Co-Pilot / 辅助式
更新于 24 days ago

omni-dev-fusion

Ttao3k
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tao3k/omni-dev-fusion
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💡 摘要

Omni-Dev-Fusion是一个代理操作系统内核,通过基于技能的命令自动化软件开发生命周期。

🎯 适合人群

寻求自动化工具的软件开发人员管理CI/CD管道的DevOps工程师需要动态技能获取的数据科学家监督开发工作流程的技术项目经理探索基于代理系统的AI研究人员

🤖 AI 吐槽:看起来很能打,但别让配置把人劝退。

安全分析中风险

风险:Medium。建议检查:是否执行 shell/命令行指令;是否发起外网请求(SSRF/数据外发);API Key/Token 的获取、存储与泄露风险;文件读写范围与路径穿越风险。以最小权限运行,并在生产环境启用前审计代码与依赖。

Omni-Dev-Fusion Fusion

From Copilot to Autopilot: Building the Agentic OS for the post-IDE era.

Omni-Dev-Fusion Fusion is an Agentic OS kernel that bridges the gap between human intent and machine execution. By integrating the innovative Tri-MCP Tri-Core Architecture, Fusion strictly separates cognitive planning (Brain/Orchestrator), atomic execution (Hands/Executor), and precision coding (Pen/Coder) at the physical layer.

With Nix for absolute environment reproducibility and a rigorous "Legislation-Execution" policy engine, Fusion empowers AI to autonomously handle the complete SDLC—from architectural design to AST-level refactoring.

One Tool Architecture

Fusion uses a single MCP tool entry point with infinite skill commands:

@omni("git.status") # Get git status @omni("git.commit", {...}) # Commit with cog validation @omni("file.read", {...}) # Read file @omni("help") # Show all skills

| Pattern | Example | Dispatches To | | --------------- | ------------ | ------------------ | | skill.command | git.status | git.git_status() | | skill | git | Shows skill help |

Skill Network (Git Installer)

Omni can now download and install skills from Git repositories at runtime, enabling true capability expansion:

# Install a skill from GitHub omni skill install https://github.com/omni-dev/skill-pandas # Install specific version omni skill install https://github.com/omni-dev/skill-docker --version v2.1.0 # Update an installed skill omni skill update pandas-expert # List all installed skills omni skill list # Show skill details omni skill info pandas-expert

Skill Management Commands

| Command | Description | | -------------------------------------------------------------- | ---------------------------------- | | omni skill install <url> | Install skill from Git URL | | omni skill install <url> --name <name> | Install with custom name | | omni skill install <url> --version <ref> | Install specific branch/tag/commit | | omni skill update <skill> | Update skill to latest | | omni skill update <skill> --strategy stash\|abort\|overwrite | Update with conflict handling | | omni skill list | List all installed skills | | omni skill info <skill> | Show skill manifest and lockfile |

How It Works

  1. Clone/Update: Uses GitPython + subprocess for reliable Git operations
  2. Sparse Checkout: Supports monorepo subdirectory installation
  3. Dependency Detection: Prevents circular dependencies during install
  4. Lockfile: Generates .omni-lock.json for reproducible installs
  5. Dirty Handling: Stashes local changes, pulls, then pops (stash strategy)

Cascading Templates & Skill Structure Validation

Omni supports cascading templates with "User Overrides > Skill Defaults" pattern:

# Check skill structure omni skill check # Check all skills omni skill check git # Check specific skill omni skill check git --examples # With structure examples # Manage templates (cascading pattern) omni skill templates list git # List templates with source omni skill templates eject git commit_message.j2 # Copy default to user dir omni skill templates info git commit_message.j2 # Show template content # Create new skill from template omni skill create my-skill --description "My new skill"

Cascading Template Pattern

# Priority 1: User Overrides (assets/templates/{skill}/)
assets/templates/git/
├── commit_message.j2     # Custom template (highest priority)

# Priority 2: Skill Defaults (assets/skills/{skill}/templates/)
assets/skills/git/templates/
├── commit_message.j2     # Skill default (fallback)
├── workflow_result.j2
└── error_message.j2

Skill Structure Validation

🔍 git

✅ Valid: True
📊 Score: 100.0%
📁 Location: assets/skills/git

## 📁 Structure
├── SKILL.md              # Required
├── scripts/              # Required (commands.py with @skill_command)
├── templates/            # Optional (cascading)
└── tests/                # Optional (zero-config)

JIT Skill Acquisition

Omni can dynamically discover and install skills when you need capabilities not currently loaded:

# Discover skills matching a query @omni("skill.discover", {"query": "data analysis", "limit": 5}) # Get task-based suggestions @omni("skill.suggest", {"task": "analyze pcap file"}) # Install and load a skill @omni("skill.jit_install", {"skill_id": "network-analysis"}) # List all known skills @omni("skill.list_index")

Workflow: Acquiring a New Capability

User: "Analyze this pcap file"

You: @omni("skill.suggest", {"task": "analyze pcap file"})
     → Found: network-analysis (keywords: pcap, network, wireshark)

     @omni("skill.jit_install", {"skill_id": "network-analysis"})
     → ✅ Installed and loaded!

