Monitoring
Logging, metrics, and observability
langsmith-trace-analyzer
by Lubu-Labs
"Fetch, organize, and analyze LangSmith traces for debugging and evaluation. Use when you need to: query traces/runs by project, metadata, status, or time window; download traces to JSON; organize outcomes into passed/failed/error buckets; analyze token/message/tool-call patterns; compare passed vs failed behavior; or investigate benchmark and production failures."
predictability
by toss
Use when getX()나 fetchX()에 숨은 부수 효과가 있거나, 같은 종류의 함수들이 서로 다른 반환 타입을 가지거나, 함수 이름과 실제 동작이 다를 때
add-memory-trace-tags
by openharmonyinsight
Use when adding new resource tracking types to memory profiling in developtools_profiler and third_party_musl repositories. Triggered by requests to add trace tags, resource labels, or memory tracking types.
python-observability-patterns
by 0xDarkMatter
"Observability patterns for Python applications. Triggers on: logging, metrics, tracing, opentelemetry, prometheus, observability, monitoring, structlog, correlation id."
techdebt
by jh941213
기술 부채 정리 - 중복 코드, console.log, 사용하지 않는 import 등 검사 및 정리. 세션 종료 전 사용 권장.
swift
by Joannis
'Expert guidance on Swift best practices, patterns, and implementation. Use when developers mention: (1) Swift configuration or environment variables, (2) swift-log or logging patterns, (3) OpenTelemetry or swift-otel, (4) Swift Testing framework or @Test macro, (5) Foundation avoidance or cross-platform Swift, (6) platform-specific code organization, (7) Span or memory safety patterns, (8) non-copyable types (~Copyable), (9) API design patterns or access modifiers.'
grafana
by cosmix
Observability visualization with Grafana and LGTM stack. Dashboard design, panel configuration, alerting, variables/templating, and data sources. USE WHEN: Creating Grafana dashboards, configuring panels and visualizations, writing LogQL/TraceQL queries, setting up Grafana data sources, configuring dashboard variables and templates, building Grafana alerts. DO NOT USE: For writing PromQL queries (use /prometheus), for alerting rule strategy (use /prometheus), for general observability architecture (use senior-software-engineer with infrastructure focus). TRIGGERS: grafana, dashboard, panel, visualization, logql, traceql, loki, tempo, mimir, data source, annotation, variable, template, row, stat, graph, table, heatmap, gauge, bar chart, pie chart, time series, logs panel, traces panel, LGTM stack.
prometheus
by cosmix
Prometheus monitoring and alerting for cloud-native observability. USE WHEN: Writing PromQL queries, configuring Prometheus scrape targets, creating alerting rules, setting up recording rules, instrumenting applications with Prometheus metrics, configuring service discovery. DO NOT USE: For building dashboards (use /grafana), for log analysis (use /logging-observability), for general observability architecture (use senior-software-engineer with infrastructure focus). TRIGGERS: metrics, prometheus, promql, counter, gauge, histogram, summary, alert, alertmanager, alerting rule, recording rule, scrape, target, label, service discovery, relabeling, exporter, instrumentation, slo, error budget.
model-evaluation
by cosmix
Evaluates machine learning models for performance, fairness, and reliability using appropriate metrics and validation techniques. Covers training debugging, hyperparameter tuning, and production monitoring. Trigger keywords: model evaluation, metrics, accuracy, precision, recall, F1, F1-score, ROC, AUC, ROC-AUC, confusion matrix, cross-validation, k-fold, stratified, overfitting, underfitting, bias, variance, bias-variance tradeoff, hyperparameter, hyperparameter tuning, loss, loss function, metric, benchmark, benchmarking, model performance, classification metrics, regression metrics, RMSE, MSE, MAE, MAPE, R2, R-squared, train-test split, validation set, test set, hold-out, learning curve, validation curve, model selection, error analysis, residual analysis, ML testing, training issues, convergence, gradient, vanishing gradient, exploding gradient, training instability, LLM evaluation, language model evaluation, prompt engineering evaluation, A/B testing, champion-challenger, model monitoring, model drift, data drift, concept drift, model decay.
data-visualization
by cosmix
Creates effective data visualizations, charts, dashboards, and reports across analytics, infrastructure monitoring, and ML domains. Covers library selection, UX design, and accessibility. Trigger keywords: chart, graph, plot, dashboard, report, visualization, matplotlib, plotly, d3, seaborn, grafana, tableau, superset, metabase, KPI, metric, analytics, histogram, heatmap, time-series, scatter, bar-chart.
logging-observability
by cosmix
Comprehensive logging and observability patterns for production systems including structured logging, distributed tracing, metrics collection, log aggregation, and alerting. Triggers for this skill - log, logging, logs, trace, tracing, traces, metrics, observability, OpenTelemetry, OTEL, Jaeger, Zipkin, structured logging, log level, debug, info, warn, error, fatal, correlation ID, span, spans, ELK, Elasticsearch, Loki, Datadog, Prometheus, Grafana, distributed tracing, log aggregation, alerting, monitoring, JSON logs, telemetry.
greptimedb-trigger
by GreptimeTeam
Guide for creating GreptimeDB triggers, by which we can trigger external webhook like Alertmanager. This feature can be used as alternative to Prometheus alerting rule.
monitoring-observability
by Logos-Liber
Prometheus, Grafana, CloudWatch, Azure Monitor, Stackdriver, logging, alerting, and SRE practices
github
by SimHacker
See also: tmnn7-8/github-simulation for GitHub as MMORPG
debugging
by SimHacker
Systematic bug investigation with hypothesis tracking
FastAPI Observability
by markus41
This skill should be used when the user asks to "add logging", "implement metrics", "add tracing", "configure Prometheus", "setup OpenTelemetry", "add health checks", "monitor API", or mentions observability, APM, monitoring, structured logging, distributed tracing, or Grafana. Provides comprehensive observability patterns.
ast-grep
by Dwsy
语法感知的代码搜索、linting 和重写工具。支持基于 AST 的结构化代码搜索和批量代码转换。
cto-advisor
by shipshitdev
Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Includes tech debt analyzer, team scaling calculator, engineering metrics frameworks, technology evaluation tools, and ADR templates. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.
go-functional-options
by cxuu
The functional options pattern for Go constructors and public APIs. Use when designing APIs with optional configuration, especially with 3+ parameters.
prometheus-expert
by personamanagmentlayer
Expert-level Prometheus monitoring, metrics collection, PromQL queries, alerting, and production operations
analyze-php-logs
by dykyi-roman
Parses and analyzes PHP application logs in PSR-3/Monolog, Laravel, Symfony, and plain error_log formats. Extracts exceptions, stack traces, request context, error frequency, and correlates related errors.
bug-root-cause-finder
by dykyi-roman
Root cause analysis methods for PHP bugs. Provides 5 Whys technique, fault tree analysis, git bisect guidance, and stack trace parsing.
go-error-handling
by cxuu
Comprehensive Go error handling patterns from Google and Uber style guides. Covers returning errors, wrapping with %w, sentinel errors, choosing error types, handling errors once, error flow structure, and logging. Use when writing Go code that creates, returns, wraps, or handles errors.
circuit-breaker-pattern
by aj-geddes
Implement circuit breaker patterns for fault tolerance, automatic failure detection, and fallback mechanisms. Use when calling external services, handling cascading failures, or implementing resilience patterns.