菜单
Use OpenRefine through an agent-native CLI for importing messy data, applying JSON operation histories, inspecting rows, exporting cleaned data, and managing session undo/redo.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Capability-based multi-tool matrix for 3D modeling, CAD, point clouds, rendering, GPU debugging, and fabrication. Covers mesh/parametric/photogrammetry and the path from idea to printed part or game-ready asset.
Capability-based multi-tool matrix for game development: engine, 3D/2D/audio assets, AI-generated assets, agent playtesting, packaging, store publishing, and telemetry.
Capability-based multi-tool matrix for image and graphic design: AI generation, raster/vector editing, UI mockups, diagrams, upscaling, photo library, and publishing.
Capability-based multi-tool matrix for research, note-taking, document authoring, and publishing. Agents compose providers (CLI-Anything harnesses, public CLIs, Python libs, native binaries, cloud APIs) per capability.
Capability-based multi-tool matrix for video production. Agents pick providers (CLI-Anything harnesses, public CLIs, Python libs, native binaries, cloud APIs) per capability rather than marching through fixed stages, including storyboard planning, story/audio direction, source triage, internet video/music search/download, capture/generation, analysis, sound design, high-end caption design, NLE/render doctor investigation, review, and packaging.
Discover agent-native CLIs for professional software. Access the live catalog to find tools for creative workflows, productivity, AI, and more.
| name | cli-anything-openrefine |
| description | Use OpenRefine through an agent-native CLI for importing messy data, applying JSON operation histories, inspecting rows, exporting cleaned data, and managing session undo/redo. |
| contributor | CLI-Anything-Team |
Use this skill when a task needs OpenRefine data cleaning, transformation, reusable operation histories, or CSV/TSV export from an automated agent workflow.
Install the harness:
cd openrefine/agent-harness
python -m pip install -e .
Start OpenRefine before backend commands:
openrefine -i 127.0.0.1 -p 3333
Set a custom server with OPENREFINE_URL=http://127.0.0.1:3333 or pass --base-url.
--json on every one-shot command.--session <path> for isolated task state.data apply.cli-anything-openrefine --json server ping
cli-anything-openrefine --json project list
cli-anything-openrefine --json --session run/session.json project import messy.csv --name cleanup
cli-anything-openrefine --json --session run/session.json data rows --limit 10
cli-anything-openrefine --json ops text-transform run/trim.json --column Name --expression 'value.trim()'
cli-anything-openrefine --json --session run/session.json data apply run/trim.json
cli-anything-openrefine --json --session run/session.json data export run/clean.csv --format csv
cli-anything-openrefine --json --session run/session.json session undo
cli-anything-openrefine --json --session run/session.json session redo
Run cli-anything-openrefine with no subcommand to enter the REPL.
When --json is set, command failures write a JSON object to stderr with ok: false.