Resolve three-layer TOML customization for a Master Test Architect assistant.
npx skills add https://github.com/joekhosbayar/go-mighty --skill bmad-tea-joekhosbayar
Please help me install this Agent Skill. Skill: bmad-tea Source: https://github.com/joekhosbayar/go-mighty/tree/main/.gemini/skills/bmad-tea Command: npx skills add https://github.com/joekhosbayar/go-mighty --skill bmad-tea-joekhosbayar
The bmad-tea skill provides a persona-driven AI assistant tailored for testing governance, enabling three-layer customization resolution, resource-aware activation, and a structured capabilities menu to guide decision-making.
Run python3 scripts/resolve-customization.py bmad-tea to resolve customization, then apply the persona and load any listed resources before interacting with the agent.
High-intent search queries and answers about installing and using this skill.
AI test architecture guidance is customized using a three-layer TOML configuration system. It merges user, team, and default settings to resolve a final Master Test Architect persona, ensuring governance rules are applied safely.
A Master Test Architect persona is an AI assistant role configured for testing governance. It provides structured, auditable decision-making by loading specific knowledge fragments and exposing a capabilities menu for test architecture tasks.
Customized activation prompts are loaded by running the resolve-customization script with the skill name. This script processes three-layer TOML overrides and dynamically loads supplementary resources to prepare the agent for interaction.
Yes, user and team level overrides are applied through the three-layer TOML customization resolution. This mechanism prioritizes user configurations, then team settings, and finally defaults to deliver governed AI testing recommendations.
No external dependencies are required to run this test architecture skill. It operates independently using internal scripts to resolve TOML configurations and load resource knowledge fragments for the AI assistant.
TOML overrides for AI testing governance rely on static configuration files, meaning dynamic runtime changes outside the loaded resource paths are not supported. Guidance is strictly bound to the resolved persona and loaded knowledge fragments.
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