Ml Ops
v1.0.0Deep MLOps workflow—reproducible training, experiment tracking, packaging, deployment, monitoring (drift, performance), governance, and rollback for ML. Use...
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by@clawkk
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name, description, and content consistently describe an MLOps workflow; no unexpected binaries, env vars, or config paths are requested.
Instruction Scope
SKILL.md contains advisory steps and checklists for MLOps stages only — it does not instruct the agent to read files, access environment variables, call external endpoints, or run commands.
Install Mechanism
No install spec or code files are present; this is instruction-only so nothing will be written to disk or downloaded during install.
Credentials
The skill declares no required environment variables, credentials, or config paths; requested access is proportional (none) to its advisory purpose.
Persistence & Privilege
always is false and model invocation is allowed (default); the skill is user-invocable and does not request persistent installation or elevated privileges.
Assessment
This skill is a pure guidance document about MLOps and appears internally coherent. It does not request secrets or install code, so installing it has low technical risk. However, if you or an agent later use this guidance to wire up real systems (artifact registries, monitoring, feature stores, cloud deploys), those integrations will require credentials and privileged access — evaluate each connector (CI/CD, cloud accounts, feature stores, monitoring hooks) for least privilege, audit logging, and secret handling before granting them. If a future version adds tooling or install steps, re-evaluate for downloads, unexpected URLs, or broad env var requirements.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.