Results for “test-app”

LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.

A/B and multivariate testing methodology. Design experiments, calculate sample sizes, determine statistical significance, avoid common pitfalls, and interpret results. Platform-agnostic framework applicable to landing pages, emails, ads, pricing, and product features. Use when the user asks about A/B testing, split testing, experiment design, statistical significance, or conversion experiments.

Documents AI-built apps with architecture, permissions, secrets, and test coverage maps to make them reviewable before shipping.

Test-drive Django applications with pytest, factory_boy, and Django REST Framework, covering models, views, serializers, and API endpoints.

Audits and optimizes conversion points across the funnel, applying behavioral science to produce prioritized, testable hypotheses.

Guides test-driven development for Django applications using pytest, factory_boy, and Django REST Framework, covering models, views, serializers, and API testing.

Guides the creation, editing, and verification of agent skills using a test-driven development approach, with structured documentation and quality gates.

Performs design operations in the big-data domain, including hypothesis testing, statistical analysis, and data visualization using ML frameworks.

Tests and debugs web applications in real browsers using Chrome DevTools MCP, enabling DOM inspection, console error capture, network analysis, performance profiling, and visual verification with live runtime data.

Test web application email functionality for SMTP header injection vulnerabilities that allow attackers to inject additional email headers, modify recipients, and abuse contact forms for spam relay.

Systematically QA test a web application and fix bugs found. Runs QA testing, then iteratively fixes bugs in source code, committing each fix atomically and re-verifying. Use when asked to "qa", "QA", "test this site", "find bugs", "test and fix", or "fix what's broken". Proactively suggest when the user says a feature is ready for testing or asks "does this work?". Three tiers: Quick (critical/high only), Standard (+ medium), Exhaustive (+ cosmetic). Produces before/after health scores, fix evidence, and a ship-readiness summary. For report-only mode, use /qa-only. (gstack) Voice triggers (speech-to-text aliases): "quality check", "test the app", "run QA".

Test web applications for path traversal vulnerabilities that allow reading or writing arbitrary files on the server by manipulating file path parameters.

Automates end-to-end QA: starts the app, exercises screens and API endpoints, verifies functionality and design quality, runs domain analysis, and fixes issues found.

Race condition and TOCTOU testing for web apps. Use when testing one-time operations, concurrent HTTP abuse, rate-limit bypass, Turbo Intruder gates, HTTP/2 single-packet attacks, and CWE-362-style synchronization gaps.

Orchestrate altering an existing, working feature to new desired behavior by updating tests first, then changing implementation, reviewing, and committing with gated approval.

Provides best practices for building idiomatic Spring Boot applications with Kotlin, covering project setup, dependency injection, configuration, web layer, services, data layer, testing, and coroutines.

Track build processing, find latest builds, and clean up old builds with asc. Use when managing build retention or waiting on processing.

Assists with intercepting network requests for API mocking using Mock Service Worker (MSW). Use when mocking REST or GraphQL APIs for unit tests, integration tests, or local development without modifying application code or running mock servers. Trigger words: msw, mock service worker, api mocking, test mocking, request handlers, setupServer.

Prove a feature works by delegating verification to an independent sub-agent that drives the real app, then open a pull request with the proof.

Defines, validates, runs, resumes, and audits repo-local multi-step automations using the `asc workflow` CLI and `.asc/workflow.json`, including step outputs and safe release/TestFlight workflows.

Dynamically instrument iOS apps with Frida to trace methods, extract secrets, and bypass security controls during authorized penetration testing.

Provides best practices for developing high-quality Spring Boot applications, covering project structure, dependency injection, configuration, web layer, service layer, data layer, logging, testing, and security.

Test web applications for clickjacking vulnerabilities by assessing frame embedding controls and crafting proof-of-concept overlay attacks during authorized security assessments.

Systematically explore a web application to find bugs and UX issues, producing a structured report with screenshots, repro videos, and detailed steps for each finding.

Test LLM applications for system prompt leakage using manual payloads, garak, and Promptfoo to extract embedded secrets and routing logic.

Builds, refines, tests, or validates a CLI-Anything harness for a GUI application or source repository, producing a stateful Click CLI with JSON output and REPL mode.

Applies behavior-driven development principles including Gherkin scenarios and test-driven development. This skill should be used when the user asks to implement features, fix bugs, or when writing executable specifications and tests before writing production code.

Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.

Design and apply QA methodology for software teams: test strategy, regression testing, CI failure triage, test automation, quality gates and metrics, risk-based testing, exploratory testing, test design techniques, AI code quality gates (independent verification, acceptance-criteria testability review for agentic Spec-Driven Development), mutation-guided test hardening and review evidence (surviving mutants, weak assertions, diff-aware mutation testing), agentic eval design (dataset test design, judge-as-system-under-test, flaky-eval discipline), QA career levels (Senior/Staff/Principal), and SDET engineering (test infrastructure, gTAA, CI/CD integration). Do not use for root-cause debugging of production incidents, security implementation or threat modeling, or evaluation framework governance and statistical analysis — route those to systematic-debugging, secure-software-engineering, and agent-evals-and-observability respectively.

Build reliable, fault-tolerant Python applications with DBOS durable workflows, steps, queues, and communication patterns.

Applies the same change across multiple repositories in parallel using git worktrees, tests, and pull requests.

Ecto patterns for Phoenix/Elixir apps. Covers schemas, changesets, migrations, queries, Ecto.Multi, transactions, constraints, associations, pagination, tenant partitioning, performance, and testing.

Master Django 5.x with async views, DRF, Celery, and Django Channels. Build scalable web applications with proper architecture, testing, and deployment.

Set up CI/CD pipelines for Flutter apps. Use when configuring automated testing, build, or deployment workflows with GitHub Actions or Fastlane.

Use when testing or validating the client UI end-to-end - verifying a page renders, a form submits, navigation works, or checking visual/responsive behavior in a real browser. Use when the user asks to "test", "check", or "verify" something in the app that requires clicking through the UI, not just unit tests.

Configure TLS 1.3 on nginx, Apache, and Python applications, validate configurations with openssl and testssl.sh, and disable legacy TLS versions.