Reading
Designed specifically for Gemini CLI, this high-efficiency SKILL.md formula and agent workflow optimizes zero token waste and maximizes developer efficiency.
Section 01
This project focuses on efficient AI prompt engineering for Gemini CLI, aiming at zero token waste and maximizing developer efficiency. It uses SKILL.md methodology (structured reusable skills) and agent workflows, with key highlights including direct execution without redundant explanations, Gemini CLI integration, and a Tahoe OS 26 case study showing significant efficiency gains.
Section 02
LLM API calls have costs and rate limits. Traditional interactions (explanations first, then solutions) lead to unnecessary token consumption and slower development. The Antigravity project addresses this by shifting to execution-focused interactions.
Section 03
The core philosophy eliminates redundant explanations to focus on direct execution. Key principles: zero token waste, high-fidelity output, developer speed first. SKILL.md defines input format, processing logic, output specs, and error handling for reusable skills.
Section 04
Designed for Gemini CLI, leveraging native tool calls (file operations/code analysis), multi-modal understanding (UI screenshots/diagrams), and context window optimization. Agent workflows enable autonomous task decomposition, state management, and integration with Git/Docker.
Section 05
Tahoe OS 26 demonstrates Antigravity's effectiveness: Liquid Glass engine (120fps refraction), hardware telemetry (battery/memory data), Intelligence 2.0 (writing tools/Genmoji). Gains: faster iteration, better code quality, lower API costs, improved maintainability.
Section 06
Suitable scenarios: high-frequency tasks, team collaboration, cost control, CI/CD automation. Suggestions: start simple, version control SKILL.md, share across teams, optimize continuously. Future plans: expand to other CLIs, IDE plugins, skill market, visualization tools.
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