mutation-testing-js
Mutation testing patterns for JS/TS using Stryker. Analyze branch code to find weak or missing tests, verify test effectiveness, and strengthen Node.js test suites.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
267 skills found
Mutation testing patterns for JS/TS using Stryker. Analyze branch code to find weak or missing tests, verify test effectiveness, and strengthen Node.js test suites.
Official Sunhat toolkit for end-to-end TRON smart contract lifecycle: development, compilation, cross-framework testing, and deployment.
Enforces a strict evidence-before-assertion protocol for coding agents, requiring fresh command-line verification output before any claim of completion, success, or bug fixes.
Autonomous QA cycling workflow that runs test-verify-fix loops until your quality goals are met.
Automate high-quality screenshot generation for MicroSim visualizations using Chrome headless mode. Ideal for documentation, social media previews, and quality assessment.
Token-efficient CLI for browser automation, web testing, and agentic workflows using Playwright.
Debug the AWF (Agentic Workflow Firewall) by inspecting containers, analyzing Squid logs, checking iptables, and troubleshooting network or domain access issues in isolated sandboxes.
Fixes CJS/ESM module compatibility issues in Nango integrations after zero-yaml migration, including path adjustments, ESM wrappers, and restoring original implementations.
Implements an autonomous, critical self-verification layer for AI agents to validate code quality, security, and requirement alignment before task completion.
Perform automated security audits, bug detection, and code quality assessments on local branch diffs using a structured, checklist-driven verification process.
Guide for implementing a new AI coding agent analyzer in Splitrail to track token usage, costs, and performance metrics.
Framework for building AI agents that persist state across multiple context windows, enabling them to complete complex, multi-day coding tasks without losing progress or context.