local-env-setup
Configure the local wisp-science runtime — uv/Python bootstrap, Node+scimaster-cli for bear-* literature skills, pixi for bioinformatics multi-env analysis. Detect mainland-China network and apply mirrors. Use when Capabilities shows missing Python/uv/Node/sci/pixi, bootstrap errors, or the user asks to 配置环境 / install Python / uv / Node / pixi / set up the local environment. Not for remote GPU/SSH compute (use compute-env-setup).
Profile →npx skills add xuzhougeng/wisp-science --skill local-env-setup --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Local runtime setup wisp-science needs three **independent** local toolchains: | Layer | Tools | Purpose | |---|---|---| | **Core** | `uv` + managed Python venv | App bootstrap, `python` tool, bundled MCP servers | | **Literature** | Node >= 20, `npm`, `sci` (scimaster-cli) | Bundled `bear-*` skills (real paper search) | | **Bioinformatics** | `pixi` | Per-project conda/pip multi-env analysis (scanpy, nextflow-adjacent stacks, etc.) | Core is **required** for the app. Literature and bioinformatics layers are optional until the user runs those skills — but Capabilities shows all of them; install what's missing for the user's goal. Restart wisp-science after changing PATH or global config so bootstrap re-runs. ## Step 0 — Detect platform, region, and current state Read the **Environment** section in the system prompt (`Operating system`, `Working directory`). ### 0a — Region / network (mirror or not) **Before any install or `pip`/`npm`/`pixi add`, decide whether the user is on mainland China and needs mirrors.** Signals (use several; do not rely on one): | Signal | Mainland likely | |---|---| | User writes in Chinese and mentions 国内 / 镜像 / 翻墙 / 清华 / 阿里 | yes | | `TZ` / system timez
- Step 0 — Detect platform, region, and current state
- 0a — Region / network (mirror or not)
- 0b — Tool presence
- Layer 1 — Core: uv + Python
- What gets created automatically
- Install uv
- Python via uv
- Manual bootstrap (auto-setup failed)
- Verify core
- Layer 2 — Literature: Node + scimaster-cli
- Install Node >= 20
- scimaster-cli
- Layer 3 — Bioinformatics: pixi
- Install pixi
PyPI / uv (core bootstrap + pixi pip deps) export UV_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple export PIP_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple npm (scimaster-cli) npm config set registry https://registry.npmmirror.com pixi config set --global pypi-config.index-url https://pypi.tuna.tsinghua.edu.cn/simple for c in uv node npm sci pixi; do command -v $c && $c --version 2>/dev/null; done macOS / Linux curl -LsSf https://astral.sh/uv/install.sh | sh brew install uv # macOS
What does the local-env-setup skill do?
Configure the local wisp-science runtime — uv/Python bootstrap, Node+scimaster-cli for bear-* literature skills, pixi for bioinformatics multi-env analysis. Detect mainland-China network and apply mirrors. Use when Capabilities shows missing Python/uv/Node/sci/pixi, bootstrap errors, or the user asks to 配置环境 / install Python / uv / Node / pixi / set up the local environment. Not for remote GPU/SSH compute (use compute-env-setup).
How do I install it?
Run `npx skills add xuzhougeng/wisp-science --skill local-env-setup --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From xuzhougeng/wisp-science, a repository with 895 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.