Loading...
Loading...
Found 803 Skills
Show federation health — peers, sessions, trust levels, and message metrics
Set up and run experiments in LaunchDarkly. Create experiments with metrics and treatments, start iterations to collect data, and monitor results.
Create a new SigNoz alert rule from a natural-language intent — threshold, anomaly, log-volume, error-rate, latency, or absent-data alerts across metrics, logs, traces, and exceptions. Make sure to use this skill whenever the user says "alert me when…", "notify me if…", "set up monitoring for…", "page me on…", "create an alert for…", or asks for a new alert/notification rule, even if they don't say the word "alert" explicitly. Also use it when someone asks to be notified about error rates, latency spikes, log volume, CPU/memory pressure, or anomalous behavior on a service or host.
Onboard a project to Superlog by installing OpenTelemetry traces, logs, and metrics across every app and service in the repo. Triggers on requests like 'install Superlog', 'set up Superlog', 'add Superlog telemetry', 'onboard this repo to Superlog', 'instrument with OpenTelemetry for Superlog'.
Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Triggers: 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]', or any variation requesting multi-source recency intelligence on a topic. Also use for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.
Guides experiment state transitions: launching, pausing, resuming, ending, shipping variants, archiving, resetting, and duplicating. Covers preconditions, implications for variant assignment and analysis, and the decision framework for when to use each action. TRIGGER when: user asks to launch, pause, resume, end, ship, archive, reset, or duplicate an experiment. DO NOT TRIGGER when: user is creating an experiment (use creating-experiments), configuring rollout (use configuring-experiment-rollout), or setting up metrics (use configuring-experiment-analytics).
Guides failure-prevention culture and operational excellence for mission-critical engineering— zero-defect aspiration vs error budgets; HRO principles; defense-in-depth; fail-safe/fail-closed; verification gates and independent checks; redundancy and graceful degradation; pre-mortems and FMEA; stop-the-line; defect escape, near-miss, and repeat-incident metrics; leadership against normalization of deviance—not blame culture. Use for failure-prevention programs, HRO practices, verification gates, fail-safe design, pre-mortem/FMEA, stop-the-line, near-miss reporting, or defect-escape metrics—not SRE error budgets only (site-reliability-engineer), incident command only (incident-management-engineer), backup/restore only (cyber-resilience-engineer), CI lint only (build-validator), agile coaching, HR discipline, or classified ATO without ops-excellence lens (classified-cyber-security-senior-manager).
Query and browse evaluation results stored in MLflow. Use when the user wants to look up runs by invocation ID, compare metrics across models, fetch artifacts (configs, logs, results), or set up the MLflow MCP server. ALWAYS triggers on mentions of MLflow, experiment results, run comparison, invocation IDs in the context of results, or MLflow MCP setup.
Implement Syncfusion Blazor Bullet Chart (SfBulletChart) for KPI and performance visualization. Use this when displaying target vs actual metrics, goal tracking, or performance dashboards. This skill covers actual/target bars, qualitative ranges, and comparative analysis for KPI visualization in Blazor applications.
Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.
Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML visualization toolkit
This skill should be used when establishing comprehensive QA testing processes for any software project. Use when creating test strategies, writing test cases following Google Testing Standards, executing test plans, tracking bugs with P0-P4 classification, calculating quality metrics, or generating progress reports. Includes autonomous execution capability via master prompts and complete documentation templates for third-party QA team handoffs. Implements OWASP security testing and achieves 90% coverage targets.