← Back to Skills Marketplace
MetriLLM
by
TheBlueHouse75
· GitHub ↗
· v0.2.11
427
Downloads
0
Stars
0
Active Installs
11
Versions
Install in OpenClaw
/install metrillm
Description
Find the best local LLM for your machine. Tests speed, quality and RAM fit, then tells you if a model is worth running on your hardware.
Usage Guidance
This skill is coherent for benchmarking local LLMs, but take two precautions before installing: (1) review the npm package / GitHub repo (https://github.com/MetriLLM/metrillm) or audit the package contents before running npm install -g, since global npm installs execute third-party code on your machine; (2) only use --share if you consent to publishing model names, scores and hardware details (the README says no personal data is sent, but verify what the package actually uploads). Also ensure you have Node 20+ and run Ollama or LM Studio locally as instructed.
Capability Analysis
Type: OpenClaw Skill
Name: metrillm
Version: 0.2.11
The skill bundle contains a shell injection vulnerability in SKILL.md by instructing the agent to pass unvalidated $ARGUMENTS directly into Bash commands (e.g., `metrillm bench --model $ARGUMENTS`). It also performs high-risk operations including a global npm installation and optional data exfiltration of hardware and performance metrics to an external endpoint (metrillm.dev). While these actions are documented and align with the tool's purpose as a benchmark utility, the combination of broad Bash permissions and the injection risk poses a significant security threat.
Capability Assessment
Purpose & Capability
The name/description match the instructions: it tells you how to install the metrillm CLI, requires Node 20+ and a local LLM server (Ollama or LM Studio), and runs benchmarking commands. No unrelated credentials, binaries, or config paths are requested.
Instruction Scope
Instructions stay within the benchmarking scope (run metrillm bench, view local ~/.metrillm/results/). One caution: the optional --share command uploads results (model name, scores, hardware specs) to metrillm.dev; the SKILL.md states no personal data is sent, but that claim cannot be verified from instructions alone. The skill does not instruct access to unrelated files or env vars.
Install Mechanism
Installation is via npm (npm install -g metrillm) which is a standard delivery for a Node CLI. npm installs are moderate-risk because they execute third-party code on your system; this is proportionate to the stated purpose but you should inspect the package or source repository before global installation.
Credentials
No environment variables, credentials, or config paths are required. The only data potentially exported is from the explicit --share action (model, scores, hardware specs), which is reasonable for a community leaderboard.
Persistence & Privilege
The skill is not always-enabled and is user-invocable. It does not request persistent elevated privileges or modify other skills. Autonomous invocation is permitted by default (normal), but nothing in the skill attempts to gain extra persistence.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install metrillm - After installation, invoke the skill by name or use
/metrillm - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.2.11
Fix license: Apache-2.0, not MIT
v0.2.10
Add open source section with GitHub repo link
v0.2.9
Use global metrillm commands instead of npx, remove duration estimates
v0.2.8
Use global metrillm commands instead of npx, remove duration estimates
v0.2.7
Remove misleading benchmark duration estimates
v0.2.6
Fix install command: npm install -g instead of npx
v0.2.5
Add install instructions, LM Studio support, community leaderboard description, --share transparency for security scan compliance
v0.2.3
Rewrite description for clarity
v0.2.2
Improve listing description
v0.2.1
Security fixes, zero-config MCP, LM Studio improvements
v0.1.1
- Initial public release of metrillm.
- Benchmark local LLM models for both performance (tokens/sec, time to first token, memory) and quality (reasoning, math, coding, etc.).
- Computes clear hardware fitness verdict: EXCELLENT / GOOD / MARGINAL / NOT RECOMMENDED.
- Works with models run locally through Ollama.
- Supports quick performance-only benchmarks and sharing results to a public leaderboard.
Metadata
Frequently Asked Questions
What is MetriLLM?
Find the best local LLM for your machine. Tests speed, quality and RAM fit, then tells you if a model is worth running on your hardware. It is an AI Agent Skill for Claude Code / OpenClaw, with 427 downloads so far.
How do I install MetriLLM?
Run "/install metrillm" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is MetriLLM free?
Yes, MetriLLM is completely free (open-source). You can download, install and use it at no cost.
Which platforms does MetriLLM support?
MetriLLM is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created MetriLLM?
It is built and maintained by TheBlueHouse75 (@thebluehouse75); the current version is v0.2.11.
More Skills