modal
Skill1 starsChanged 30 days agoNo licenceView on GitHub
Use this skill when running code on Modal (modal.com) - serverless cloud functions with on-demand GPUs, autoscaling web endpoints, parallel map, volumes, and cron schedules. Trigger for tasks involving Modal apps, serverless GPU jobs, massively parallel fan-out, hosted demos/endpoints, or when deciding between Modal and OpenWeights for a GPU workload.
- Reads credentials
- Installs packages
17 other projects use a version of this.
Adopted by
Most recently taken up by
- BrightGold70/skillstheir own version, first seen Nov 8, 2026
- lobehub/lobehubtheir own version, first seen Nov 5, 2026
- MarieLynneBlock/arcanum-artifextheir own version, first seen Nov 1, 2026
- nagisanzenin/modal-skilltheir own version, first seen Oct 25, 2026
- BlockRunAI/blockrun-mcptheir own version, first seen Oct 20, 2026
- patoangolano/bio-stacktheir own version, first seen Oct 15, 2026
Used with
Projects with it also use torch-geometric, get-available-resources and 9 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
Hongyu-yuSkilltorch-geometric
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.
Also in 3 projects that use this
SoljournerSkillget-available-resources
Enumerate installed packages, databases, and tools for engineering workflows
Also in 3 projects that use this
garri333Skillscientific-schematics
Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.
Also in 3 projects that use this
Hugging FaceSkilltransformers
Agent-invokable Transformers commands. Pass `--format json` at the top level (e.g. `transformers --format json classify ...`) to receive the structured output documented in each capability's `outputs` schema.
Also in 3 projects that use this
ZanderRussSkillseaborn
Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.
Also in 3 projects that use this
silvainfmSkillpolars
Lightning-fast DataFrame library written in Rust for high-performance data manipulation and analysis. Use when user wants blazing fast data transformations, working with large datasets, lazy evaluation pipelines, or needs better performance than pandas. Ideal for ETL, data wrangling, aggregations, joins, and reading/writing CSV, Parquet, JSON files.
Also in 3 projects that use this
Other versions17 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 17
- lobehub/lobe-chat★ 84ksame name
- lobehub/lobehub★ 84ksame name
- LeonChaoX/qinyan-academic-skills★ 910same name
- BlockRunAI/blockrun-mcp★ 389same name
- qinyan-ai/qinyan-academic-skills★ 80same name
- MarieLynneBlock/arcanum-artifex★ 4same name
- JunMA98/Computer-science-claude-skills★ 3same name
- modal-projects/skills★ 3same name
- BrightGold70/skills★ 1same name
- garri333/Skills★ 1same name
7 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository8 other files it gives its agents.
- compute-costsSkill
- litellmSkill
- mcp-builderSkill
- openweightsSkill
- skill-creatorSkill
- synthetic-dataSkill
- tinkerSkill
- vibes-evalSkill
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 0 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 16 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
“Common” is measured: kept by at least 6 in 10 of the 16 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.