── YES → Review communications (Step 3), correlate findings (Step 4), summarize (Step 5)
└── NO → Broaden search criteria:
         - Expand time window
         - Search by related services (e.g., if ELB is affected, also check EC2 and Target Group cases)
         - Search by error code or symptom keywords in case subjects

Tips for Effective Case Review

  • Start narrow, then broaden: Begin with specific filters (service + time window) and expand only if no relevant cases are found.
  • Check resolved cases: The most valuable information often comes from resolved cases where root cause and fix are documented.
  • Note case severity patterns: If past cases for the same issue were filed at critical severity, the current incident may warrant similar urgency.
  • Cross-reference with deployments: If a past case was caused by a deployment, check if a similar deployment occurred before the current incident.

相關技能

ajay-0010/traffic-ai-system

Traffic AI System predicts traffic using XGBoost and optimizes routes with Dijkstra’s Algorithm. It integrates ML with a graph-based routing engine, featuring a FastAPI backend and Streamlit frontend for real-time predictions and interactive map visualization, showcasing full-stack ML and system design skills.

community

dydanz/agen-kecerdasan-buatan-48

Thin AI agent runtime for solo operators — connects Discord/Telegram to Claude, routes intent to hot-reloadable skill files, and compounds knowledge without code deploys. Built as an EM's experiment in AI-first SDLC.

community

to-real/historical-portrait-skill

Codex skill for historically grounded modern-photo reconstructions of historical figures

community

oliwoodman/verify-loop-skill

A Claude skill that runs a supervised, self-verifying loop on a coding task. The loop is the easy part — verification is the point. Built on Boris Cherny's loop engineering.

community

samber/golang-structs-interfaces

Golang struct and interface design patterns — composition, embedding, type assertions, type switches, interface segregation, dependency injection via interfaces, struct field tags, and pointer vs value receivers. Use this skill when designing Go types, defining or implementing interfaces, embedding structs or interfaces, writing type assertions or type switches, adding struct field tags for JSON/YAML/DB serialization, or choosing between pointer and value receivers. Also use when the user asks about "accept interfaces, return structs", compile-time interface checks, or composing small interfaces into larger ones.

community

Janianorthkorean166/claude-code-design-guide

Explore Claude Code design patterns, Agent Runtime, context engineering, and tool systems for building modern AI coding workflows

community