git:20260907.0ae92d0 to v2.8.0

1 added, 0 removed. Audit A to A.

---

name: gemini-agent-booster

+ version: "2.8.0"

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: "vibes-plug-swarm"

---

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

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

---

## English

### Orchestration & Integration

Connects and orchestrates with relevant domain skills like `brainstorming`, `zero-to-prod-orchestrator`, `ai-llm-integration-expert`, and `project-context-mapper` 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. Dynamic Thinking Budget & Reasoning Protocol

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

- **Flash Thinking for Rapid Tasks**: Set lower or default thinking budgets for quick bug fixes, linting, and boilerplate generation.

- **Extended Thinking for Critical Paths**: Allocate high thinking budgets (e.g. 8k–32k thinking tokens) when designing distributed schemas, refactoring core engines, or evaluating cryptographic trade-offs.

- **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

const cache = await ai.createCachedContent({

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

Integrate real-time, low-latency multimodal interaction:

- **Bidirectional Streaming**: Stream audio input and receive audio/text responses over WebSockets using Gemini Multimodal Live API.

- **Screen & UI Grounding**: Capture frames from browser subagents or desktop windows; Gemini grounds user queries directly to coordinate points on screen.

- **Visual UI Auditing Protocol**:

1. Capture current running application via `browser_subagent`.

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.

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

### 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.

---

## Bahasa Indonesia

### Integrasi Orkestrasi

Terhubung dan mengorkestrasi skill domain yang relevan seperti `brainstorming`, `zero-to-prod-orchestrator`, `ai-llm-integration-expert`, dan `project-context-mapper` 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. Dynamic Thinking Budget & Protokol Penalaran

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

- **Flash Thinking untuk Tugas Cepat**: Gunakan alokasi budget penalaran default atau rendah untuk perbaikan bug ringan, formatting, dan boilerplate.

- **Extended Thinking untuk Alur Kritis**: Alokasikan budget penalaran tinggi (misal: 8k–32k thinking tokens) saat mendesain skema terdistribusi, refaktor engine inti, atau evaluasi kriptografi.

- **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

const cache = await ai.createCachedContent({

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

Integrasikan interaksi multimodal latensi rendah secara langsung:

- **Streaming Dua Arah**: Streaming input suara dan terima respons audio/teks via WebSockets menggunakan Gemini Multimodal Live API.

- **Screen & UI Grounding**: Tangkap frame layar dari browser subagent; Gemini memetakan perintah ke koordinat visual yang presisi di layar.

- **Protokol Audit UI Visual**:

1. Ambil screenshot aplikasi yang sedang berjalan via `browser_subagent`.

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

3. Bandingkan dengan referensi desain target menggunakan `generate_image`.

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

### 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.

- Jalankan pencarian web atau spawn subagent pekerja secara simultan guna meminimalkan total round-trip latency.