Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · AI
Venice.Ai Router Openclaw
Supreme model router for Venice.ai — the privacy-first, uncensored AI platform. Automatically classifies query complexity and routes to the cheapest adequate...
skill openclawclawhub Free
Supreme model router for Venice.ai — the privacy-first, uncensored AI platform. Automatically classifies query complexity and routes to the cheapest adequate...
⬇ 0 downloads ★ 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
- README.md, SKILL.md, install.sh, references/models.md, scripts/venice-router.py, scripts/venice-router.sh
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. Then review README.md for any prerequisites, environment setup, or post-install checks. 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. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.5.0
Provenance
- Publisher
- PlusOne
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Venice.ai Supreme Router
Smart, cost-optimized model routing for Venice.ai — the AI platform for people who don't want Big Tech watching over their shoulder. Unlike OpenAI, Anthropic, and Google — where every prompt is logged, analyzed, and potentially used to train future models — Venice offers true privacy with zero data retention on private models. Your conversations stay yours. Venice is also uncensored: no content filters, no refusals, no "I can't help with that."
Setup
Get a Venice.ai API key from venice.ai/settings/api Set the environment variable: export VENICE_API_KEY="your-key-here" Or configure in ~/.openclaw/openclaw.json: { "skills": { "entries": { "venice-router": { "enabled": true, "apiKey": "YOUR_VENICE_API_KEY" } } } }
Route a prompt (auto-selects model)
python3 {baseDir}/scripts/venice-router.py --prompt "What is 2+2?"
Force a specific tier
python3 {baseDir}/scripts/venice-router.py --tier cheap --prompt "Tell me a joke" python3 {baseDir}/scripts/venice-router.py --tier budget-medium --prompt "Write a Python function" python3 {baseDir}/scripts/venice-router.py --tier mid --prompt "Explain quantum computing" python3 {baseDir}/scripts/venice-router.py --tier premium --prompt "Write a distributed systems architecture"
Stream output
python3 {baseDir}/scripts/venice-router.py --stream --prompt "Write a poem about lobsters"
Web search (LLM searches the web and cites sources)
python3 {baseDir}/scripts/venice-router.py --web-search --prompt "Latest news on AI regulation"
Uncensored mode (prefer models with no content filters)
python3 {baseDir}/scripts/venice-router.py --uncensored --prompt "Write edgy creative fiction"
Private-only mode (zero data retention, no Big Tech proxying)
python3 {baseDir}/scripts/venice-router.py --private-only --prompt "Analyze this confidential contract"
Conversation-aware routing (multi-turn context)
# Save conversation history as JSON, then route follow-ups with context python3 {baseDir}/scripts/venice-router.py --conversation history.json --prompt "Can you add tests too?" The router analyzes conversation history to keep context: trivial follow-ups ("thanks") go cheap, while follow-ups in complex code discussions stay at the right tier.
Function calling (tool use)
# Define tools in a JSON file (OpenAI tools format) python3 {baseDir}/scripts/venice-router.py --tools tools.json --prompt "What's the weather in NYC?" python3 {baseDir}/scripts/venice-router.py --tools tools.json --tool-choice auto --prompt "Search for latest AI news" Tool definitions use the standard OpenAI format. The router auto-bumps to mid tier minimum for function calling since it requires capable models.
Cost budget tracking
# Show current spending python3 {baseDir}/scripts/venice-router.py --budget-status # Track per-session costs python3 {baseDir}/scripts/venice-router.py --session-id my-project --prompt "help me code" Set VENICE_DAILY_BUDGET and/or VENICE_SESSION_BUDGET to enforce spending limits. The router auto-downgrades tiers as you approach budget limits.
