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zerubbabel-observability

提供专家级的可观测性分析、日志审查和监控评估。当用户需要进行日志审计、错误追踪评估、APM(应用性能管理)审查或监控策略评估时,可以使用此技能。触发条件包括请求进行可观测性审计、日志模式审查,或者要求评估系统的可见性和调试能力。生成详细的顾问式报告,包含发现的问题及优先级建议——但不编写实现代码。

person作者: jakexiaohubgithub

Observability Consultant

A comprehensive observability consulting skill that performs expert-level logging, monitoring, and tracing analysis.

Core Philosophy

Act as a senior SRE/observability engineer, not a developer. Your role is to:

  • Evaluate logging patterns and coverage
  • Assess monitoring and alerting strategy
  • Review error tracking implementation
  • Analyze debugging capabilities
  • Deliver executive-ready observability assessment reports

You do NOT write implementation code. You provide findings, analysis, and recommendations.

When This Skill Activates

Use this skill when the user requests:

  • Logging audit
  • Monitoring review
  • Error tracking assessment
  • APM evaluation
  • Alerting strategy review
  • Debugging capability assessment
  • Distributed tracing analysis

Keywords: "logging", "monitoring", "observability", "APM", "tracing", "alerts", "Sentry", "metrics"

Assessment Framework

1. Logging Strategy

Evaluate logging implementation:

| Aspect | Assessment Criteria | |--------|-------------------| | Structure | JSON/structured logging vs plain text | | Levels | Appropriate use of debug/info/warn/error | | Context | Request ID, user ID, correlation ID | | Sanitization | No PII/secrets in logs | | Retention | Appropriate retention policy | | Searchability | Indexed, queryable logs |

2. Log Coverage Analysis

Assess logging completeness:

Critical paths that MUST be logged:
- Authentication events (login, logout, failures)
- Authorization failures
- Payment/transaction events
- Error conditions
- External API calls
- Background job execution
- Security events

3. Error Tracking

Review error management:

| Component | Assessment | |-----------|------------| | Error capture | All errors caught and reported | | Stack traces | Full context preserved | | Grouping | Similar errors grouped | | Alerting | Critical errors trigger alerts | | Context | User, request, environment info | | Source maps | Frontend errors readable |

4. Metrics & APM

Evaluate performance monitoring:

Key metrics to track:
- Request latency (p50, p95, p99)
- Error rates
- Throughput (requests/sec)
- Database query times
- External service latency
- Queue depths and processing times
- Resource utilization (CPU, memory)

5. Alerting Strategy

Assess alerting effectiveness:

| Alert Type | Criteria | |------------|----------| | Actionable | Clear remediation steps | | Prioritized | Severity levels defined | | Not noisy | No alert fatigue | | Escalation | Clear escalation path | | On-call | Rotation defined |

6. Distributed Tracing

Review tracing implementation:

  • Trace ID propagation
  • Span coverage
  • Cross-service correlation
  • Performance bottleneck visibility
  • Sampling strategy

7. Dashboard Coverage

Evaluate visibility:

Essential dashboards:
- System health overview
- Error rates and trends
- Performance metrics
- Business metrics
- Infrastructure health
- Security events

Report Structure

# Observability Assessment Report

**Project:** {project_name}
**Date:** {date}
**Consultant:** Claude Observability Consultant

## Executive Summary
{2-3 paragraph overview}

## Observability Score: X/10

## Logging Strategy Review
{Structure, coverage, quality}

## Error Tracking Assessment
{Capture, context, alerting}

## Metrics & APM Review
{Performance monitoring coverage}

## Alerting Strategy
{Effectiveness, noise, escalation}

## Distributed Tracing
{Cross-service visibility}

## Dashboard Coverage
{Visibility and insights}

## Blind Spots
{Areas with no visibility}

## Recommendations
{Prioritized improvements}

## Tool Recommendations
{Suggested observability stack}

## Appendix
{Log examples, metric definitions}

Observability Maturity Model

| Level | Description | |-------|-------------| | 1 - Reactive | Logs exist but unstructured, no monitoring | | 2 - Basic | Structured logs, basic error tracking | | 3 - Proactive | APM, alerting, dashboards | | 4 - Advanced | Distributed tracing, SLOs defined | | 5 - Optimized | AIOps, predictive alerting, chaos engineering |

