Results for “performance-regression”

Performance regression detection using the browse daemon. (gstack)

Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.

Measures performance baselines, detects regressions before and after PRs, and compares stack alternatives.

Use this skill to measure performance baselines, detect regressions before/after PRs, and compare stack alternatives.

Performance regression detection using the browse daemon. Establishes baselines for page load times, Core Web Vitals, and resource sizes. Compares before/after on every PR. Tracks performance trends over time. Use when: "performance", "benchmark", "page speed", "lighthouse", "web vitals", "bundle size", "load time". (gstack) Voice triggers (speech-to-text aliases): "speed test", "check performance".

Use this skill to measure performance baselines, detect regressions before/after PRs, and compare stack alternatives.

Measure performance baselines, detect regressions before and after PRs, and compare stack alternatives using browser, API, and build benchmarks.

Performance Profiler

Performance-coaching mode for repeated failures, passive behavior, completion-quality issues, or explicit try-harder requests. Uses structured troubleshooting and evidence-first delivery habits.

Launches four parallel read-only sub-agents to review a git diff or file scope for regressions, security risks, performance issues, and contract gaps, then aggregates findings into a prioritized fix path.

The instruction to profile before optimizing survives because intuition about

Measures application performance first, identifies bottlenecks, and applies targeted fixes for frontend and backend systems.

Performance profiling principles. Measurement, analysis, and optimization techniques.

Use when evaluating, measuring, or comparing the performance of systems, functions, or services. This skill provides a framework for establishing baselines, measuring performance, and validating that changes meet performance requirements.

Reviews closed trades, partial exits, and monthly trade aggregates for process adherence, risk discipline, execution quality, and evidence-based trading behavior patterns.

Performance-coaching mode for repeated failures, passive behavior, completion-quality issues, or explicit try-harder requests. Uses structured troubleshooting and evidence-first delivery habits.

Performance baseline measurement and regression detection. Use when measuring perf before/after a PR, setting up baselines, investigating "feels slow" reports, validating launch performance targets, or comparing your stack against alternatives.

Performance — Forge Skill

Improves measured performance while preserving correctness, reliability, and maintainability.

Use for identifying and resolving performance bottlenecks.

Systematically profile Node.js, Python, and Go applications to identify CPU, memory, and I/O bottlenecks, generate flamegraphs, analyze bundle sizes, optimize database queries, and run load tests with k6 and Artillery.

Delivers measurement-driven performance optimization for latency, throughput, memory, and tail behavior, with correctness preservation and regression guards.

Use the status-briefing skill to run `pk-reconcile session-start`, then

Prevents AI-introduced regressions with sandbox-mode API testing, automated bug-check workflows, and patterns that catch blind spots where the same model writes and reviews code.

Evaluate the financial impact of pricing changes using ARPU, conversion, churn risk, NRR, and payback analysis to make data-driven go/no-go decisions.

Use when tuning RL reward function weights, fixing reward hacking, or addressing P&L gradient issues

Facilitate a structured sprint retrospective — what went well, what didn't, and prioritized action items with owners and deadlines. Use when running a retrospective, reflecting on a sprint, creating action items from team feedback, or learning how to run effective retros.

Analyze sprint retrospectives for patterns and action item tracking. Usage: /retro analyze <retro_data.json>

Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.

Monitors a deployed URL for regressions after releases by checking HTTP status, console errors, network failures, performance metrics, content integrity, API health, static assets, and SSE streams.