Skill

openrouter-model-routing

Implement intelligent model routing strategies with OpenRouter. Use when optimizing cost/quality tradeoffs across models. Trigger with phrases like 'openrouter routing', 'model selection', 'route requests', 'model routing strategy'.

From openrouter-pack

Install

Run in your terminal

npx claudepluginhub nickloveinvesting/nick-love-plugins --plugin openrouter-pack

Tool Access

This skill is limited to using the following tools:

ReadWriteEditGrep

Supporting Assets

View in Repository

references/cascading-router.md

references/context-aware-routing.md

references/cost-quality-optimization.md

references/errors.md

references/examples.md

references/implementation.md

references/intelligent-model-selection.md

Skill Content

Similar Skills

cache-components

Guides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.

cache-components

138.6k

claude-opus-4-5-migration

2 files

Migrates code, prompts, and API calls from Claude Sonnet 4.0/4.5 or Opus 4.1 to Opus 4.5, updating model strings on Anthropic, AWS, GCP, Azure platforms.

claude-opus-4-5-migration

83.2k

evaluation-methodology

1 file

Details PluginEval's skill quality evaluation: 3 layers (static, LLM judge), 10 dimensions, rubrics, formulas, anti-patterns, badges. Use to interpret scores, improve triggering, calibrate thresholds.

plugin-eval

32.9k

Stats

Parent Repo Stars0

Parent Repo Forks0

Last CommitMar 20, 2026

Actions

View Source View Plugin View on GitHub View README

Instructions

Classify request complexity: Analyze the incoming prompt to determine if it needs a simple, mid-tier, or advanced model (e.g., by token count, keyword patterns, or task type)

Build a routing table: Map task categories to model IDs — e.g., simple Q&A to google/gemma-2-9b-it:free, code generation to anthropic/claude-3.5-sonnet, reasoning to openai/gpt-4-turbo

Implement the router function: Create a function that takes a prompt and returns the appropriate model ID based on your classification logic

Add cost guardrails: Set per-request max_tokens and budget caps to prevent expensive models from exceeding cost limits

Monitor and tune: Log which model handles each request and track quality metrics to adjust routing thresholds over time

Error Handling

Error

Cause

Fix

Wrong model selected

Classification logic too simple

Add more granular task categories; test with diverse prompts

Model unavailable

Selected model is temporarily down

Chain to fallback model (see openrouter-fallback-config)

Cost overrun

Complex tasks routed to expensive models

Set hard max_tokens limits and daily budget caps

See ${CLAUDE_SKILL_DIR}/references/errors.md for full error reference.

Openrouter Model Routing

Overview

This skill teaches you how to build intelligent routing logic that selects the best model based on task complexity, cost constraints, or latency requirements.

Prerequisites

OpenRouter integration with multiple models tested
Understanding of model capabilities and pricing differences

Instructions

Classify request complexity: Analyze the incoming prompt to determine if it needs a simple, mid-tier, or advanced model (e.g., by token count, keyword patterns, or task type)
Build a routing table: Map task categories to model IDs — e.g., simple Q&A to google/gemma-2-9b-it:free, code generation to anthropic/claude-3.5-sonnet, reasoning to openai/gpt-4-turbo
Implement the router function: Create a function that takes a prompt and returns the appropriate model ID based on your classification logic
Add cost guardrails: Set per-request max_tokens and budget caps to prevent expensive models from exceeding cost limits
Monitor and tune: Log which model handles each request and track quality metrics to adjust routing thresholds over time

Output

A routing function that selects models based on task type and constraints
Cost savings from using cheaper models for simple tasks
Quality metrics per route to validate routing decisions

Error Handling

Error	Cause	Fix
Wrong model selected	Classification logic too simple	Add more granular task categories; test with diverse prompts
Model unavailable	Selected model is temporarily down	Chain to fallback model (see openrouter-fallback-config)
Cost overrun	Complex tasks routed to expensive models	Set hard `max_tokens` limits and daily budget caps

See ${CLAUDE_SKILL_DIR}/references/errors.md for full error reference.

Examples

See ${CLAUDE_SKILL_DIR}/references/examples.md for runnable code samples.

openrouter-model-routing

openrouter-model-routing

Openrouter Model Routing

Overview

Prerequisites

Instructions

Output

Error Handling

Examples

Resources

Openrouter Model Routing

Overview

Prerequisites

Instructions

Output

Error Handling

Examples

Resources