图像安装
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- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: LiveView Skills Index
description: | A LiveView is an interactive component the agent opens in the Pantheon UI's right sidebar, the…
category: 通用
runtime: 无特殊运行时
---
# LiveView Skills Index 输出预览
## PART A: 任务判断
- 适用问题:通用任务拆解、检查和交付。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“Available skills / Vitessce — spatial / single-cell / imaging data / Viv — bioimage / microscopy viewer”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于通用任务拆解、检查和交付,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Available skills / Vitessce — spatial / single-cell / imaging data / Viv — bioimage / microscopy viewer”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、主要在本地完成、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件;主要在本地完成;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件。
先用一个小任务确认它会围绕“Available skills / Vitessce — spatial / single-cell / imaging data / Viv — bioimage / microscopy viewer”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: LiveView Skills Index
description: | A LiveView is an interactive component the agent opens in the Pantheon UI's right sidebar, the…
category: 通用
source: aristoteleo/PantheonOS
---
# LiveView Skills Index
## 什么时候使用
- 把通用方向的常用动作沉淀成 Agent 可调用的技能 适合处理通用任务拆解、检查、交付和复盘,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查、可继续迭代的步骤;通常不需要额外…
- 面向通用任务拆解、检查和交付,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「Available skills / Vitessce — spatial / single-cell / imaging data / Viv — bioimage / microscopy viewer」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件;主要在本地完成;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "LiveView Skills Index" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Available skills / Vitessce — spatial / single-cell / imaging data / Viv — bioimage / microscopy viewer
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> 无特殊运行时 | 读取文件、写入/修改文件 | 主要在本地完成
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} LiveView — Agent-Controllable UI Components
A LiveView is an interactive component the agent opens in the Pantheon
UI's right sidebar, then drives and observes through the live_view tools.
Unlike a static plot image, a LiveView is live: the agent changes its state
and the user sees it update; the user interacts with it and the agent reads
the result back.
Load the relevant skill file before building a visualization.
Architecture — only the LiveView SDK runtime is built in. Every viewer
is a plugin: a folder skills/live_view/<name>/ holding <name>.md
(this guide), adapter.js (a setup(lv, root) module), and an optional
demo.json. open_live_view either resolves a named viewer plugin
(view_type="vitessce") or loads an agent-generated component
(view_type="custom" + module_url). Adding a viewer = dropping a new
<name>/ folder here; no app code changes.
Available skills
Vitessce — spatial / single-cell / imaging data
Open a Vitessce browser to explore spatial transcriptomics, single-cell, and microscopy-imaging datasets: spatial scatterplots, gene-expression coloring, heatmaps, cell-set selection, image layers.
Skill file: vitessce/vitessce.md
When to use:
- Visualizing spatial transcriptomics (10x Visium, Xenium, MERFISH, …)
- Single-cell data with embeddings (UMAP/t-SNE) the user should explore
- Cell segmentations as interactive objects — click/hover a cell, colour by type or gene. (Just viewing boundaries on an image → use Viv; Vitessce does not render clean boundaries.)
- Spatial omics where cells/sets/embeddings matter, not just the image
Viv — bioimage / microscopy viewer
Open a Viv viewer for high-resolution, multiplexed bioimaging — OME-TIFF and OME-Zarr (OME-NGFF): multichannel fluorescence, microscopy, IF/IMC/ CODEX, whole-slide images. Channel colors, contrast, pan/zoom, overview.
Skill file: viv/viv.md
When to use:
- The data is an image — OME-TIFF / OME-Zarr microscopy
- Multichannel fluorescence the user wants to recolour / adjust
- Cloud-hosted or local bioimages (served via
serve_local_data) - Overlaying a cell segmentation / showing cell boundaries on an image (boundaries as an extra channel — the preferred way to view a mask)
Mol* — 3D molecular structures
Open a Mol* viewer for 3D macromolecular structures — proteins, nucleic
acids, complexes — from the RCSB PDB, the AlphaFold DB, or a local
.pdb / .cif file. Rotate, zoom, inspect; AlphaFold models colour by
pLDDT.
Skill file: molstar/molstar.md
When to use:
- Showing a protein / nucleic-acid 3D structure (experimental or predicted)
- Visualising an AlphaFold prediction
- Any
.pdb/.cifstructure file (see also thestructural_biologyskill for obtaining / predicting structures)
IGV — genome browser (tracks on a reference)
Open an IGV.js genome browser to view BAM/CRAM alignments, VCF variants, BED/GFF annotations, bigWig coverage — on a reference genome (hg38, mm10, custom FASTA, …). Pan, zoom, jump to a gene or locus.
