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okaris

Llm Models

by Ömer Karışman · GitHub ↗ · v0.1.5
cross-platform ⚠ suspicious
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Install in OpenClaw
/install llm-models
Description
Access Claude, Gemini, Kimi, GLM and 100+ LLMs via inference.sh CLI using OpenRouter. Models: Claude Opus 4.5, Claude Sonnet 4.5, Claude Haiku 4.5, Gemini 3...
README (SKILL.md)

LLM Models via OpenRouter

Access 100+ language models via inference.sh CLI.

LLM Models via OpenRouter

Quick Start

curl -fsSL https://cli.inference.sh | sh && infsh login

# Call Claude Sonnet
infsh app run openrouter/claude-sonnet-45 --input '{"prompt": "Explain quantum computing"}'

Install note: The install script only detects your OS/architecture, downloads the matching binary from dist.inference.sh, and verifies its SHA-256 checksum. No elevated permissions or background processes. Manual install & verification available.

Available Models

Model App ID Best For
Claude Opus 4.5 openrouter/claude-opus-45 Complex reasoning, coding
Claude Sonnet 4.5 openrouter/claude-sonnet-45 Balanced performance
Claude Haiku 4.5 openrouter/claude-haiku-45 Fast, economical
Gemini 3 Pro openrouter/gemini-3-pro-preview Google's latest
Kimi K2 Thinking openrouter/kimi-k2-thinking Multi-step reasoning
GLM-4.6 openrouter/glm-46 Open-source, coding
Intellect 3 openrouter/intellect-3 General purpose
Any Model openrouter/any-model Auto-selects best option

Search LLM Apps

infsh app list --search "openrouter"
infsh app list --search "claude"

Examples

Claude Opus (Best Quality)

infsh app run openrouter/claude-opus-45 --input '{
  "prompt": "Write a Python function to detect palindromes with comprehensive tests"
}'

Claude Sonnet (Balanced)

infsh app run openrouter/claude-sonnet-45 --input '{
  "prompt": "Summarize the key concepts of machine learning"
}'

Claude Haiku (Fast & Cheap)

infsh app run openrouter/claude-haiku-45 --input '{
  "prompt": "Translate this to French: Hello, how are you?"
}'

Kimi K2 (Thinking Agent)

infsh app run openrouter/kimi-k2-thinking --input '{
  "prompt": "Plan a step-by-step approach to build a web scraper"
}'

Any Model (Auto-Select)

# Automatically picks the most cost-effective model
infsh app run openrouter/any-model --input '{
  "prompt": "What is the capital of France?"
}'

With System Prompt

infsh app sample openrouter/claude-sonnet-45 --save input.json

# Edit input.json:
# {
#   "system": "You are a helpful coding assistant",
#   "prompt": "How do I read a file in Python?"
# }

infsh app run openrouter/claude-sonnet-45 --input input.json

Use Cases

  • Coding: Generate, review, debug code
  • Writing: Content, summaries, translations
  • Analysis: Data interpretation, research
  • Agents: Build AI-powered workflows
  • Chat: Conversational interfaces