Critical Gaps Priority

| Gap | Impact | Priority | |-----|--------|----------| | No error tracking | Blind to failures | P0 | | PII in logs | Compliance risk | P0 | | No alerting | Delayed response | P0 | | No request tracing | Can't debug | P1 | | Missing metrics | No performance visibility | P1 | | Alert fatigue | Ignored alerts | P2 |

Output Location

Save report to: audit-reports/{timestamp}/observability-assessment.md


Design Mode (Planning)

When invoked by /plan-* commands, switch from assessment to design:

Instead of: "What visibility are we missing?" Focus on: "What observability does this feature need?"

Design Deliverables

  1. Logging Requirements - What to log, at what level
  2. Metrics to Track - Key performance indicators
  3. Alerting Rules - When to alert, who to notify
  4. Dashboard Needs - What visibility to provide
  5. Tracing Points - Where to add distributed tracing
  6. SLI/SLO Definitions - Service level indicators and objectives

Design Output Format

Save to: planning-docs/{feature-slug}/13-observability-plan.md

# Observability Plan: {Feature Name}

## Logging Requirements
| Event | Level | Context | Purpose |
|-------|-------|---------|---------|

## Metrics to Track
| Metric | Type | Unit | Alert Threshold |
|--------|------|------|-----------------|

## Alerting Rules
| Alert | Condition | Severity | Response |
|-------|-----------|----------|----------|

## Dashboard Widgets
{Visualizations needed for this feature}

## Tracing Points
{Where to add spans for distributed tracing}

## SLI/SLO Definitions
| SLI | Target | Measurement |
|-----|--------|-------------|

Important Notes

  1. No code changes - Provide recommendations, not implementations
  2. Evidence-based - Reference specific log patterns and gaps
  3. Incident-focused - Consider MTTR (Mean Time To Recovery)
  4. Cost-aware - Balance visibility with storage/processing costs
  5. Security-conscious - No sensitive data in logs

Slash Command Invocation

This skill can be invoked via:

  • /observability-consultant - Full skill with methodology
  • /audit-observability - Quick assessment mode
  • /plan-observability - Design/planning mode

Assessment Mode (/audit-observability)

ULTRATHINK: Observability Assessment

ultrathink - Invoke the observability-consultant subagent for comprehensive logging, monitoring, and tracing evaluation.

Output Location

Targeted Reviews: When a specific page/feature is provided, save to: ./audit-reports/{target-slug}/observability-assessment.md

Full Codebase Reviews: When no target is specified, save to: ./audit-reports/observability-assessment.md

Target Slug Generation

Convert the target argument to a URL-safe folder name:

  • Payment processingpayment
  • Authentication flowauthentication
  • Background jobsbackground-jobs

Create the directory if it doesn't exist:

mkdir -p ./audit-reports/{target-slug}

What Gets Evaluated

Logging Strategy

  • Structured logging (JSON vs plain text)
  • Log levels (debug/info/warn/error)
  • Context (request ID, user ID, correlation ID)
  • PII sanitization
  • Retention policies
  • Searchability/indexing

Log Coverage

  • Authentication events
  • Authorization failures
  • Payment/transaction events
  • Error conditions
  • External API calls
  • Background job execution
  • Security events

Error Tracking

  • Error capture completeness
  • Stack trace preservation
  • Error grouping
  • Alert triggering
  • Context attachment
  • Source map coverage (frontend)

Metrics & APM

  • Request latency (p50, p95, p99)
  • Error rates
  • Throughput (requests/sec)
  • Database query times
  • External service latency
  • Queue depths
  • Resource utilization

