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Lynkr AI Routing Proxy

作者 Vishal Veera Reddy · GitHub ↗ · v0.6.0 · MIT-0
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在 OpenClaw 中安装
/install lynkr
功能描述
Intelligent LLM routing proxy with complexity-based tier routing, agentic workflow detection, and multi-provider failover. Drop-in replacement for direct pro...
使用说明 (SKILL.md)

Lynkr - Intelligent LLM Routing Proxy

Lynkr routes AI coding requests to the best available model based on task complexity, cost, and provider health. It supports 12+ providers and works as an OpenAI-compatible proxy.

Quick Start

npm install -g lynkr
lynkr --port 8081

Then point your AI coding tool at http://localhost:8081/v1.

How It Works

  1. Complexity Analysis - Scores each request 0-100 based on token count, tool usage, code patterns, and domain keywords
  2. Tier Routing - Maps score to a tier (SIMPLE/MEDIUM/COMPLEX/REASONING), each configured with a specific provider:model
  3. Agentic Detection - Detects multi-step workflows (tool loops, autonomous agents) and upgrades to higher tiers
  4. Cost Optimization - Picks the cheapest provider that can handle the tier
  5. Circuit Breaker + Failover - Automatic failover when a provider is down

Configuration for OpenClaw

Set tier routing in your environment:

MODEL_PROVIDER=ollama
TIER_SIMPLE=ollama:qwen2.5-coder:7b
TIER_MEDIUM=openrouter:anthropic/claude-sonnet-4-20250514
TIER_COMPLEX=bedrock:anthropic.claude-sonnet-4-20250514-v1:0
TIER_REASONING=bedrock:anthropic.claude-sonnet-4-20250514-v1:0

OpenClaw Mode

When running under OpenClaw, enable model name rewriting so the actual provider and model appear in responses:

OPENCLAW_MODE=true

This replaces the generic model: "auto" in responses with the actual provider/model that handled the request (e.g., ollama/qwen2.5-coder:7b or bedrock/claude-sonnet-4).

Provider Registration

Add to your openclaw.json:

{
  "models": {
    "providers": [
      {
        "name": "lynkr",
        "type": "openai-compatible",
        "base_url": "http://localhost:8081/v1",
        "api_key": "any-value",
        "models": ["auto"]
      }
    ]
  },
  "agents": {
    "defaults": {
      "models": {
        "primary": "lynkr/auto",
        "fallback": "lynkr/auto"
      }
    }
  }
}

Features

  • 12+ providers: Ollama, OpenAI, Anthropic (Azure/Bedrock/Direct), OpenRouter, Vertex, Moonshot, Z.AI, LM Studio, llama.cpp
  • Smart routing: Heuristic + optional BERT-based complexity classification
  • Tool support: Server-side tool execution with IDE-aware tool mapping (Cursor, Cline, Continue, Codex)
  • Session management: Persistent sessions with cross-request deduplication
  • Observability: Prometheus metrics, circuit breaker status, routing decision headers (X-Lynkr-*)
  • Agent-aware: X-Agent-Role header for multi-agent framework routing hints
  • Lazy tool loading: On-demand tool registration for fast startup
  • History compression: Automatic conversation trimming for long sessions

Response Headers

Every response includes routing metadata:

Header Description
X-Lynkr-Provider Provider that handled the request
X-Lynkr-Model Model used
X-Lynkr-Tier Complexity tier (SIMPLE/MEDIUM/COMPLEX/REASONING)
X-Lynkr-Complexity-Score Numeric score 0-100
X-Lynkr-Routing-Method How the route was decided
X-Lynkr-Cost-Optimized Whether cost optimization changed the provider
安全使用建议
This skill appears to be a legitimate LLM routing proxy, but several things don't add up. Before installing or running it: 1) Inspect the actual npm package and GitHub repository (verify maintainer, recent commits, and code) rather than relying only on SKILL.md. 2) Confirm how provider API keys are configured and stored — do not run an unauthenticated public proxy. 3) Be cautious about installing a global npm package and running it as a service — review the package contents and any startup scripts. 4) If you enable OPENCLAW_MODE, understand it will expose the actual provider/model names in responses (possible metadata leakage). 5) Because the SKILL.md mentions server-side tool execution, limit network exposure and run it in an isolated environment until you’ve audited its behavior. Providing the repository URL, package tarball, or the lynkr source code would materially increase confidence and allow a more precise assessment.
功能分析
Type: OpenClaw Skill Name: lynkr Version: 0.6.0 The skill bundle describes 'Lynkr', an LLM routing proxy designed to optimize provider usage based on task complexity and cost. The documentation in SKILL.md and metadata in _meta.json provide standard installation and configuration instructions for integration with OpenClaw, with no evidence of malicious code, data exfiltration, or harmful prompt injection attempts.
能力评估
Purpose & Capability
The skill's name and description (an LLM routing proxy) match the SKILL.md content (tier routing, complexity scoring, multi-provider). However the registry metadata at the top of the evaluation says 'Required binaries: none' while the SKILL.md itself declares node >=18 and an npm package (lynkr) — an inconsistency between manifest metadata and the runtime instructions.
Instruction Scope
SKILL.md instructs installing a global npm package (npm install -g lynkr) and running a local proxy, plus enabling features like server-side tool execution and OPENCLAW_MODE which rewrites model names in responses. Those instructions imply executing third-party code and possibly server-side tool invocation (command execution), but the skill does not declare how or where provider credentials are configured. The doc also suggests adding an 'api_key' value of 'any-value' for openclaw.json, which is ambiguous and could enable an unauthenticated or misconfigured proxy if followed literally.
Install Mechanism
There is no formal install spec in the registry entry (instruction-only), but SKILL.md tells operators to use npm to install a published 'lynkr' package. Installing a public npm package is a standard workflow but carries inherent risk (you are executing third-party code); the instruction does not point to a verified release URL or checksum. This is moderate risk but expected for an npm-distributed tool.
Credentials
The skill declares no required environment variables in the metadata, yet the SKILL.md shows multiple env vars (MODEL_PROVIDER, TIER_* entries, OPENCLAW_MODE) and implies the proxy will use provider-specific credentials to call many cloud providers. The manifest omits any requirement for provider API keys or guidance on securely supplying them; the provided openclaw.json snippet uses 'api_key':'any-value', which is ambiguous and could encourage insecure deployment. Requesting no secrets in metadata while supporting many providers is inconsistent and should be clarified.
Persistence & Privilege
The skill is not marked always:true and does not request special persistent privileges in the registry metadata. It is user-invocable and can be invoked autonomously by the agent (default), which is expected for skills.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install lynkr
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /lynkr 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.6.0
Initial release - intelligent LLM routing with 12+ providers
元数据
Slug lynkr
版本 0.6.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Lynkr AI Routing Proxy 是什么?

Intelligent LLM routing proxy with complexity-based tier routing, agentic workflow detection, and multi-provider failover. Drop-in replacement for direct pro... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 99 次。

如何安装 Lynkr AI Routing Proxy?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install lynkr」即可一键安装,无需额外配置。

Lynkr AI Routing Proxy 是免费的吗?

是的,Lynkr AI Routing Proxy 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Lynkr AI Routing Proxy 支持哪些平台?

Lynkr AI Routing Proxy 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Lynkr AI Routing Proxy?

由 Vishal Veera Reddy(@vishalveerareddy123)开发并维护,当前版本 v0.6.0。

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