Agent Skills: hbase
Apache HBase wide-column store on Hadoop. Use for big data.
dataID: kilo-org/kilo-marketplace/hbase
199384
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The files that make up hbase.
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- create-hookCreate and configure git hooks with intelligent project analysis, suggestions, and automated testing
- write-testsWrite and run ryOS tests with Bun's native test runner (bun:test). Covers unit/wiring tests (no server) vs API integration tests (require the standalone API server), shared HTTP helpers, and the package.json suite commands. Use when adding tests, writing test coverage for a change, or running/triaging the test suite.
- review-prReview an existing GitHub pull request and post inline review comments on its diff. Use when the changes are on an opened PR rather than your local working tree.
- plan-treeMaintain a structured planning document tree made of roadmap/status files, implementation status or handoff TODO files, topic notes, decision records, open questions, ideas/inspiration pools, and repository/file-structure hygiene plans. Use when Codex needs to create, reorganize, audit, or update a multi-file plan, design-doc folder, roadmap tree, active implementation-status file, repo cleanup/filesystem plan, ADR/decision log, ideas inbox, or linked planning knowledge base; reconcile Done/In Progress/Next state; resume work from TODO/handoff state; move resolved questions into decisions; promote ideas into formal plan artifacts; or keep plan documents and file-structure planning internally consistent without making this project-specific.
- sanity-checkRun an E2E smoke test that installs rivetkit packages from npm in an isolated temp project, starts the hello-world counter actor, then verifies both HTTP actions and WebSocket actions + events work end-to-end. Use when the user asks to sanity check, smoke test, or verify a rivetkit release/preview-publish works.
- hf-cloud-python-env-setupSet up an isolated Python environment for SageMaker / AWS work, with the right Python version and current boto3. Use this skill whenever Python code will be executed for a SageMaker deployment, training job, or any AWS automation — including when about to run `pip install`, when about to invoke `boto3`, when creating or activating a virtualenv, or when the user asks to "set up the environment". Never use system Python and never `pip install` into it. Always isolate. This skill prevents the most common failure modes: wrong Python version, dependency conflicts, and stale SDKs.