Delegate large context and multimodal tasks to Gemini CLI. Use when context exceeds 100K tokens, analyzing images/screenshots, processing large codebases, or for speed/cost-sensitive operations. Triggers on "delegate to gemini", "route to gemini", "use gemini", "large context", "analyze image", "screenshot analysis".
Scanned 5/28/2026
Install via CLI
openskills install nexus-substrate/nexus-agents---
name: gemini-delegator
description: |
Delegate large context and multimodal tasks to Gemini CLI.
Use when context exceeds 100K tokens, analyzing images/screenshots,
processing large codebases, or for speed/cost-sensitive operations.
Triggers on "delegate to gemini", "route to gemini", "use gemini",
"large context", "analyze image", "screenshot analysis".
allowed-tools: Bash, Read, Grep, Glob
---
# Gemini Delegator Skill
<!-- CANONICAL SOURCES:
- docs/architecture/ROUTING_SYSTEM.md
- packages/nexus-agents/src/mcp/tools/delegate-to-model.ts
- skills/references/orchestration-patterns.md (multi-agent coordination, retry policies, deadline propagation)
-->
**Full documentation:**
- [ROUTING_SYSTEM.md](../../docs/architecture/ROUTING_SYSTEM.md)
## Real-World Performance (Tested 2026-01-18)
| Metric | Value | Notes |
| ------------------ | ------------------------- | ----------------------------------- |
| Max files analyzed | 978 files in single query | ~280k LOC processed successfully |
| Latency (simple) | 10-15 seconds | Single directory analysis |
| Latency (complex) | 58-73 seconds | Full codebase analysis |
| Cache efficiency | 94k tokens cached | Significant cost savings |
| Tool calls/session | Up to 20 | File reads auto-executed |
| Model routing | flash-lite → pro | Two-model approach for optimization |
## When to Delegate to Gemini
| Condition | Threshold/Criteria | Reason |
| ------------------------- | -------------------------- | --------------------------- |
| Context size | > 100K tokens | Gemini: 1M context window |
| Large codebase analysis | Multiple files, > 50 files | Fast bulk processing |
| Image/screenshot analysis | Any visual content | Native multimodal support |
| Video/audio processing | Any A/V content | Native multimodal support |
| Speed-critical tasks | Latency sensitive | Flash models optimized |
| Cost-sensitive operations | Budget constraints | Generous free tier (1K/day) |
| Google Cloud integration | BigQuery, Cloud Functions | Native integration |
## When NOT to Delegate
- Complex reasoning requiring deep analysis
- Security-critical implementations
- Production code generation needing high quality
- Tasks requiring careful planning and architecture
## Methods
### Method 1: delegate_to_model MCP Tool
Use the nexus-agents MCP tool for intelligent routing:
```bash
# The tool analyzes task and recommends optimal model
nexus-agents delegate_to_model --task "Analyze this 500K token codebase"
```
### Method 2: Direct Gemini CLI
```bash
# Basic delegation (human-readable output)
gemini -p "Analyze this codebase"
# JSON output for parsing (note: response may contain markdown fences)
gemini -p "Analyze this codebase" --output-format json
# With auto-approve for autonomous operation
gemini --yolo -p "Review all files in src/" --output-format json
# Specify model
gemini -m gemini-2.5-flash -p "Quick analysis task"
gemini -m gemini-3-pro-preview -p "Complex reasoning task"
```
**JSON Output Parsing Note:** The `response` field in JSON output may contain markdown code fences. Parse accordingly:
````typescript
const result = JSON.parse(output);
const response = result.response.replace(/```\w*\n?/g, '').trim();
````
## Multimodal Examples
### Image Analysis
```bash
# Analyze screenshot
gemini -p "Describe this UI and identify usability issues" < screenshot.png
# Analyze architecture diagram
gemini -p "Extract components and relationships from this diagram" < diagram.png
# Code screenshot OCR
gemini -p "Extract the code from this screenshot" < code-image.png
```
### Video Analysis
```bash
# Analyze video content (uses File API for > 1 minute)
gemini -p "Summarize the key points from this demo video" < demo.mp4
```
### Batch Processing
```bash
# Process multiple images
for img in screenshots/*.png; do
gemini -p "Analyze this UI screenshot" < "$img" --output-format json >> results.json
done
```
## Context Advantage
| Model | Context Window | Best For |
| ------------ | -------------- | ------------------------- |
| Claude | ~200K tokens | Quality reasoning |
| Gemini Pro | 1M tokens | Large context, multimodal |
| Gemini Flash | 200K-1M tokens | Speed, high volume |
**The 1M token context window enables:**
- Entire codebase analysis in single context
- Full documentation sets without chunking
- Complete git history review
- Large data file processing
## Output Formats
```bash
# Human readable (default)
gemini -p "task"
# JSON for parsing
gemini -p "task" --output-format json
# Streaming JSON for real-time
gemini -p "task" --output-format stream-json
```
## Process
1. **Evaluate task requirements:**
- Estimate context size
- Check for multimodal content
- Assess speed/cost sensitivity
2. **Choose delegation method:**
- Use `delegate_to_model` for intelligent routing
- Use direct Gemini CLI for explicit control
3. **Configure execution:**
- Select appropriate model (Pro vs Flash)
- Set output format for parsing
- Use `--yolo` for autonomous tasks
4. **Process results:**
- Parse JSON output
- Integrate findings into workflow
## Quick Reference
```bash
# Large context analysis
gemini -p "Analyze this entire codebase structure" --yolo
# Screenshot analysis
gemini -p "What does this UI show?" < screenshot.png
# Fast iteration
gemini -m gemini-2.5-flash -p "Quick review" --output-format json
# Cost-sensitive batch
for f in *.ts; do gemini -p "Review: $(cat $f)" >> reviews.txt; done
```
## Anti-rationalization — Gemini delegation
| Excuse | Counter |
| --------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------- |
| "Gemini for everything, it has a big context" | Big context isn't free — output quality varies by task. Use Gemini for >100k context, multimodal, or research-shaped tasks. |
| "Skip the multimodal check" | If the task includes images, Gemini is the canonical CLI. Other CLIs may text-summarize via OCR but lose information. |
| "I'll use Gemini even for short code-gen" | Codex is faster on code. Use Gemini when context size or multimodal forces the choice. |
## Red flags
- Gemini used for short single-file code-gen (Codex is faster)
- Multimodal task routed to a non-Gemini CLI without explicit reason
- Context exceeded 1M without verification of token budget
## Verification checklist
- [ ] Task category matches Gemini's strengths (large context, research, multimodal)
- [ ] Token estimate confirmed within Gemini's context window before dispatch
- [ ] Outcome recorded for adaptive routing
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