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Oraclaw Cmaes
by
Whatsonyourmind
· GitHub ↗
· v1.0.0
· MIT-0
129
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Install in OpenClaw
/install oraclaw-cmaes
Description
CMA-ES continuous optimization for AI agents. State-of-the-art derivative-free optimizer. 10-100x more sample-efficient than genetic algorithms on continuous...
Usage Guidance
This skill appears coherent: it describes a hosted CMA-ES optimizer and only needs ORACLAW_API_KEY. Before installing, verify the vendor (https://oraclaw.dev/cmaes), confirm billing/pricing and the exact API endpoints the agent will call, and ensure the API key you provide has the minimal required scope. Because this is an instruction-only skill, the static scanner had nothing to analyze—monitor API usage after enabling the skill and rotate the key if you see unexpected requests. If you need stronger guarantees, ask the vendor for documentation of the API and authentication flow and limit access to a test account or budget-limited key first.
Capability Analysis
Type: OpenClaw Skill
Name: oraclaw-cmaes
Version: 1.0.0
The oraclaw-cmaes skill is a legitimate tool for continuous optimization using the CMA-ES algorithm. The SKILL.md file provides clear instructions for hyperparameter tuning and parameter calibration, requiring only a standard API key (ORACLAW_API_KEY) for its external service (oraclaw.dev). No malicious code, data exfiltration, or prompt injection attempts were identified.
Capability Assessment
Purpose & Capability
Name/description (CMA-ES optimizer) match the declared requirement of a single ORACLAW_API_KEY to use a hosted optimization tool. Nothing requested (binaries, unrelated env vars, config paths) is extraneous to a remote optimization API.
Instruction Scope
SKILL.md is an instruction-only spec describing the optimizer, parameters, and expected outputs. It does not instruct the agent to read arbitrary files, access other environment variables, or exfiltrate data. The instructions are focused on optimizing continuous parameters and note that the service minimizes objectives.
Install Mechanism
No install spec and no code files — lowest-risk pattern. The skill won't write code or binaries to disk via an installer.
Credentials
Only a single primary credential (ORACLAW_API_KEY) is required, which is appropriate for a hosted optimization API. There are no other surprising secrets or credential requests.
Persistence & Privilege
always is false and the skill is user-invocable; it does not request forced permanent presence or attempt to modify other skills or system-wide settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install oraclaw-cmaes - After installation, invoke the skill by name or use
/oraclaw-cmaes - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of oraclaw-cmaes v1.0.0.
- Provides state-of-the-art CMA-ES optimizer for continuous, derivative-free optimization.
- Sample-efficient alternative to genetic algorithms for smooth continuous problems.
- Supports hyperparameter tuning, portfolio optimization, and parameter calibration.
- Requires ORACLAW_API_KEY environment variable.
- Usage pricing: $0.10 per optimization, first 1,000 calls/month free.
Metadata
Frequently Asked Questions
What is Oraclaw Cmaes?
CMA-ES continuous optimization for AI agents. State-of-the-art derivative-free optimizer. 10-100x more sample-efficient than genetic algorithms on continuous... It is an AI Agent Skill for Claude Code / OpenClaw, with 129 downloads so far.
How do I install Oraclaw Cmaes?
Run "/install oraclaw-cmaes" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Oraclaw Cmaes free?
Yes, Oraclaw Cmaes is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Oraclaw Cmaes support?
Oraclaw Cmaes is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Oraclaw Cmaes?
It is built and maintained by Whatsonyourmind (@whatsonyourmind); the current version is v1.0.0.
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