v3.0.0 to v3.0.0

+ ---

+ name: gemini-agent-booster

+ description: "Master optimization protocol for Gemini Agent (Antigravity) to unlock native 2M+ long-context reasoning, Gemini 3.x thinking budget control, native context caching, Multimodal Live API protocols, and high-speed problem solving / Protokol optimasi utama untuk Gemini Agent (Antigravity) untuk mengaktifkan pemikiran long-context 2M+, kontrol thinking budget Gemini 3.x, context caching native, protokol Multimodal Live API, dan pemecahan masalah kecepatan tinggi."

+ author: "Roedy Rustam"

+ ---

+

+ # Gemini Agent Booster (2026 Edition — Gemini 3.x Ecosystem)

+

+ [English](#english) | [Bahasa Indonesia](#bahasa-indonesia)

+

+ ---

+

+ <a name="english"></a>

+ ## English

+

+ ### Orchestration & Integration

+ Connects and orchestrates with relevant domain skills like `brainstorming`, `zero-to-prod-orchestrator`, `ai-llm-integration-expert`, and `session-memory-manager` to ensure cohesive execution.

+

+ ### Description

+ Master optimization protocol for the Gemini Agent (Antigravity) to leverage native Gemini 3.x (Gemini 3.8 Flash, Gemini 3.5/3.1 Pro/Flash) capabilities — including 1M–2M token context window, dynamic thinking budget control, native context caching (`cachedContent`), Multimodal Live API integration, visual UI auditing, and parallel tool calling.

+

+ ### Trigger Conditions

+ - Analyzing very large codebases, full log histories, or monolithic documents requiring 1M–2M token context.

+ - Managing reasoning budgets with Gemini 3.x Thinking Mode (`thinkingConfig`).

+ - Implementing cost-saving strategies with native Gemini Context Caching (`cachedContent`).

+ - Performing real-time bidirectional multimodal audio/video or visual UI audits.

+ - Running deep research tasks requiring web search grounding + reasoning synthesis.

+ - Delegating complex multi-step tasks to parallel agent swarms or browser subagents.

+

+ ### Gemini 3.x Capability Matrix (2026)

+

+ | Capability | Gemini 3.1 / 3.5 Pro | Gemini 3.8 / 3.1 Flash |

+ |---|---|---|

+ | Context Window | Up to 2M tokens | 1M–2M tokens |

+ | Thinking / Reasoning | Extended Reasoning (Deep Think) | Flash Thinking (Configurable Budget) |

+ | Native Context Caching | Supported (`cachedContent`) | Supported (`cachedContent`) |

+ | Multimodal (Image/Video/Audio) | Native Multimodal | Native Multimodal + Live API |

+ | Code Generation & Tool Calling | State-of-the-Art Architecture | Ultra-fast iteration & subagents |

+ | Search Grounding | Google Search Grounding | Google Search Grounding |

+ | TTFT (Time to First Token) | Optimized for depth | 3–5x lower latency |

+ | Relative Cost Profile | Higher (for critical paths) | Ultra-low cost (ideal for high-frequency loops) |

+

+ ### 1. Thinking Budget Optimization for Frontier Tasks

+ For complex architectural decisions, security audits, or debugging race conditions, control the reasoning depth via `thinkingConfig`:

+ - **Dynamic Thinking Budget Allocation**: Allocate budgets dynamically based on task complexity classification.

+ - **Cost-Performance Tradeoff Matrix**: Balance costs between Flash Thinking, Extended 32k thinking, and Full Pro reasoning.

+ - **Tier Guidelines**:

+ - **Quick Fixes (2k)**: Linting, boilerplate, typo fixes.

+ - **Standard Dev (8k)**: Feature implementation, UI alignment.

+ - **Architecture Design (16k)**: Designing distributed schemas, refactoring core engines.

+ - **Critical System Design (32k)**: Evaluating cryptographic trade-offs, deeply complex race conditions.

+ - **Token Monitoring**: Actively monitor thinking tokens and track reasoning costs.

+ - **Reasoning Token Separation**: Ensure internal thinking tokens (`<thought>`) are isolated from client-facing output streams so that final responses remain crisp, clean, and token-efficient.

+

+ ### 2. Native Context Caching (`cachedContent`)

+ Reduce token costs by up to 75–90% and drastically cut latency on large repositories:

+ - **Threshold**: Cache prompts, repository snapshots, or API schemas larger than 32,768 tokens.

