open-routerConfigure OpenRouter model routing with provider auth, model selection, fallback chains, and cost-aware defaults for stable multi-model workflows.
Install via ClawdBot CLI:
clawdbot install ivangdavila/open-routerRequires:
Grade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://clawic.com/skills/open-routerAudited Apr 16, 2026 · audit v1.0
Generated Mar 20, 2026
An agency uses the skill to route different content tasks—like blog writing, social media copy, and long-form articles—to cost-effective models on OpenRouter, ensuring quality while managing budgets across multiple clients. Fallback chains prevent downtime during provider outages, maintaining delivery schedules.
Developers leverage the skill to route coding assistance and code review tasks to specialized models, optimizing for accuracy and speed. By setting cost boundaries for low-stakes debugging versus high-impact architecture reviews, they control expenses without sacrificing productivity.
Researchers use the skill to route data analysis and summarization tasks to appropriate models, handling large datasets efficiently. Fallback policies ensure reliability during peak usage times, while budget controls prevent overspending on experimental queries.
A company integrates the skill to route customer inquiries to models based on complexity—simple FAQs to cheaper models, complex issues to premium ones. This balances response quality and cost, with fallbacks ensuring service continuity during technical issues.
Offer the skill as part of a subscription service for AI workflow management, providing regular updates and support. Revenue comes from monthly or annual fees, targeting businesses needing reliable multi-model routing without in-house setup.
Provide consulting services to help clients configure and optimize the skill for their specific use cases, such as setting up routing rules and fallback chains. Revenue is generated through project-based fees or hourly rates.
Offer a basic version of the skill for free, with advanced features like detailed analytics, custom fallback policies, or priority support available in a paid tier. This attracts users and upsells to enterprises needing enhanced capabilities.
💬 Integration Tip
Start by classifying your workload types and mapping them to models before adjusting budgets, and always verify changes with test prompts to avoid disruptions.
Scored May 11, 2026
Manages free AI models from OpenRouter for OpenClaw. Automatically ranks models by quality, configures fallbacks for rate-limit handling, and updates openclaw.json. Use when the user mentions free AI, OpenRouter, model switching, rate limits, or wants to reduce AI costs.
Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.
Reduce OpenClaw AI costs by 97%. Haiku model routing, free Ollama heartbeats, prompt caching, and budget controls. Go from $1,500/month to $50/month in 5 min...
Generate and edit images with Gemini API using pure Python stdlib. Zero dependencies - works on locked-down environments where pip/uv aren't available.
Manage and use local Ollama models. Use for model management (list/pull/remove), chat/completions, embeddings, and tool-use with local LLMs. Covers OpenClaw sub-agent integration and model selection guidance.
Auto-route tasks to the cheapest Claude model that works correctly. Three-tier progression: Haiku → Sonnet → Opus. Classify before responding. HAIKU (default): factual Q&A, greetings, reminders, status checks, lookups, simple file ops, heartbeats, casual chat, 1-2 sentence tasks. ESCALATE TO SONNET: code >10 lines, analysis, comparisons, planning, reports, multi-step reasoning, tables, long writing >3 paragraphs, summarization, research synthesis, most user conversations. ESCALATE TO OPUS: architecture decisions, complex debugging, multi-file refactoring, strategic planning, nuanced judgment, deep research, critical production decisions. Rule: If a human needs >30 seconds of focused thinking, escalate. If Sonnet struggles with complexity, go to Opus. Save 50-90% on API costs by starting cheap and escalating only when needed.