ETL and data transformation for agents
Data Pipeline provides tools for extracting, transforming, and loading data. Agents can process large datasets, clean data, apply transformations, and load results into warehouses.
Low blast radius on the evidence available, but it is still third-party code — a quick look at the SKILL.md costs nothing.
Nothing in this listing indicates that it needs credentials, host access or outbound network calls. That is not a guarantee — it only means the listing does not say so.
These permissions are inferred from this listing — the credentials it declares, any maintainer warning, and the operations its own description mentions. ClawVault has not audited this skill's source code. Treat it as a starting point for your own review, not a substitute for one.
An OpenClaw skill is a directory containing a SKILL.md file: Markdown with YAML frontmatter. At startup OpenClaw scans the eligible skill directories and injects a compressed description of each skill into its system prompt, so the agent knows what it can do and invokes a skill when a request matches.
openclaw skills search data-pipelineClawHub is the public registry for OpenClaw skills. Searching first gives you the exact owner-qualified reference, which is what the install command needs. Omit the query to browse the default feed.
openclaw skills verify @<owner>/data-pipelineverify prints ClawHub's verification envelope, including its scan decision and, when available, a commit-pinned source URL. Add --card to read the generated Skill Card instead. Substitute the owner handle returned by the search above.
openclaw skills install @<owner>/data-pipelineNative ClawHub skills use an @owner/slug reference. By default this installs into the active workspace skills/ directory; add --global to install into the shared managed directory instead. You can also install from Git with git:owner/repo, or from a local folder with ./path.
openclaw skills checkcheck reports which ready skills are actually visible to the agent's prompt surface, which is the quickest way to catch a skill that installed but did not load.
Commands follow the official OpenClaw documentation. Placeholders such as <owner> are filled in by the search step, because registry references are publisher-scoped.
Added streaming support, improved performance, better error recovery
Since February 2026 ClawHub screens submitted skills with VirusTotal: each bundle is hashed and looked up, new bundles are scanned with Code Insight, and results drive an approve, warn or block decision with daily re-scanning. This materially reduces supply-chain risk but does not eliminate it, and independent research has found that different scanners frequently disagree about the same skill. Read the SKILL.md of anything you install, especially if it requests shell access or credentials.
Deploy OpenClaw, Hermes, or PicoClaw on Bluehost with the right template for the job.
The GitHub skill gives your OpenClaw agent complete access to GitHub — creating and reviewing pull requests, managing issues, listing repositories, checking build status, browsing code and triggering workflows. For developers running OpenClaw as a coding assistant this skill is essential. It closes the loop between your agent writing code and that code actually landing in a repository. Widely used in automated PR workflows, issue triage pipelines and code review automations. Works seamlessly alongside Composio for teams that need multi-service integration.
N8N Workflow connects your OpenClaw agent to your N8N automation instance, letting the agent trigger workflows, pass data between systems and monitor automation runs through plain conversation. If you already use N8N for business automation, this skill turns your agent into the intelligent orchestration layer on top — deciding which workflows to trigger based on context rather than fixed schedules. Particularly powerful for teams using N8N as their backend automation layer who want to add AI decision-making on top.
Claude Vision enables agents to understand and analyze images, screenshots, diagrams, and visual content. Perfect for agents that process visual information, extract data from images, or analyze screenshots and diagrams.