+ - **TTL Management**: Set appropriate time-to-live (TTL, e.g., 1–2 hours for active dev sessions, 24 hours for stable documentation).

+ - **Structure**:

+ ```typescript

+ // Native Gemini Context Caching Example

+ import { GoogleGenAI } from '@google/genai';

+ const ai = new GoogleGenAI({ apiKey: process.env.GOOGLE_API_KEY });

+

+ const cache = await ai.caches.create({

+ model: 'gemini-3.1-pro',

+ contents: [{ role: 'user', parts: [{ text: fullCodebaseDump }] }],

+ ttl: '3600s',

+ });

+

+ const response = await ai.models.generateContent({

+ model: 'gemini-3.1-pro',

+ contents: [{ role: 'user', parts: [{ text: 'Locate memory leak in worker thread' }] }],

+ cachedContent: cache.name,

+ });

+ ```

+

+ ### 3. 2M+ Token Long-Context Strategies

+ When inspecting massive codebases:

+ 1. **Pass Full File Trees**: Use `list_dir` to obtain the complete project structure, then supply full source files into context.

+ 2. **Whole-File Ingestion**: With 1M–2M context, avoid grep fragmentation; inspect complete classes and dependency trees in one shot.

+ 3. **Cross-Service Traceability**: Analyze upstream microservice contracts, protobufs, and frontend consumers concurrently in the same session.

+ 4. **Massive Server Logs**: Ingest complete production logs to uncover subtle intermittent race conditions and memory leaks.

+

+ ### 4. Multimodal Live API & Screen Grounding (Astra Paradigm)

+ Integrate real-time, low-latency multimodal interaction using Astra-paradigm patterns:

+ - **Bidirectional Streaming**: Stream audio input and receive audio/text responses over WebSockets using Gemini Multimodal Live API with sub-200ms interruption handling for conversational turn-taking.

+ - **Continuous Video Perception**: Process 60fps video streams with spatial grounding.

+ - **Spatial Memory Protocol**: Track object locations across video frames, maintaining a spatial state map.

+ - **Episodic Memory Buffer Management**: Compress video segments into episodic summaries stored beyond the context window.

+ - **Screen & UI Grounding**: Capture frames and map GUI interactions using exact screen grounding coordinates.

+ - **Code Example - Spatial Memory**:

+ ```typescript

+ // Astra Paradigm: Spatial Tracking

+ liveSession.on('frame', async (frame) => {

+ const locations = await ai.analyzeSpatialState(frame);

+ spatialMemory.updateCoordinates(locations);

+ });

+ ```

+ - **Visual UI Auditing Protocol**:

+ 1. Capture current running application (delegate to `browser-automation-expert` skill using Playwright/Stagehand).

+ 2. Audit layout, typography, contrast, and visual hierarchy against HIG and WCAG standards.

+ 3. Compare visually with target design using `generate_image` or design system guidelines. (Note: If `generate_image` is not available in the current environment, delegate to the `ai-media-generation-expert` skill for visual asset generation.)

+ 4. Perform targeted micro-edits to CSS/Tailwind tokens until alignment reaches pixel perfection.

+

+ ### 4.5 Gemini as Narrative Simulation Engine

+ Leveraging Gemini's 2M+ context window for persistent world-state in narrative simulations:

+ - **Persistent World-State**: Maintain complete environment state within the context window.

+ - **Character AI Persona Management**: Utilize system instructions to manage personality vectors and emotional states.

+ - **Multi-turn Narrative Coherence**: Use context caching to cache the world state and only stream new character interactions.

+ - **Cost Optimization**: Cache world-state/character definitions (75-90% cost reduction), only stream new dialogue/actions.

+ - **Integration Pattern**: Act as the "World Engine" coordinating specialized character agents.

+ - **Code Example - Cached World-State**:

+ ```typescript

+ const worldCache = await ai.caches.create({

+ model: 'gemini-3.1-pro',

+ contents: [{ role: 'system', parts: [{ text: fullWorldStateAndPersonas }] }],

+ ttl: '3600s',

+ });

+ const characterResponse = await ai.models.generateContent({

+ model: 'gemini-3.1-pro',

+ contents: [{ role: 'user', parts: [{ text: 'Character X walks into the tavern.' }] }],

+ cachedContent: worldCache.name,

+ });

+ ```

+

+ ### 5. Deep Research & Search Grounding

+ Gemini's native Search Grounding connects the agent directly to real-time web knowledge:

+ - Use Grounding for fresh library releases, breaking API deprecations, or zero-day CVE lookups.

