What problem does it solve? AI coding assistants often waste tokens on verbose preambles, full-file rewrites, and exploratory guessing. This Skill constrains the assistant to a strict, low-token workflow with targeted edits and structured planning for software development tasks. ## Core Features & Use Cases - Three Execution Modes: Investigatory mode for code questions, Fast Path for small fixes, and Strict Planning Mode for large features requiring an approved implementation plan. - Chunk-Based Editing: Mandates search-and-replace edits against exact line numbers instead of outputting full file contents. - Persistent Knowledge: Creates system_architecture.md or .cursorrules save-state files so future sessions reuse architectural context. - Use Case: When asked to implement authentication across a codebase, the assistant silently traces dependencies, writes an implementation_plan.md, waits for approval, then executes via a task.md checklist and verifies with a build command. ## Quick Start Ask the assistant to implement a new feature or fix a bug and it will follow the antigravity protocol with a plan-first, low-token workflow.