Classify only (no API call)
python3 {baseDir}/scripts/venice-router.py --classify "Explain the Riemann hypothesis"
List available models and tiers
python3 {baseDir}/scripts/venice-router.py --list-models
Override model directly
python3 {baseDir}/scripts/venice-router.py --model deepseek-v3.2 --prompt "Hello"
Tiers
TierModelsCost (input/output per 1M tokens)Best ForcheapVenice Small (qwen3-4b), GLM 4.7 Flash, GPT OSS 120B, Llama 3.2 3B$0.05–$0.15 / $0.15–$0.60Simple Q&A, greetings, math, lookupsbudgetQwen 3 235B, Venice Uncensored, GLM 4.7 Flash Heretic$0.14–$0.20 / $0.75–$0.90Moderate questions, summaries, translationsbudget-mediumGrok Code Fast, DeepSeek V3.2, MiniMax M2.1$0.25–$0.40 / $1.00–$1.87Moderate-to-complex tasks, code snippets, structured outputmidDeepSeek V3.2, MiniMax M2.1/M2.5, Qwen3 Thinking 235B, Venice Medium, Llama 3.3 70B$0.25–$0.70 / $1.00–$3.50Code generation, analysis, longer writing, reasoninghighGLM 5, Kimi K2 Thinking, Kimi K2.5, Grok 4.1 Fast, Hermes 3 405B, Gemini 3 Flash$0.50–$1.10 / $1.25–$3.75Complex reasoning, multi-step tasks, code reviewpremiumGPT-5.2, GPT-5.2 Codex, Gemini 3 Pro, Gemini 3.1 Pro (1M ctx), Claude Opus/Sonnet 4.5/4.6$2.19–$6.00 / $15.00–$30.00Expert-level analysis, architecture, research papers
Routing Strategy
The router classifies each prompt using keyword + heuristic analysis: Length — longer prompts suggest more complex tasks Keywords — domain-specific terms (e.g., "architecture", "optimize", "prove") signal complexity Code markers — presence of code blocks, function names, or technical syntax Instruction depth — multi-step instructions, comparisons, or "explain in detail" bump the tier Conversational simplicity — greetings, yes/no, small talk stay on the cheapest tier Conversation history — when --conversation is provided, analyzes full chat context: code in history boosts tier, trivial follow-ups ("thanks") downgrade, tool calls in history signal complexity Function calling — --tools auto-bumps to at least mid tier (capable models required) Thinking/reasoning mode — --thinking prefers chain-of-thought reasoning models (Qwen3 Thinking, Kimi K2) and bumps to at least mid tier Budget constraints — progressive tier downgrade as spending approaches daily/session limits (95% → cheap, 80% → budget, 60% → mid, 40% → high) The classifier errs on the side of cheaper models — it only escalates when there's strong signal for complexity.
Environment Variables
VariableDescriptionDefaultVENICE_API_KEYVenice.ai API key (required)—VENICE_DEFAULT_TIERMinimum floor tier — auto-classification never goes below this. Valid: cheap, budget, budget-medium, mid, high, premiumbudgetVENICE_MAX_TIERMaximum tier to ever use (cost cap)premiumVENICE_TEMPERATUREDefault temperature0.7VENICE_MAX_TOKENSDefault max tokens4096VENICE_STREAMEnable streaming by defaultfalseVENICE_UNCENSOREDAlways prefer uncensored modelsfalseVENICE_PRIVATE_ONLYOnly use private models (zero data retention)falseVENICE_WEB_SEARCHEnable web search by default ($10/1K calls)falseVENICE_THINKINGAlways prefer thinking/reasoning modelsfalseVENICE_DAILY_BUDGETMax daily spend in USD (0 = unlimited)0VENICE_SESSION_BUDGETMax per-session spend in USD (0 = unlimited)0
Why Venice.ai?
🔒 Private inference — Models marked "Private" have zero data retention. Your data never trains anyone's model. 🔓 Uncensored — No guardrails blocking legitimate use cases. No refusals, no filters. 🔌 OpenAI-compatible — Same API format, just change the base URL. Drop-in replacement. 📦 30+ models — From tiny efficient models ($0.05/M) to Claude Opus 4.6 and GPT-5.2. 🌐 Built-in web search — LLMs can search the web and cite sources in a single API call.
Tips
Use --classify to preview which tier a prompt would hit before spending tokens Set VENICE_MAX_TIER=mid to cap costs and never hit premium models Use --uncensored for creative, security research, or other content mainstream AI won't touch Use --private-only when processing sensitive/confidential data — zero retention guaranteed Use --web-search when you need up-to-date information with cited sources Use --conversation with a JSON message history for smarter multi-turn routing Use --tools to enable function calling — the router auto-bumps to capable models Set VENICE_DAILY_BUDGET=1.00 to cap daily spend at $1 — the router auto-downgrades tiers as you approach the limit Use --budget-status to see a detailed breakdown of your spending by tier Use --thinking for math proofs, logic puzzles, and multi-step reasoning — routes to Qwen3 Thinking or Kimi K2 models The router prefers private (self-hosted) Venice models over anonymized ones when available at the same tier When --uncensored is active, the router auto-bumps to the nearest tier with uncensored models Combine with OpenClaw WebChat for a seamless chat experience routed through Venice.ai
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
3 Docs3 Scripts
- SKILL.md
- README.md
- references/models.md
- install.sh
- scripts/venice-router.py
- scripts/venice-router.sh