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gooseR brings goose AI into R. Itβs a comprehensive, intelligent R development assistant powered by the goose CLI.
goose_honk() - Actually reads your
code and provides specific feedback
gentle, moderate,
harsh, brutalgoose_rename_columns() - Transform
long survey questions into meaningful variable names
sat_cust_servnpsgoose_give_sample() - Share data
samples with AI for contextgoose_make_a_plan() - Get AI-powered
analysis plans (exploratory/predictive/diagnostic)goose_continuation_prompt() - Save
your work context for tomorrowgoose_handoff() - Create comprehensive
project handoffsgoose_summarize_session() - Summarize
your work sessiongoose_backup(),
goose_restore(), goose_clear_tags()with_goose_session() with auto-cleanupgoose_view_column_map() for renamed survey datagoose_format_response() - Beautiful
markdown formattinggoose_format_table() - Clean table
outputgoose_format_code() -
Syntax-highlighted code blocksgoose_format_list() - Formatted lists
with emojisgoose is your friendly AI partner who can understand what you want to do and help you do it! The best part is that goose can learn from your preferences and remember them for next time!
# Install from GitHub (soon on CRAN!)
# install.packages("remotes")
remotes::install_github("blockbtheriault/gooseR")If Goose CLI is already working on your machine, youβre ready to go! No extra R-side setup needed.
library(gooseR)
# Test your setup
if (goose_test_cli()) message("Goose CLI is ready! π¦")If you donβt have Goose CLI configured yet:
# Configure credentials (example for OpenAI)
goose_configure(provider = "openai", model = "gpt-4o", api_key = "your-key")library(gooseR)
# Ask Goose a question
goose_ask("Summarize mtcars and suggest 2 visualizations")
# Get intelligent code review
goose_honk(severity = "moderate") # Reviews your current script
# Clean survey data
survey_data <- read.csv("qualtrics_export.csv")
clean_data <- goose_rename_columns(survey_data)
goose_view_column_map(clean_data) # See the mapping
# Save and load R objects with memory
model <- lm(mpg ~ wt + cyl, data = mtcars)
goose_save(model, category = "models", tags = c("mtcars", "regression"))
my_model <- goose_load("model")
# Create a branded visualization
library(ggplot2)
ggplot(mtcars, aes(wt, mpg)) +
geom_point() +
theme_brand("block") +
labs(title = "Fuel Efficiency")# Load messy Qualtrics data
survey <- read.csv("survey_export.csv")
# Clean column names intelligently
clean <- goose_rename_columns(survey)
# "How satisfied are you with..." β sat_overall
# "On a scale of 1-10..." β nps
# Get analysis plan
goose_make_a_plan("exploratory")
# Save for tomorrow
goose_continuation_prompt()# Share data context
goose_give_sample(my_data)
# Get analysis plan
plan <- goose_make_a_plan("predictive")
# Write your model...
model <- glm(outcome ~ ., data = my_data, family = binomial)
# Get tough feedback
goose_honk(severity = "harsh")
# Create handoff document
goose_handoff()# Backup team's work
goose_backup()
# Clean up test objects
goose_clear_tags(c("test", "temp", "draft"))
# Summarize sprint work
goose_summarize_session()
# Create continuation for next sprint
goose_continuation_prompt()goose_ask() - General AI queriesgoose_review_code() - AI code reviewgoose_document() - Generate roxygen2 docsgoose_generate_tests() - Create test suitesgoose_explain_error() - Debug errorsgoose_honk() - Context-aware code reviewgoose_make_a_plan() - Analysis planninggoose_give_sample() - Share data contextgoose_handoff() - Project documentationgoose_continuation_prompt() - Save work contextgoose_rename_columns() - Smart column renaminggoose_view_column_map() - View rename mappingsgoose_save(), goose_load() - Save/load any
R objectgoose_list(), goose_delete() - Manage
saved objectsgoose_backup(), goose_restore() - Bulk
operationsgoose_clear_tags() - Clean by tagswith_goose_session() - Temporary work sessionstheme_brand() - Apply brand themesbrand_palette() - Access color palettesbrand_css() - Export CSS stylesbrand_rmd_template() - RMarkdown templatesgoose_format_response() - Beautiful markdowngoose_format_table() - Clean tablesgoose_format_code() - Syntax highlightinggoose_format_list() - Formatted listsgoose_stream() - Streaming responsesgoose_cache_*() - Caching systemgoose_batch() - Parallel processinggoose_template_*() - Template system
More examples in docs/assets/ and
inst/examples/.
browseVignettes("gooseR") for tutorialsexamples/ directory for
use cases?function_name for
detailed helpgoose_honk()We welcome contributions! Please see the CONTRIBUTING.md and CODE_OF_CONDUCT.md files in the source repository at https://github.com/blockbtheriault/gooseR.
MIT License. See LICENSE for details.
Built with β€οΈ by the Block People Analytics & Research team. Special thanks to the goose team for creating such an amazing AI platform!
gooseR: Making R development more intelligent, one honk at a time! π¦
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.