Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Open Router
Configure OpenRouter model routing with provider auth, model selection, fallback chains, and cost-aware defaults for stable multi-model workflows.
skill openclawclawhub Free
Configure OpenRouter model routing with provider auth, model selection, fallback chains, and cost-aware defaults for stable multi-model workflows.
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, auth-and-provider.md, cost-guardrails.md, fallback-reliability.md, memory-template.md, routing-playbooks.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- ivangdavila
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Setup
On first use, read setup.md to align activation boundaries, reliability goals, and routing preferences before making configuration changes.
When to Use
Use this skill when the user wants to connect an OpenAI-compatible workflow to OpenRouter, choose models by task type, set safe fallbacks, and control cost drift over time.
Architecture
Memory lives in ~/open-router/. See memory-template.md for structure. ~/open-router/ βββ memory.md # Active routing profile and constraints βββ providers.md # Confirmed provider and auth choices βββ routing-rules.md # Task -> model and fallback policy βββ incidents.md # Outages, rate limits, and recovery notes βββ budgets.md # Spend guardrails and optimization actions
Quick Reference
Use the smallest relevant file for the current task. TopicFileSetup and activation preferencessetup.mdMemory templatememory-template.mdAuthentication and provider wiringauth-and-provider.mdRouting patterns by workloadrouting-playbooks.mdReliability and fallback handlingfallback-reliability.mdCost controls and spend reviewscost-guardrails.md
1. Start from Workload Classes, Not Model Hype
Classify requests first: coding, analysis, extraction, summarization, or long-context synthesis. Map each class to a primary model and a fallback before changing any defaults.
2. Keep Authentication Explicit and Verifiable
Use OPENROUTER_API_KEY from the local environment, never pasted into logs or chat memory. Validate auth with a minimal request before applying routing changes.
3. Design Fallbacks for Failure Modes, Not Convenience
Separate fallback reasons: rate limit, provider outage, latency spike, or output quality failure. Keep at least one fallback from a different provider family for resilience.
4. Enforce Cost Boundaries Before Throughput Tuning
Set cost ceilings by task class and check expected token burn before broad rollout. Route low-stakes tasks to cheaper models and reserve premium models for high-impact tasks.
5. Change One Layer at a Time
Modify either model selection, fallback policy, or budget limits in a single iteration. After each change, run a quick verification prompt set and record outcome.
6. Record Decisions for Repeatability
Save the final routing policy, rationale, and known tradeoffs in memory. Reuse proven policies instead of repeatedly rebuilding from scratch.
Common Traps
Choosing one model for every task -> higher cost and unstable quality under varied workloads. Using same-family fallback chain only -> cascading failures during provider-specific incidents. Ignoring token limits for long inputs -> truncated responses and hidden quality loss. Changing routing and budgets simultaneously -> unclear root cause when quality drops. Running without verification prompts -> broken routing detected only after user-facing failures.
External Endpoints
These endpoints are used only to discover model metadata and execute routed inference requests under explicit user task intent. EndpointData SentPurposehttps://openrouter.ai/api/v1/modelsnone or auth header onlyDiscover current model catalog and metadatahttps://openrouter.ai/api/v1/chat/completionsuser prompt content and selected model idExecute routed inference requests No other data is sent externally.
Security & Privacy
Data that leaves your machine: Prompt text and selected model metadata sent to OpenRouter when inference is requested. Data that stays local: Routing notes and preferences under ~/open-router/. Local environment variable references and verification logs. This skill does NOT: Request raw API keys in chat. Store plaintext secrets in skill memory files. Modify files outside ~/open-router/ for its own state.
Trust
By using this skill, prompt content is sent to OpenRouter for model execution. Only install if you trust this service with your data.
Related Skills
Install with clawhub install <slug> if user confirms: api β API request design, payload shaping, and response validation patterns auth β credential handling and auth troubleshooting workflows models β model comparison and selection guidance monitoring β runtime health checks and incident tracking practices
Feedback
If useful: clawhub star open-router Stay updated: clawhub sync
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
6 Docs
- SKILL.md
- auth-and-provider.md
- cost-guardrails.md
- fallback-reliability.md
- memory-template.md
- routing-playbooks.md