Related Skills

# Full platform skill (all 150+ apps)
npx skills add inference-sh/skills@inference-sh

# Web search (combine with LLMs for RAG)
npx skills add inference-sh/skills@web-search

# Image generation
npx skills add inference-sh/skills@ai-image-generation

# Video generation
npx skills add inference-sh/skills@ai-video-generation

Browse all apps: infsh app list

Documentation

Usage Guidance
This skill appears to be what it claims: a guide to using the inference.sh CLI to access many models. Before installing: 1) Inspect the installer script at https://cli.inference.sh (do not blindly run curl | sh). 2) Verify the downloaded binary's SHA-256 against the published checksums on dist.inference.sh. 3) Use API credentials only for the intended provider (inference.sh/OpenRouter) and avoid reusing high-privilege keys. 4) Consider installing in a sandbox or container if you want to limit risk. If you need the skill to run non-interactively, ask the author how credentials are expected to be provided and stored.
Capability Analysis
Type: OpenClaw Skill Name: llm-models Version: 0.1.5 The skill bundle is classified as suspicious primarily due to the `curl -fsSL https://cli.inference.sh | sh` command in `SKILL.md`. While this is presented as a legitimate installation method for the `inference.sh` CLI, executing arbitrary remote scripts via `curl | sh` is a significant supply chain vulnerability that could lead to Remote Code Execution (RCE) if the `cli.inference.sh` domain were compromised. Although the `SKILL.md` attempts to explain the script's benign function and mentions checksum verification, the method itself carries inherent risk. There is no evidence of direct malicious intent (e.g., data exfiltration, backdoors, or prompt injection against the agent for harmful objectives) within the provided files, and the `allowed-tools: Bash(infsh *)` directive limits the agent's shell access, but the installation method is a critical vulnerability.
Capability Assessment
Purpose & Capability
The name/description (access many LLMs via inference.sh/OpenRouter) matches the SKILL.md examples and commands. Required binaries/env vars are not declared because the skill is instruction-only and expects the inference.sh CLI and an account login, which is proportionate to the stated purpose.
Instruction Scope
Instructions are narrowly scoped to installing the inference.sh CLI, running login, and calling infsh app run/sample commands. They do not ask the agent to read arbitrary system files or unrelated credentials, but they do instruct running a remote installer (curl | sh) and performing an interactive login (implying you will provide credentials).
Install Mechanism
The SKILL.md tells users to run a remote installer via curl -fsSL https://cli.inference.sh | sh which downloads and installs a binary from dist.inference.sh. The doc mentions SHA-256 checksums, but running a piped install is a moderate risk — the installer writes executables to disk and you should verify checksums and the script contents before executing.
Credentials
No environment variables are declared in the registry metadata, yet the instructions require an interactive 'infsh login' (so you'll supply an API key or account credentials). This is expected for a CLI that talks to OpenRouter/inference.sh and is not disproportionate, but the skill does not declare the auth variables or storage location explicitly.
Persistence & Privilege
always is false and there are no OS restrictions. The installer will create a local CLI binary (persistent on disk), which is normal for a CLI-based integration. The skill does not request elevated platform privileges or modify other skills.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install llm-models
  3. After installation, invoke the skill by name or use /llm-models
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.5
llm-models 0.1.5 changelog: - Clarified supported models, now listing Claude Opus 4.5, Claude Sonnet 4.5, Claude Haiku 4.5, Gemini 3 Pro, Kimi K2, GLM-4.6, and Intellect 3. - Enhanced SKILL.md with detailed quick start, installation, model selection, usage examples, and use cases. - Added automatic model fallback and cost optimization explanation. - Included links to documentation for agents, agent SDK, and sample integrations. - Expanded related skills section for extending functionality.
v0.1.0
- Initial release of llm-models skill. - Access 100+ language models via inference.sh CLI using OpenRouter, including Claude, Gemini, Kimi, GLM, and more. - Supports major models: Claude Opus 4.5, Claude Sonnet 4.5, Claude Haiku 4.5, Gemini 3 Pro, Kimi K2, GLM-4.6, and Intellect 3. - Single unified API for all models, offering automatic fallback and cost optimization. - Provides quickstart instructions, model IDs, usage examples, and links to further documentation and related skills.
Metadata
Slug llm-models
Version 0.1.5
License
All-time Installs 5
Active Installs 5
Total Versions 2
Frequently Asked Questions

What is Llm Models?

Access Claude, Gemini, Kimi, GLM and 100+ LLMs via inference.sh CLI using OpenRouter. Models: Claude Opus 4.5, Claude Sonnet 4.5, Claude Haiku 4.5, Gemini 3... It is an AI Agent Skill for Claude Code / OpenClaw, with 1426 downloads so far.

How do I install Llm Models?

Run "/install llm-models" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Llm Models free?

Yes, Llm Models is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Llm Models support?

Llm Models is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Llm Models?

It is built and maintained by Ömer Karışman (@okaris); the current version is v0.1.5.

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