Results for “regression”

Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.

The English summary is being prepared. Showing the original description.

Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.

The English summary is being prepared. Showing the original description.

Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.

The English summary is being prepared. Showing the original description.

Econometrics skill for Regression Discontinuity Design (RDD). Activates when the user asks about: "regression discontinuity", "RDD", "RD design", "sharp RDD", "fuzzy RDD", "running variable", "forcing variable", "cutoff", "bandwidth selection", "local linear regression", "McCrary test", "density test", "RDROBUST", "continuity assumption", "donut hole RDD", "geographic RDD", "断点回归", "回归不连续", "运行变量", "截断值", "带宽选择", "精确断点", "模糊断点", "密度检验", "局部线性回归"

The English summary is being prepared. Showing the original description.

Visual regression: production-level screenshots, diff thresholds, anti-flake. Use when implementing, reviewing or testing visual regression for React, Vite, Next.js or Perfect_AI projects.

The English summary is being prepared. Showing the original description.

Discover governing equations from data using PySR (evolutionary symbolic regression). Physics-constrained search with dimensional analysis, custom operators, and complexity-accuracy tradeoffs. Use when you need an interpretable equation, not a black-box model.

The English summary is being prepared. Showing the original description.

Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.

The English summary is being prepared. Showing the original description.

Implements visual regression testing with screenshot comparison, diff detection, and CI integration using Playwright or Chromatic. Use when users request "visual testing", "screenshot testing", "UI regression", "visual diff", or "Chromatic setup".

The English summary is being prepared. Showing the original description.

Review new and existing software tests for the behavior and regressions they actually protect. Identify duplicate or implementation-dependent checks, document evidence before removal, and simplify code used only by tests while retaining meaningful coverage.

• Checking whether a new test adds useful coverage
• Auditing duplicate or implementation-dependent tests
• Reviewing code exposed only for testing

Inventory existing tests and identify gaps. Link requirements, business rules, risks, and bugs to stable test identifiers and executable evidence, maintaining a test registry that shows what is covered and what still needs verification.

• Inventory existing tests and identify gaps
• Link bug fixes to regression evidence
• Check client and server behavior against one shared contract

Define success criteria before AI coding, then assess new capabilities and check that existing behavior still works using code, rules, models, or human review. Track repeated-attempt success metrics and reports to compare prompt changes, agent changes, or model versions.

• Defining success criteria before AI implementation
• Checking existing behavior after prompt or agent changes
• Measuring reliability across repeated attempts

Measure web page speed, API response times, and build or test duration. Save baseline measurements as JSON tracked in Git, then compare results before and after changes to identify performance regressions and assess launch targets.

• Comparing performance before and after a code change
• Investigating reports that a page feels slow
• Checking performance targets before launch

Review Spec Kit code changes against relevant design documents, tests for expected and unwanted behavior, evidence that bug fixes prevent recurrence, and repository terminology. Findings identify the document sections behind design mismatches.

• Reviewing a Spec Kit pull request
• Checking test coverage for expected and unwanted behavior
• Checking regression evidence for a bug fix

Investigate software errors by tracing code, reviewing recent changes, and reproducing symptoms. Test a specific cause before making a minimal fix, then verify the result with regression tests and a structured debug report.

• Investigating errors and stack traces
• Tracing bugs introduced by recent changes
• Verifying fixes and documenting regression tests

Measure web page loading times, rendering milestones, and resource sizes in a real browser. Save baseline measurements, compare results before and after code changes, and inspect historical trends to spot performance regressions.

• Saving performance baselines before changes
• Checking page speed after a code change
• Finding slow resources and large transfers

Investigate failing tests, broken builds, and unexpected behavior through a structured debugging process. Reproduce the failure, narrow down its source, fix the root cause, and add a regression test that catches the same problem.

• Investigating a test that fails after a code change
• Finding the cause of a broken build
• Tracing a feature that stopped working

Investigate slow PostgreSQL queries in Paperclip, reproduce their cost locally, and implement measured fixes. Compare performance and returned results, add regression coverage, and carry pull requests through review and automated checks.

• Investigate slow requests with a suspected database cause
• Reduce the cost of frequently repeated queries
• Compare query speed and results before and after a fix

Measure and optimize claude-flow v3 startup, search, attention processing, and memory use. Compare benchmarks against performance targets, track changes over time, and identify regressions to guide further optimization.

• Compare performance before and after v3 optimization
• Evaluate vector search speed and memory use
• Track performance regressions over time

Measure code performance and run benchmarks to investigate slow operations, regressions, or memory pressure. Establish a baseline, compare results under matching conditions, report variability, and rerun correctness tests after optimization.

• Investigate slow operations
• Compare performance before and after a change
• Measure performance when memory pressure occurs

Check a codebase for known dependency vulnerabilities, hard-coded secrets, and risky code patterns using Ruflo security tools. Choose a scan depth, inspect matching lines, and report verified concerns with a clear account of what was checked.

• Checking pull requests for security regressions
• Inspecting authentication and input-handling code for risky patterns
• Running security checks before production deployment

Develop features through a test-first workflow using mocks, or stand-ins for dependencies. Write a failing behavior test, implement the minimum code, refactor, and record observed results from final target and regression tests.

• Define expected behavior before implementing a feature
• Test modules with mocked external dependencies
• Refactor code while keeping tests passing

Compare two recorded browser sessions at matching step IDs using screenshots and accessibility snapshots, which describe page elements. Report the first difference and overall similarity to check interface changes or verify replayed sessions.

• Checking visual regressions after interface changes
• Verifying a replay against its original session
• Comparing A/B variants of a form workflow

Compare two saved cost-summary JSON snapshots to identify changes in total spending, sessions, and model costs. Set limits on spending increases or token growth to flag cost regressions during pull request checks.

• Comparing spending before and after a pull request
• Finding models responsible for cost changes
• Failing checks when spending exceeds set limits

Measure and optimize claude-flow v3 startup, search, attention processing, and memory use. Compare benchmarks against performance targets, track changes over time, and identify regressions to guide further optimization.

• Compare performance before and after v3 optimization
• Evaluate vector search speed and memory use
• Track performance regressions over time