     Ready to analyze your pcap file.

Available Skills in Index (20 skills)

| Skill ID | Description | Keywords | | ------------------ | ----------------------------------------- | ---------------------------------- | | pandas-expert | Advanced pandas data manipulation | pandas, dataframe, data-analysis | | docker-ops | Docker container management | docker, containers, kubernetes | | network-analysis | PCAP analysis and network troubleshooting | pcap, network, wireshark | | ml-pytorch | Machine learning with PyTorch | pytorch, ml, deep-learning | | aws-cloud | AWS cloud services management | aws, ec2, s3, lambda | | database-sql | SQL database operations | sql, postgres, mysql, query | | video-processing | FFmpeg video transcoding | video, ffmpeg, transcoding | | rust-systems | Rust systems programming | rust, wasm, systems | | graphql-api | GraphQL schema design | graphql, api, schema | | terraform-infra | Infrastructure as Code | terraform, infrastructure, iac | | security-audit | Security vulnerability scanning | security, vulnerability, audit | | regex-master | Regular expression parsing | regex, pattern, text | | http-client | HTTP requests and API testing | http, api, rest, curl | | git-advanced | Advanced git operations | git, rebase, bisect, workflow | | shell-scripting | Bash/shell scripting | bash, shell, scripting, automation | | cryptography | Encryption and cryptographic ops | crypto, encryption, hash | | testing-pytest | Python testing with pytest | pytest, testing, coverage | | async-python | Python async/await programming | async, asyncio, concurrency | | fastapi-web | FastAPI web framework | fastapi, web, api, openapi | | image-processing | PIL/Pillow image manipulation | image, pillow, png, jpeg |

Key Features

  1. Weighted Scoring: Keywords (+10), ID (+8), Name (+5), Description (+2)
  2. Auto-Load: Skills are automatically loaded after installation
  3. Index-Based: Uses known_skills.json for reliable discovery

Vector-Enhanced Discovery (Virtual Loading)

Omni now uses LanceDB-based vector search for intelligent skill discovery with semantic matching:

# Reindex all skills into vector store omni skill reindex omni skill reindex --clear # Full rebuild # Show index statistics omni skill index-stats # Search local skills only @omni("skill.discover", {"query": "docker containers", "local_only": true}) # Get task-based suggestions @omni("skill.suggest", {"task": "analyze nginx logs"})

Routing Flow

User Request
    ↓
1. Semantic Cortex (fuzzy cache)
2. Exact Match Cache
3. LLM Routing (Hot Path)
4. Vector Fallback (Cold Path) ← NEW
    - Only searches LOCAL skills (installed_only=True)
    - Returns suggested_skills in RoutingResult

How It Works

  • Index Source: SKILL.md files are parsed and embedded
  • Storage: LanceDB table skills (via omni-vector)
  • Query: Semantic similarity search with metadata filtering
  • Fallback: Triggered when LLM confidence < 0.5 or uses generic skills

Vector Fallback Example

# User: "write documentation about this project" # LLM returns: confidence=0.7, selects generic "writer" skill # Vector Fallback triggers # Searches for "write documentation" in local skills # Finds: documentation (score=0.92) # Result: # { # "selected_skills": ["writer"], # "suggested_skills": ["documentation"], # NEW! # "confidence": 0.85, # Boosted # "reasoning": "... [Vector Fallback] Found local skill: documentation" # }

Available Commands

| Command | Description | | ------------------------ | -------------------------- | | omni skill reindex | Rebuild vector index | | omni skill index-stats | Show index statistics | | skill.discover | Semantic skill search | | skill.suggest | Task-based recommendations | | skill.reindex | Rebuild index (tool) |

See Developer Guide for detailed architecture documentation.

Hot Reload & Index Sync

Omni now supports zero-downtime skill reloading wi

五维分析
清晰度8/10
创新性9/10
实用性9/10
完整性8/10
可维护性7/10
优缺点分析

优点

  • 高度灵活的技能管理
  • 支持动态技能发现
  • 与Git集成以进行版本控制
  • 促进可重现的环境

缺点

  • 复杂性可能会让新用户感到不知所措
  • 依赖外部Git仓库
  • 更新时可能会出现版本冲突
  • 需要理解技能架构

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版权归原作者所有 tao3k.