Skill file: igv/igv.md
When to use:
- "Look at this region in a genome browser" — RNA-seq pileups, ChIP/ATAC peaks, variant calling, splice junctions, CRISPR-screen hits
- Any BAM/CRAM/VCF/BED/GFF/bigWig on a reference genome
- A gene symbol or coordinate range to display
Gosling — designed genomic figures (Vega-Lite-like grammar)
Open a Gosling.js view for designed genomic visualisations — circular ideograms, multi-track / multi-sample layouts, comparative dual-genome views, custom encodings. Driven by a declarative JSON spec.
Skill file: gosling/gosling.md
When to use:
- Circular chromosome ideograms / circos-style plots
- Designed multi-track or sample-faceted genomic figures
- Comparative dual-genome / synteny visualisations
- Anything that's hard to build with matplotlib but easy with a grammar
- Use IGV instead if the task is to look at a BAM / VCF / BED file at a locus; the two viewers do not overlap.
Cytoscape — biological networks & pathways
Open a Cytoscape.js view for interactive networks — protein-protein interactions, signalling / metabolic / regulatory pathways, ontology graphs. Nodes + edges as JSON, built-in layouts (cose, breadthfirst, circle, dagre, ...), CSS-like stylesheet by selectors.
Skill file: cytoscape/cytoscape.md
When to use:
- PPI networks (STRING, BioGRID, IntAct)
- Signalling / metabolic / regulatory pathways
- Gene-regulatory networks (TF → target)
- Any graph the user benefits from interactively (drag, hover, zoom)
MSA — multiple sequence alignment viewer
Open a multiple-sequence-alignment view (EBI Nightingale's
<nightingale-msa>) for protein or DNA alignments. Standard colour
schemes (clustal, taylor, hydro, zappo, ...), configurable tile sizes.
Skill file: msa/msa.md
When to use:
- Display a pre-computed alignment from MAFFT / MUSCLE / Clustal / MMseqs2
- Compare orthologs at a functional site / domain
- Pair with
phylotreefor tree + alignment side-by-side
RDKit — 2D small-molecule depictions
Render 2D depictions of small molecules from SMILES / MOL block using
RDKit-JS (WebAssembly build). Complements molstar (3D macromolecules)
— RDKit is the canonical 2D view for drugs, metabolites, organics.
Skill file: rdkit/rdkit.md
When to use:
- A SMILES (or list) to view as a 2D structure
- Pull drugs / metabolites from ChEMBL / PubChem / DrugBank → render
- Display the substrate / product of a reaction
- Highlight substructures or specific atoms on a molecule
Phylotree — phylogenetic trees
Open a phylotree.js view for an interactive phylogenetic tree from a Newick string. Linear or radial layout, branch-length-scaled; rerooting, ladderise, clade collapse built in.
Skill file: phylotree/phylotree.md
When to use:
- Show a phylogeny from IQ-TREE / RAxML / FastTree / MrBayes / BEAST
- Inspect / collapse / reroot a clade interactively
- Pair with
msafor tree + alignment side-by-side
Generate a custom LiveView app
Write your own interactive component with the LiveView SDK when no existing viewer fits — a bespoke dashboard, custom plot, or tailored data view that the agent can still open, drive, and observe.
Skill file: live-view-app.md
When to use:
- The data / interaction doesn't match a ready-made viewer
- You need a tailored view of analysis output
- You want a custom interactive control surface for the user
The live_view tools
| Tool | Purpose |
|---|---|
open_live_view(view_type, title, state, module_url?) |
Open a viewer plugin (e.g. view_type="vitessce") or a custom component (view_type="custom" + module_url); returns view_id |
serve_local_data(path) |
Expose a workspace file/dir over HTTP+CORS; returns a fetchable URL |
live_view_update(view_id, patch) |
Deep-merge a partial-state patch (drive it) |
live_view_set_state(view_id, state) |
Replace the whole state |
live_view_get_state(view_id) |
Read state, status, and diagnostics — incl. the user's own edits |
live_view_call(view_id, action, args) |
Invoke a component-defined action |
live_view_screenshot(view_id) |
Render the view to an image — observe_images it to see it |
list_live_views() / close_live_view(view_id) |
List / close |
Workflow: open_live_view → verify (live_view_get_state for
diagnostics, live_view_screenshot to see it — status: ready does NOT
mean it rendered correctly) → drive with live_view_update →
live_view_get_state before the next move. Never treat reading back your
own live_view_update value as verification.
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核