Run frontend functional, accessibility, visual, and performance test planning with structured reports.
The English summary is being prepared. Showing the original description.
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
Validate frontend quality across user journeys, a11y, visual regressions, and performance targets.
@axe-core/playwrightfrontend-test-report.json with Lighthouse scores and pass/fail counts.python skills/web-frontend-tester/scripts/frontend_tester.py --input <workspace> --output <out.json> --format json
references/tools.mdNo reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Scaffold MCP server projects and baseline tool contract checks. Use for defining tool schemas, generating starter server layouts, and validating MCP-ready structure.
The English summary is being prepared. Showing the original description.
Generate reusable multi-step agent workflow blueprints. Use for trigger/action orchestration, deterministic workflow definitions, and automation handoff artifacts.
The English summary is being prepared. Showing the original description.
Build incident response timelines and report packs from event logs. Use for detection-to-recovery reporting, phase tracking, and stakeholder-ready incident summaries.
The English summary is being prepared. Showing the original description.
Prioritize vulnerability remediation using KEV-style exploitation context plus asset criticality. Use for CVE triage, patch order decisions, and remediation reporting.
The English summary is being prepared. Showing the original description.
Map application security findings to OWASP Top 10 categories and generate remediation checklists. Use for normalized AppSec review outputs and category-level prioritization.
The English summary is being prepared. Showing the original description.
Build transformer fine-tuning run plans with task settings, hyperparameters, and model-card outputs. Use for repeatable Hugging Face or PyTorch finetuning workflows.
The English summary is being prepared. Showing the original description.