Use Go struct tags to render styled terminal output in gh-aw.
npx skills add https://github.com/github/gh-aw --skill console-rendering
Use this guide for the struct tag-based console rendering system.
Use the console struct tag to control rendering behavior:
header:"Name" - Sets the display name for fields (used in both structs and tables)title:"Section Title" - Sets the title for nested structs, slices, or mapsformat:"type" - Sets the formatting type for the field valueformat:number - Formats integers as human-readable numbers (e.g., "1k", "1.2M")format:cost - Formats floats as currency with $ prefix (e.g., "$1.234")omitempty - Skips the field if it has a zero value"-" - Always skips the fieldtype Overview struct {
RunID int64 `console:"header:Run ID"`
Workflow string `console:"header:Workflow"`
Status string `console:"header:Status"`
Duration string `console:"header:Duration,omitempty"`
}
data := Overview{
RunID: 12345,
Workflow: "test-workflow",
Status: "completed",
Duration: "5m30s",
}
// Simple rendering
fmt.Print(console.RenderStruct(data))
// Output:
// Run ID : 12345
// Workflow: test-workflow
// Status : completed
// Duration: 5m30s
type Metrics struct {
TokenUsage int `console:"header:Token Usage,format:number"`
Errors int `console:"header:Errors"`
}
data := Metrics{
TokenUsage: 250000,
Errors: 5,
}
// Renders as:
// Token Usage: 250k
// Errors : 5
type Billing struct {
Cost float64 `console:"header:Estimated Cost,format:cost"`
}
data := Billing{
Cost: 1.234,
}
// Renders as:
// Estimated Cost: $1.234
Structs are rendered as key-value pairs with proper alignment.
Slices of structs are automatically rendered as tables:
type Job struct {
Name string `console:"header:Name"`
Status string `console:"header:Status"`
Conclusion string `console:"header:Conclusion,omitempty"`
}
jobs := []Job{
{Name: "build", Status: "completed", Conclusion: "success"},
{Name: "test", Status: "in_progress", Conclusion: ""},
}
fmt.Print(console.RenderStruct(jobs))
Renders as:
Name | Status | Conclusion
----- | ----------- | ----------
build | completed | success
test | in_progress | -
Maps are rendered as markdown-style headers with key-value pairs.
time.Time fields are automatically formatted as "2006-01-02 15:04:05". Zero time values are considered empty when used with omitempty.
The rendering system safely handles unexported struct fields by checking CanInterface() before attempting to access field values.
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
Build and distribute Expo development clients locally or via TestFlight
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.
Take github/console-rendering from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.