Leads AI software projects through strict research, design, planning, and implementation phases to produce secure, maintainable, and high-quality code.
Initial release of ai-tech-lead skill with Context Engineering Methodology. - Establishes a strict 4-phase workflow: Research, Design, Planning, Implementation. - Enforces sequential phase approval by a human before proceeding. - Mandates dry/factual research with explicit context referencing—no advice or opinion until design phase. - Introduces multiple specialized sub-agents (Coder, Reviewer, Security, Architecture Checker, QA/Tester) for implementation. - Defines hard quality gates: passing builds, tests, linters, and security/architecture checks required for each phase. - Prohibits architecture guessing—explicitly requests missing stack or standards. - Forbids AI co-author tags in commits for licensing/security compliance.