ClawRouter — 技能 — openclaw中文资讯站

技能详情（站内镜像，无评论）

Smart LLM router — save 67% on inference costs. Routes every request to the cheapest capable model across 41 models from OpenAI, Anthropic, Google, DeepSeek,...

开发与 DevOps

许可证：MIT-0

MIT-0 ·免费使用、修改和重新分发。无需归因。

版本：v0.10.5

统计：⭐ 11 · 1.9k · 13 current installs · 15 all-time installs

⭐ 11

安装量（当前） 15

🛡 VirusTotal ：良性 · OpenClaw ：可疑

Package：1bcmax/clawrouter

安全扫描（ClawHub）

VirusTotal ：良性
OpenClaw ：可疑

OpenClaw 评估

The skill's instructions are mostly coherent with a model-routing utility, but it omits key details about required credentials/config and relies on an external plugin install (not included), which raises transparency and privilege concerns.

目的

Name/description match the instructions: it routes requests to many models and tells the agent to set models to blockrun/auto. However the description mentions routing 'all... through one wallet' while the skill declares no required env vars and only a single config path (models.providers.blockrun) — this is plausible if BlockRun is an aggregator, but the skill does not document what credentials or wallet config are required.

说明范围

SKILL.md only instructs installing the external OpenClaw plugin and switching the agent's model to blockrun/auto or a pinned model. It does not ask the agent to read unrelated files, secrets, or system paths beyond the declared models.providers.blockrun config path.

安装机制

This packaged skill is instruction-only and contains no code, but the provided workflow requires running 'openclaw plugins install @blockrun/clawrouter' which will download and install external code not present in this skill. The skill gives no install spec here, so installing will fetch code from outside the package (the homepage repo is given). That external install step could place arbitrary code on disk and should be audited before running.

证书

The skill declares no required environment variables but does require the config path models.providers.blockrun. The description's 'one wallet' claim implies sensitive credentials/payment details will be used. The skill does not enumerate what secrets (wallet keys, provider API keys) are needed or how they are stored, which is a transparency gap and a proportionality concern.

持久

always is false and there are no indications the skill requests persistent system-wide privileges or modifies other skills' configs. Autonomous invocation is allowed (default) but not combined here with other high-risk flags.

安装（复制给龙虾 AI）

将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「ClawRouter」。简介：Smart LLM router — save 67% on inference costs. Routes every request to the che…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/1bcmax/clawrouter/SKILL.md
（来源：yingzhi8.cn 技能库）

SKILL.md

打开原始 SKILL.md（GitHub raw）

---
name: clawrouter
description: Smart LLM router — save 67% on inference costs. Routes every request to the cheapest capable model across 41 models from OpenAI, Anthropic, Google, DeepSeek, and xAI.
homepage: https://github.com/BlockRunAI/ClawRouter
metadata: { "openclaw": { "emoji": "🦀", "requires": { "config": ["models.providers.blockrun"] } } }
---

# ClawRouter

Smart LLM router that saves 67% on inference costs by routing each request to the cheapest model that can handle it. 41 models across 5 providers, all through one wallet.

## Install

```bash
openclaw plugins install @blockrun/clawrouter
```

## Setup

```bash
# Enable smart routing (auto-picks cheapest model per request)
openclaw models set blockrun/auto

# Or pin a specific model
openclaw models set openai/gpt-4o
```

## How Routing Works

ClawRouter classifies each request into one of four tiers:

- **SIMPLE** (40% of traffic) — factual lookups, greetings, translations → Gemini Flash ($0.60/M, 99% savings)
- **MEDIUM** (30%) — summaries, explanations, data extraction → DeepSeek Chat ($0.42/M, 99% savings)
- **COMPLEX** (20%) — code generation, multi-step analysis → Claude Opus ($75/M, best quality)
- **REASONING** (10%) — proofs, formal logic, multi-step math → o3 ($8/M, 89% savings)

Rules handle ~80% of requests in <1ms. Only ambiguous queries hit the LLM classifier (~$0.00003 per classification).

## Available Models

41 models including: gpt-5.2, gpt-4o, gpt-4o-mini, o3, o1, claude-opus-4.6, claude-sonnet-4.6, claude-haiku-4.5, gemini-3.1-pro, gemini-2.5-pro, gemini-2.5-flash, gemini-2.5-flash-lite, deepseek-chat, deepseek-reasoner, grok-3, grok-3-mini.

## Example Output

```
[ClawRouter] google/gemini-2.5-flash (SIMPLE, rules, confidence=0.92)
             Cost: $0.0025 | Baseline: $0.308 | Saved: 99.2%
```