LiveView Skills Index
- Repo stars 428
- Author updated Live
- Author repo PantheonOS
- Domain
- Other
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @aristoteleo · no license declared
- Token usage
- Lean
- Setup complexity
- Plug-and-play
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 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: other
runtime: no special runtime
---
# LiveView Skills Index output preview
## PART A: Task fit
- Use case: | 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. runs entirely locally. Works with Claude ….
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Available skills / Vitessce — spatial / single-cell / imaging data / Viv — bioimage / microscopy viewer” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “| 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. runs entirely locally. Works with Claude …”.
- **02** When the source has headings, the agent prioritizes “Available skills / Vitessce — spatial / single-cell / imaging data / Viv — bioimage / microscopy viewer” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Start with a small task and check whether the result follows “Available skills / Vitessce — spatial / single-cell / imaging data / Viv — bioimage / microscopy viewer”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: LiveView Skills Index
description: | A LiveView is an interactive component the agent opens in the Pantheon UI's right sidebar, the…
category: other
source: aristoteleo/PantheonOS
---
# LiveView Skills Index
## When to use
- | A LiveView is an interactive component the agent opens in the Pantheon UI's right sidebar, then drives and observes…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Available skills / Vitessce — spatial / single-cell / imaging data / Viv — bioimage / microscopy viewer” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "LiveView Skills Index" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Available skills / Vitessce — spatial / single-cell / imaging data / Viv — bioimage / microscopy viewer
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} 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.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review