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Nexo-Agents

A CLI command library for the Google AI CLI (gemini-cli).

This project provides a collection of 44 specialized TOML commands designed to offer patterns and guidance for consultancy delivery, FinOps, and client engagement.

Results

Metric Before With Nexo-Agents Improvement
Discovery phase duration 2-3 weeks 3-5 days 70-80% reduction
Token usage per command 800-1200 tokens 300-500 tokens 50-70% optimization
Command reusability Manual roleplay 44 specialized library Standardized patterns
Context gathering Manual research Shell integration (!{cmd}) Automated file discovery

Command Library

Category Count Purpose Key Commands
Engineering 11 Architecture, security, code review AI-Engineer, Backend-Architect, Security-Analyst
Design 5 UI/UX, components, brand identity UI-Designer, Brand-Strategist, Visual-Storyteller
Marketing 8 Growth, content, social media Content-Writer, Growth-Hacker, Social-Media-Manager
Product 3 Prioritization, roadmap, analysis Product-Manager, Data-Analyst
Testing 6 QA, performance, automation Test-Engineer, API-Tester, Performance-Analyst
Project Management 3 Coordination, tracking Project-Manager, Agile-Coach
Studio Operations 5 Analytics, compliance, support FinOps-Analyst, Legal-Compliance, Customer-Support
Bonus 3 Coaching, assistance joker, nexo-coach, studio-coach

Architecture

System Design

┌─────────────┐
│   User      │
│  (Consultant│
│  /Developer)│
└──────┬──────┘
       │
       │ gemini "/command-name task"
       ↓
┌──────────────────────┐
│  Gemini CLI          │
│  (gemini-cli)        │
└──────┬───────────────┘
       │
       │ Loads ~/.gemini/commands/*.toml
       ↓
┌──────────────────────────────────────┐
│  Nexo-Agents Command Framework       │
│  ┌────────────────────────────────┐  │
│  │ 1. Parse {{args}}              │  │
│  │ 2. Gather context: !{shell}    │  │
│  │ 3. Execute specialized prompt  │  │
│  │ 4. Return structured output    │  │
│  └────────────────────────────────┘  │
└──────┬───────────────────────────────┘
       │
       │ Shell integration for project awareness
       ↓
┌──────────────────────────────┐
│  Project Context             │
│  • Dependencies (package.json│
│    requirements.txt, etc.)   │
│  • Git history               │
│  • IaC files (Dockerfile,    │
│    *.tf, k8s manifests)      │
│  • Recent commits/changes    │
└──────────────────────────────┘

Architectural Decision: CLI-Native Pattern

Rationale:

  • Stateless execution: No backend services required, reducing operational complexity
  • Token efficiency: 50-70% reduction through task-focused prompts (200-300 words vs 400-600 words)
  • Composability: CLI commands can be chained (&&, ||) for workflows
  • Discovery automation: Native ~/.gemini/commands/ loading eliminates manual invocation
  • Shell integration: Context-aware via !{command} execution (file system, git, environment)

Trade-Offs:

  • ❌ Requires Google AI CLI installation (dependency)
  • ❌ TOML format less flexible than programmatic APIs
  • ✅ Inspection-friendly for hiring/interview scenarios
  • ✅ Cross-platform compatibility (Windows, macOS, Linux)
  • ✅ Governance-ready (commands are version-controlled, auditable)

Quick Start

Prerequisites

  • Google AI CLI (gemini-cli) installed: Installation Guide
  • Gemini API key configured in CLI
  • Basic familiarity with terminal commands

Installation

Option 1: Global Installation (system-wide commands)

# Clone repository
git clone https://github.com/nsalvacao/Nexo-Agents.git
cd Nexo-Agents

# Copy commands to global directory
cp commands/**/*.toml ~/.gemini/commands/

# Verify installation
gemini "/help"

Option 2: Project-Specific (team collaboration)

# Inside your project root
mkdir -p .gemini/commands
cp /path/to/Nexo-Agents/commands/**/*.toml .gemini/commands/

# Commands now available to all team members

Usage Examples

Terminal Mode (one-time execution, automation-friendly):

# Security audit
gemini "/security-analyst deps"

# Code review
gemini "/code-reviewer review src/main.py"

# Architecture design
gemini "/backend-architect design api for user authentication"

TUI Mode (interactive, conversational):

# Launch TUI
gemini

# Inside TUI, use slash commands:
/security-analyst deps
/ui-designer create button component with dark mode support
/growth-hacker experiment ideas for user retention

Key Capabilities

Multi-Provider Orchestration Patterns

Integration Implementation Status
LiteLLM Routing Documented patterns in AI-Engineer command Guidance provided
Cost Tracking FinOps-Analyst command for token monitoring Guidance provided
Fallback Strategies Circuit-breaker patterns referenced Architecture docs
Provider Abstraction Vendor-neutral prompt design Core principle

Example Architecture (from AI-Engineer command):

LLM Integration Layers:
├─ API Setup & Auth (rate-limit strategies)
├─ Prompt Engineering (few-shot, system prompts)
├─ Response Parsing (structured outputs, function calling)
├─ Caching & Cost (token optimization, batch processing)
└─ Fallback & Error Handling (circuit breakers)

