context-driven-testing
Apply context-driven testing principles to adapt testing strategies based on project goals, risks, and constraints rather than relying on universal best practices.
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439 skills found
Apply context-driven testing principles to adapt testing strategies based on project goals, risks, and constraints rather than relying on universal best practices.
Apply Holistic Testing with PACT (Proactive, Autonomous, Collaborative, Targeted) principles to build quality into team culture and test strategies for modern software systems.
Clarify ambiguous requirements through systematic dialogue and scoring to ensure high-quality, actionable PRDs before starting implementation.
Expert technical support for the Litestream disaster recovery tool, covering WAL monitoring, LTX replication, cloud storage backends, and SQLite page management.
Comprehensive security audit and hardening for AI agents: credential scanning, PII protection, prompt injection defense, and workspace config optimization.
Monitor US-Iran strike probability via real-time open-source signals including market odds, flight traffic, energy prices, and geopolitical alerts.
Scaffold and register new sensor, actuator, or service tools for familiar-ai, automating file creation and boilerplate integration in agent.py and config.py.
Full-stack application orchestrator that analyzes natural language requests to determine tech stacks, scaffold projects, and coordinate specialized development agents.
Social media intelligence gathering for TikTok and Instagram. Discover trending hooks, analyze creator strategies, and perform profile data research using the ScrapeCreators API.
Fetch real-time financial signals, transmission-chain reasoning, and market confidence metrics directly from the DeepEar Lite platform.
Autonomous multi-agent orchestration framework for Claude Code with memory-driven workflows, parallel-first task execution, Aristotle-based deconstruction, and multi-stage quality gates.
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement in AI agents.