Skill-Verzeichnis

Wiederverwendbare Skills für AI Agents entdecken.

Durchsuche reale GitHub-Skills nach Aufgabe und prüfe Stars, Trust, Audit, Kategorie und Installationspfad vor der Verwendung.

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Englisches Verzeichnis

React and Next.js performance guidance for writing, reviewing, and refactoring production UI code.

30K
Stars
88/100
Trust
Kategorie: coding-agentsAudit

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

51K
Stars
68/100
Trust
Kategorie: design-creativeAudit

Official GSAP skill for GSAP plugins — registration, ScrollToPlugin, ScrollSmoother, Flip, Draggable, Inertia, Observer, SplitText, ScrambleText, SVG and physics plugins, CustomEase, EasePack, CustomWiggle, CustomBounce, GSDevTools. Use when the user asks about a GSAP plugin, scroll-to, flip animations, draggable, SVG drawing, or plugin registration.

14K
Stars
76/100
Trust
Kategorie: automationAudit

Idiomatic Golang design patterns — functional options, constructors, error flow and cascading, resource management and lifecycle, graceful shutdown, resilience, architecture, dependency injection, data handling, streaming, and more. Apply when explicitly choosing between architectural patterns, implementing functional options, designing constructor APIs, setting up graceful shutdown, applying resilience patterns, or asking which idiomatic Go pattern fits a specific problem.

3.0K
Stars
74/100
Trust
Kategorie: researchAudit

Golang benchmarking, profiling, and performance measurement. Use when writing, running, or comparing Go benchmarks, profiling hot paths with pprof, interpreting CPU/memory/trace profiles, analyzing results with benchstat, setting up CI benchmark regression detection, or investigating production performance with Prometheus runtime metrics. Also use when the developer needs deep analysis on a specific performance indicator - this skill provides the measurement methodology, while `samber/cc-skills-golang@golang-performance` provides the optimization patterns.

3.0K
Stars
67/100
Trust
Kategorie: researchAudit

Describe what an existing SigNoz alert rule does in plain language — the signal it watches, the threshold and evaluation behavior, the notification routing, and a one-line fire-frequency summary so the user knows whether the alert has been active. Make sure to use this skill whenever the user asks "what does this alert do", "explain alert X", "walk me through this rule", "how does my [Y] alert work", "is this alert configured correctly", or otherwise asks for an interpretation of an existing alert's configuration. Static explanation only — for diagnosing a specific firing incident, use `signoz-investigating-alerts`.

15
Stars
61/100
Trust
Kategorie: researchAudit

Run the full end-to-end observability setup for a service after its telemetry is already flowing into SigNoz — sequence SLI/SLO capture, data exploration (RED/USE), focused dashboards, saved Explorer views, burn-rate and absent-data alerts, and a tuning loop into one opinionated, SLO-aware workflow. Make sure to use this skill whenever the user says "set up observability after ingestion", "now that data is flowing, give me dashboards and alerts", "onboard this service to SigNoz end-to-end", "I want the full monitoring setup for X", or asks to go from raw telemetry to a complete dashboard + alerts + views package — even if they don't say "observability" explicitly. This is the orchestration layer: for a single artifact (just a dashboard, just one alert, just a saved view, or one static threshold alert, or a one-off query) use signoz-creating-dashboards, signoz-creating-alerts, signoz-managing-views, or signoz-generating-queries directly.

15
Stars
58/100
Trust
Kategorie: data-analysisAudit

Golang benchmarking, profiling, and performance measurement. Use when writing, running, or comparing Go benchmarks, profiling hot paths with pprof, interpreting CPU/memory/trace profiles, analyzing results with benchstat, setting up CI benchmark regression detection, or investigating production performance with Prometheus runtime metrics. Also use when the developer needs deep analysis on a specific performance indicator - this skill provides the measurement methodology, while golang-performance provides the optimization patterns.

12
Stars
65/100
Trust
Kategorie: researchAudit