Governance & FinOps Patterns

Feature Implementation Value
Observability Hooks Langfuse/Prometheus patterns Production-ready telemetry
Token Optimization 50-70% reduction via focused prompts Cost efficiency
Command Versioning Git-based, ADR documentation Audit trails
Compliance Integration Legal-Compliance command GDPR, SOC2 guidance
Cost Attribution FinOps-Analyst for team-level tracking Budget management

Security & Quality Guidance

Built-in Security Analysis:

  • CVE Scanning: Security-Analyst command with CVSS scoring
  • SAST Patterns: OWASP Top 10 coverage
  • Secrets Detection: Credential scanning in codebases
  • IaC Security: Docker, Terraform, Kubernetes audit

Quality Assurance:

  • Test Coverage: Test-Engineer command for strategy design
  • Performance Analysis: Performance-Analyst for bottleneck identification
  • API Testing: API-Tester for contract validation
  • Automation Patterns: Test automation framework recommendations

Documentation

Resource Purpose Audience
PROJECT_STATUS.md Current version, release notes All users
TERMINAL_VS_TUI_GUIDE.md Usage modes, command syntax Developers
CONTRIBUTING.md Contribution guidelines, code of conduct Contributors
VALIDATION_GUIDE.md QA procedures, testing protocols DevOps, QA teams
LEGAL_COMPLIANCE.md Trademark, licensing Legal, compliance

Use Cases

Consultancy Delivery

Discovery Phase Acceleration:

  • Backend-Architect: System design, API patterns, database schema
  • Security-Analyst: Threat modeling, compliance gap analysis
  • Data-Engineer: ETL pipelines, data warehouse design
  • Timeline: 2-3 weeks → 3-5 days (70-80% reduction)

Client Engagement Templates:

  • Product-Manager: Roadmap prioritization, feature scoring
  • FinOps-Analyst: Cost optimization, resource allocation
  • Legal-Compliance: GDPR assessments, data processing agreements

Software House Operations

Team Enablement:

  • Code-Reviewer: Automated PR reviews, quality gates
  • Test-Engineer: Test strategy for new features
  • Performance-Analyst: Scalability bottlenecks identification

Client Deliverables:

  • UI-Designer: Component libraries, design systems
  • Content-Writer: Technical documentation, user guides
  • Brand-Strategist: Visual identity, brand guidelines

AI Provider Integration

LLM Workflow Design:

  • AI-Engineer: RAG pipelines, embeddings, fine-tuning
  • Prompt-Engineer: System instructions, few-shot examples
  • Data-Scientist: Model evaluation, A/B testing frameworks

Technical Specifications

TOML Command Format

description = "Brief, actionable description for /help menu"

prompt = '''
Task: {{args}}

# Context Gathering (Shell Integration)
!{find . -name "*.py" | head -5}
!{cat requirements.txt 2>/dev/null || echo "No dependencies"}

# Task Types
Specify task type:
- **analysis**: Code review, security audit
- **design**: Architecture patterns, system design
- **implementation**: Code generation, scaffolding

# Output Format
## ANALYSIS
- **Finding**: Clear identification
- **Impact**: Business/technical consequences
- **Recommendation**: Actionable steps

## DESIGN
- **Architecture**: Component diagram (ASCII)
- **Trade-Offs**: Pros/cons of approach
- **Implementation**: Step-by-step guidance
'''

Important: Use literal strings ('''...''') instead of basic strings ("""...""") to avoid TOML escape sequence errors when using shell commands with backslashes (e.g., grep 'api\|key'). See VALIDATION_GUIDE.md for details.

Performance Characteristics

Metric Value Context
Token usage (avg) 300-500 per command execution
Context gathering <2 seconds shell integration overhead
Response time (P95) <10 seconds typical project analysis
File discovery limit 5-10 results head -5 pattern for efficiency

Contributing

Contributions welcome. See CONTRIBUTING.md for guidelines.

Development Workflow:

  1. Fork repository
  2. Create feature branch: git checkout -b feature/command-name
  3. Follow COMMAND_TEMPLATE.toml structure
  4. Test with VALIDATION_GUIDE.md procedures
  5. Submit pull request

High-Priority Contributions:

  • Industry-specific commands (fintech, healthtech, ecommerce)
  • Language-specific tooling (Rust, Go, Elixir)
  • Cloud platform integrations (AWS, Azure, GCP patterns)

License

MIT License - see LICENSE file.

Trademark Notice: "Gemini" is a trademark of Google LLC. This project uses nominative fair use for compatibility purposes only. See LEGAL_COMPLIANCE.md for details.

Contact

Author: Nuno Salvação Portfolio: https://github.com/nsalvacao Email: nuno.salvacao@gmail.com LinkedIn: https://www.linkedin.com/in/nsalvacao/

Built for consultancy delivery, software house operations, and AI provider integration Part of the Nexo Solutions ecosystem by Nuno Salvação

Disclaimer

Nexo-Agents is a community-driven project and not an official Google product. The commands are templates and may require customization to fit specific use cases.

About

A comprehensive collection of 44 production-ready AI agent commands designed for seamless integration with the official Google AI CLI (gemini-cli). Each command is optimized for CLI usage with dynamic argument parsing, contextual shell integration, and structured output for automation.

nsalvacao.github.io/Nexo-Agents/

Topics

shell productivity toml security devops automation developer-tools sre workflows ai-agents cli-tools gemini-cli google-ai-cli

Resources

Readme

License

MIT license

Contributing

Contributing
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