Explains what Airtable is and how data is structured — bases, tables, fields, records, views, automations, and interfaces. Use when you need context about the Airtable data model.
npx skills add https://github.com/openai/plugins --skill airtable-overview
Airtable is a no-code platform where teams build custom applications and AI-powered workflows from structured data. Users organize their data into bases, define tables with typed fields, set up automations to act on changes, and create interfaces that give different audiences tailored views of the same data.
A base is an Airtable database. It is the top-level container for all related data. A base contains one or more tables.
A table is a collection of structured data within a base, similar to a sheet in a spreadsheet or a table in a relational database. Each table has a defined set of fields and contains records.
A field defines a named, typed property on every record in a table.
A record is a single entry in a table. Each record has a unique ID and stores a cell value for each field defined on that table.
A view is a saved configuration for how to display records in a table. Views can filter, sort, group, and hide fields without changing the underlying data. Multiple views can exist on the same table, each showing the data differently.
An automation is a workflow that runs in response to a defined trigger (e.g. a record entering a view) and executes one or more actions (e.g. sending an email or updating a record).
Interfaces are custom app-like pages built on top of base data. They provide tailored, user-friendly ways to view and interact with records without exposing the full base structure or all of its data. A base can have multiple interfaces, each designed for a specific workflow or audience.
Some users can only access a base through its interfaces and cannot read or modify the underlying tables directly.
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Query the CELLxGENE Census (61M+ cells) programmatically. Use when you need expression data across tissues, diseases, or cell types from the largest curated single-cell atlas. Best for population-scale queries, reference atlas comparisons. For analyzing your own data use scanpy or scvi-tools.
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