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-packnpx claudepluginhub nickloveinvesting/nick-love-plugins --plugin openrouter-packThis skill is limited to using the following tools:
references/cascading-router.mdreferences/context-aware-routing.mdreferences/cost-quality-optimization.mdreferences/errors.mdreferences/examples.mdreferences/implementation.mdreferences/intelligent-model-selection.mdGuides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.
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.
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.
This skill teaches you how to build intelligent routing logic that selects the best model based on task complexity, cost constraints, or latency requirements.
google/gemma-2-9b-it:free, code generation to anthropic/claude-3.5-sonnet, reasoning to openai/gpt-4-turbomax_tokens and budget caps to prevent expensive models from exceeding cost limits| 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.
See ${CLAUDE_SKILL_DIR}/references/examples.md for runnable code samples.