+ - Synthesize findings with source attribution citations.

+

+ ### 6. Parallel Tool Execution

+ Gemini natively supports concurrent function calls:

+ - Read and edit multiple independent files in a single pass.

+ - Trigger parallel web searches or subagent workers simultaneously to minimize round-trip latency.

+

+ ---

+

+ <a name="bahasa-indonesia"></a>

+ ## Bahasa Indonesia

+

+ ### Integrasi Orkestrasi

+ Terhubung dan mengorkestrasi skill domain yang relevan seperti `brainstorming`, `zero-to-prod-orchestrator`, `ai-llm-integration-expert`, dan `session-memory-manager` untuk memastikan eksekusi yang kohesif.

+

+ ### Deskripsi

+ Protokol optimasi utama untuk Gemini Agent (Antigravity) memanfaatkan kapabilitas ekosistem Gemini 3.x (Gemini 3.8 Flash, Gemini 3.5/3.1 Pro/Flash) — termasuk context window 1M–2M token, kontrol dynamic thinking budget, native context caching (`cachedContent`), integrasi Multimodal Live API, audit visual UI, dan pemanggilan tool secara paralel.

+

+ ### Kondisi Pemicu

+ - Menganalisis codebase skala besar, histori log lengkap, atau dokumen monolitik yang membutuhkan konteks 1M–2M token.

+ - Mengatur alokasi reasoning budget dengan Gemini 3.x Thinking Mode (`thinkingConfig`).

+ - Menerapkan strategi pemangkasan biaya melalui native Gemini Context Caching (`cachedContent`).

+ - Menjalankan interaksi audio/video dua arah secara real-time atau audit visual UI.

+ - Menjalankan tugas riset mendalam dengan Google Search Grounding + sintesis penalaran.

+ - Mendelegasikan tugas multi-langkah ke swarm agen paralel atau browser subagent.

+

+ ### Matriks Kapabilitas Gemini 3.x (2026)

+

+ | Kapabilitas | Gemini 3.1 / 3.5 Pro | Gemini 3.8 / 3.1 Flash |

+ |---|---|---|

+ | Context Window | Hingga 2M token | 1M–2M token |

+ | Pemikiran / Penalaran | Extended Reasoning (Deep Think) | Flash Thinking (Configurable Budget) |

+ | Native Context Caching | Didukung (`cachedContent`) | Didukung (`cachedContent`) |

+ | Multimodal (Gambar/Video/Audio) | Native Multimodal | Native Multimodal + Live API |

+ | Generasi Kode & Tool Calling | Arsitektur State-of-the-Art | Iterasi & subagent ultra-cepat |

+ | Search Grounding | Google Search Grounding | Google Search Grounding |

+ | TTFT (Latensi Token Pertama) | Dioptimalkan untuk kedalaman | 3–5x lebih cepat |

+ | Profil Biaya | Lebih tinggi (untuk alur kritis) | Sangat hemat (ideal untuk perulangan cepat) |

+

+ ### 1. Thinking Budget Optimization for Frontier Tasks

+ Untuk keputusan arsitektur kompleks, audit keamanan, atau perbaikan race condition yang rumit, atur kedalaman penalaran via `thinkingConfig`:

+ - **Dynamic Thinking Budget Allocation**: Alokasikan budget secara dinamis berdasarkan klasifikasi kompleksitas tugas.

+ - **Cost-Performance Tradeoff Matrix**: Seimbangkan biaya antara Flash Thinking, Extended 32k thinking, dan Full Pro reasoning.

+ - **Panduan Tingkat Budget**:

+ - **Quick Fixes (2k)**: Perbaikan bug ringan, formatting, dan boilerplate.

+ - **Standard Dev (8k)**: Implementasi fitur, penyesuaian UI.

+ - **Architecture Design (16k)**: Mendesain skema terdistribusi, refaktor engine inti.

+ - **Critical System Design (32k)**: Evaluasi kriptografi, perbaikan race condition rumit.

+ - **Token Monitoring**: Pantau penggunaan thinking token dan lacak biaya penalaran.

+ - **Pemisahan Token Penalaran**: Pastikan token pemikiran internal (`<thought>`) dipisahkan dari aliran output pengguna agar respons akhir tetap ringkas, bersih, dan efisien token.