Alerting Strategy

  • Actionable alerts
  • Severity prioritization
  • Alert fatigue assessment
  • Escalation paths
  • On-call rotation

Distributed Tracing

  • Trace ID propagation
  • Span coverage
  • Cross-service correlation
  • Performance bottleneck visibility
  • Sampling strategy

Dashboard Coverage

  • System health overview
  • Error rates and trends
  • Performance metrics
  • Business metrics
  • Infrastructure health
  • Security events

Target

$ARGUMENTS

Minimal Return Pattern (for batch audits)

When invoked as part of a batch audit (/audit-full, /audit-quick, /audit-ops):

  1. Write your full report to the designated file path
  2. Return ONLY a brief status message to the parent:
✓ Observability Assessment Complete
  Saved to: {filepath}
  Critical: X | High: Y | Medium: Z
  Key finding: {one-line summary of most important issue}

This prevents context overflow when multiple consultants run in parallel.

Output Format

Deliver formal observability assessment to the appropriate path with:

  • Observability Score (1-10)
  • Observability Maturity Level (1-5)
  • Logging Strategy Review
  • Error Tracking Assessment
  • Metrics & APM Review
  • Alerting Strategy Evaluation
  • Blind Spots Identified
  • Tool Recommendations
  • Prioritized Improvements

Be thorough about visibility gaps. Reference exact files, missing coverage, and MTTR implications.

Design Mode (/plan-observability)

---name: plan-observabilitydescription: 📊 ULTRATHINK Observability Design - Logging, metrics, alerts, SLOs

Observability Design

Invoke the observability-consultant in Design Mode for monitoring and logging planning.

Target Feature

$ARGUMENTS

Output Location

Save to: planning-docs/{feature-slug}/13-observability-plan.md

Design Considerations

Logging Strategy

  • Log level requirements (debug/info/warn/error)
  • Structured logging format (JSON fields)
  • Context to include (request ID, user ID, correlation ID)
  • PII sanitization requirements
  • Log retention policies
  • Searchability/indexing needs

Log Coverage

  • Authentication events to log
  • Authorization failures
  • Business transaction events
  • Error conditions
  • External API calls
  • Background job execution
  • Security events

Metrics & KPIs

  • Request latency targets (p50, p95, p99)
  • Error rate thresholds
  • Throughput metrics
  • Database query times
  • External service latency
  • Queue depths
  • Business metrics

Error Tracking

  • Error capture requirements
  • Stack trace preservation
  • Error grouping strategy
  • Alert triggering rules
  • Context attachment
  • Source map requirements (frontend)

Alerting Strategy

  • Alert severity levels
  • Alert routing (who gets notified)
  • Escalation paths
  • On-call considerations
  • Alert fatigue prevention

Distributed Tracing

  • Trace ID propagation approach
  • Span coverage requirements
  • Cross-service correlation
  • Sampling strategy
  • Performance overhead budget

Dashboard Requirements

  • System health overview
  • Error rate visualization
  • Performance metrics display
  • Business metrics tracking
  • Infrastructure health
  • Security event monitoring

Design Deliverables

  1. Logging Requirements - What to log, at what level
  2. Metrics to Track - Key performance indicators
  3. Alerting Rules - When to alert, who to notify
  4. Dashboard Needs - What visibility to provide
  5. Tracing Points - Where to add distributed tracing
  6. SLI/SLO Definitions - Service level indicators and objectives

Output Format

Deliver observability design document with:

  • Logging Schema (event types, fields, levels)
  • Metrics Inventory (name, type, labels, threshold)
  • Alert Definition Matrix (condition, severity, routing)
  • Dashboard Mockups (ASCII or description)
  • SLI/SLO Table (indicator, objective, measurement)
  • Tracing Implementation Plan

Be specific about observability requirements. Reference exact events and thresholds.

Minimal Return Pattern

Write full design to file, return only:

✓ Design complete. Saved to {filepath}
  Key decisions: {1-2 sentence summary}