Apache Airflow DAG Patterns
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
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Smart LLM router — save 78% on inference costs. Routes every request to the cheapest capable model across 30+ models from OpenAI, Anthropic, Google, DeepSeek, and xAI.
---
name: clawrouter-53c66c750378
description: Smart LLM router — save 78% on inference costs. Routes every request to the cheapest capable model across 30+ 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 78% on inference costs by routing each request to the cheapest model that can handle it. 30+ 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
30+ models including: gpt-5.2, gpt-4o, gpt-4o-mini, o3, o4-mini, claude-opus-4.5, claude-sonnet-4, claude-haiku-4.5, gemini-2.5-pro, gemini-2.5-flash, 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%
```---
name: clawrouter-53c66c750378
description: Smart LLM router — save 78% on inference costs. Routes every request to the cheapest capable model across 30+ 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 78% on inference costs by routing each request to the cheapest model that can handle it. 30+ 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
30+ models including: gpt-5.2, gpt-4o, gpt-4o-mini, o3, o4-mini, claude-opus-4.5, claude-sonnet-4, claude-haiku-4.5, gemini-2.5-pro, gemini-2.5-flash, 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%
```Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.