+

+ ### 2. Native Context Caching (`cachedContent`)

+ Pangkas biaya API sebesar 75–90% serta kurangi latensi respons pada repositori besar:

+ - **Ambang Batas**: Lakukan cache pada prompt, snapshot kode, atau skema dokumen yang melebihi 32.768 token.

+ - **Manajemen TTL**: Tetapkan masa aktif cache (misal: 1–2 jam untuk sesi development aktif, 24 jam untuk dokumentasi statis).

+ - **Contoh Implementasi**:

+ ```typescript

+ import { GoogleGenAI } from '@google/genai';

+ const ai = new GoogleGenAI({ apiKey: process.env.GOOGLE_API_KEY });

+

+ const cache = await ai.caches.create({

+ model: 'gemini-3.1-pro',

+ contents: [{ role: 'user', parts: [{ text: fullCodebaseDump }] }],

+ ttl: '3600s',

+ });

+ ```

+

+ ### 3. Strategi Long-Context 2M+ Token

+ Saat menganalisis repositori besar:

+ 1. **Pohon File Penuh**: Gunakan `list_dir` untuk memetakan struktur proyek, lalu masukkan seluruh file terkait ke dalam konteks.

+ 2. **Ingesti File Penuh**: Dengan jendela 1M–2M token, hindari fragmentasi grep; periksa seluruh class dan dependency tree secara menyeluruh.

+ 3. **Pelacakan Antar Layanan**: Analisis kontrak upstream microservice, skema database, dan frontend consumer secara bersamaan dalam satu sesi.

+ 4. **Log Produksi Lengkap**: Masukkan ratusan ribu baris log untuk mengungkap anomali memori dan race condition intermiten.

+

+ ### 4. Multimodal Live API & Screen Grounding (Astra Paradigm)

+ Integrasikan interaksi multimodal latensi rendah secara langsung menggunakan pola Astra-paradigm:

+ - **Streaming Dua Arah**: Streaming input suara dan terima respons audio/teks via WebSockets menggunakan Gemini Multimodal Live API dengan sub-200ms interruption handling untuk percakapan.

+ - **Continuous Video Perception**: Proses aliran video 60fps dengan spatial grounding.

+ - **Spatial Memory Protocol**: Lacak lokasi objek di seluruh frame video, mempertahankan peta status spasial.

+ - **Episodic Memory Buffer Management**: Kompresi segmen video menjadi ringkasan episodik di luar context window.

+ - **Screen & UI Grounding**: Tangkap frame layar dan petakan interaksi GUI menggunakan koordinat grounding layar yang presisi.

+ - **Protokol Audit UI Visual**:

+ 1. Ambil screenshot aplikasi yang sedang berjalan (delegasikan ke skill `browser-automation-expert` dengan Playwright/Stagehand).

+ 2. Audit tata letak, tipografi, kontras, dan konsistensi terhadap pedoman HIG dan WCAG.

+ 3. Bandingkan dengan referensi desain target menggunakan `generate_image`. (Catatan: Jika `generate_image` tidak tersedia, delegasikan ke skill `ai-media-generation-expert`.)

+ 4. Lakukan penyesuaian presisi pada token CSS/Tailwind hingga tampilan mencapai pixel-perfect.

+

+ ### 4.5 Gemini as Narrative Simulation Engine

+ Memanfaatkan context window 2M+ Gemini untuk status dunia yang persisten dalam simulasi naratif:

+ - **Persistent World-State**: Pertahankan status lingkungan lengkap dalam context window.

+ - **Character AI Persona Management**: Kelola vektor kepribadian dan status emosional via system instructions.

+ - **Multi-turn Narrative Coherence**: Gunakan context caching untuk world state dan hanya streaming interaksi karakter baru.

+ - **Cost Optimization**: Cache world-state/karakter (hemat biaya 75-90%), hanya memproses dialog/aksi baru.

+ - **Integration Pattern**: Bertindak sebagai "World Engine" yang mengoordinasikan agen karakter khusus.

+

+ ### 5. Penelitian Mendalam & Search Grounding

+ Search Grounding native Gemini menghubungkan agen langsung ke informasi web terkini:

+ - Gunakan Grounding untuk rilis pustaka terbaru, breaking change dokumentasi, atau audit kerentanan CVE terbaru.

+ - Sintesiskan temuan lengkap dengan sitasi sumber yang dapat diverifikasi.

+

+ ### 6. Eksekusi Tool Paralel

+ Gemini secara native mendukung pemanggilan banyak function call dalam satu giliran (turn):

+ - Baca dan modifikasi beberapa file independen sekaligus.