A New AI Agent Oriented Programming Language

Grenat, a new compiled programming language for building AI agent systems, treats prompts, tools, supervised actor agents, budgets and durable workflows as first-class language constructs, with an effect system that turns prompt injection into a compile-time error (E0412). The language's specification is published in SPEC.md alongside an llms.txt reference for LLMs writing Grenat and example programs including support_desk.grn (multi-agent with human approval) and triage.grn (tests with mocks, evals with an LLM judge). Grenat marks model output as untrusted (~T), requiring it to be checked, human-approved or explicitly trusted before reaching the network, a file, a command, an email or a page, and journals each workflow step so runs resume after a crash without billing a model call twice.

Ruby's syntax, Rust's speed, agents as first-class citizens. Grenat is a compiled programming language for building AI agent systems: typed prompts, tools, supervised actor agents, budgets, durable workflows, and an effect system that turns prompt injection into a compile-time error . php prompt summarize article: String - ~Summary using :fast user "Summarize: {article}" end agent Researcher model :smart tools search web, read url budget usd: 2.00, time: 10.min on Research topic: String - ~Report run "Investigate {topic}" end end - Specification: SPEC.md https://github.com/itsmedit/grenat/blob/main/SPEC.md - A compact reference for LLMs writing Grenat: llms.txt https://github.com/itsmedit/grenat/blob/main/llms.txt - Examples: basics.grn https://github.com/itsmedit/grenat/blob/main/examples/basics.grn , reviews.grn https://github.com/itsmedit/grenat/blob/main/examples/reviews.grn native statistics + validated LLM analysis , explorer.grn https://github.com/itsmedit/grenat/blob/main/examples/explorer.grn a real agent , support desk.grn https://github.com/itsmedit/grenat/blob/main/examples/support desk.grn multi-agent, human approval , triage.grn https://github.com/itsmedit/grenat/blob/main/examples/triage.grn tests with mocks, evals with an LLM judge , macros.grn https://github.com/itsmedit/grenat/blob/main/examples/macros.grn compile-time code generation , usecases/ https://github.com/itsmedit/grenat/blob/main/examples/usecases twelve agent use cases: support, code review, research, data, documents, a weekly digest, operations, a chat with memory, a team of agents, MCP tools, a knowledge base searched by meaning, meeting minutes from a recording Every snippet below passes grenat check , grenat test and grenat fmt --check . A prompt is a function a model implements. Its return type becomes a JSON schema, and the comments describe the fields to the model. A model's answer is untrusted ~T : it must be checked, approved by a human, or explicitly trusted before it reaches the network, a file, a command, an email or a page — otherwise grenat check fails E0412 . struct Summary title: String 8 words at most bullets: Array String 3 to 5 key points end Summarizes an article. prompt summarize article: String - ~Summary using :fast user "Summarize:\n {article}" end def headline article: String - String uses llm summarize article .check { |s| s.bullets.size.between? 3, 5 }?.title end A tool is a function a model may call; an agent is an actor whose run loop calls the model and its tools until it produces the handler's return type, within a budget. Effects uses … are capabilities checked by the compiler, then again at run time. php Reads a page of the handbook. tool read page name: String - String uses fs.read "./handbook" File.read "./handbook/ {name}" end Opens a ticket. A human approves it first. tool open ticket title: String - Int uses net "tracker.acme.io" , human, env approve "Open “ {title}”?" token = Credentials.fetch :tracker, :token a Secret: never printed, never sent to a model Http.post "https://tracker.acme.io/tickets", json: {title:}, headers: {"Authorization" = "Bearer {token}"}, .status end agent Support model :smart tools read page, open ticket budget usd: 0.50, time: 2.min max turns 12 instructions "Answer from the handbook only. Open a ticket for bugs." on Ask question: String - ~String run "Customer question: {question}" end end def answer question: String - ~String uses llm, fs.read "./handbook" , net "tracker.acme.io" , human, env spawn Support .ask Ask question: end Each step of a workflow is journaled: after a crash, or a human answering days later, the run resumes where it stopped and no model call is billed twice. php def recent releases repo: String - Array String uses net "api.github.com" , env, time token = Credentials.fetch :github, :token res = Http.get "https://api.github.com/repos/ {repo}/releases", headers: {"Authorization" = "Bearer {token}"}, week ago = Time.now - 7.days res.json.trust .select { |r| Time.parse r "published at" week ago }.map { |r| r "tag name" } end workflow weekly digest monday: String uses llm, net "api.github.com" , net "smtp.acme.io" , env, human, time tags = step :fetch { recent releases "rust-lang/rust" } digest = step :summarize { summarize tags.join ", " .trust } step :review { approve "Send “ {digest.title}”?" } step :email do Mail.connect Credentials.fetch :smtp, :url .send from: "bot@acme.io", to: "team@acme.io" , subject: digest.title, body: digest.bullets.join "\n" , end end every cron: "0 8 MON" do UTC, run by grenat serve weekly digest Time.today end Answers a customer, three sentences at most. prompt reply question: String - ~String using :fast user question end get "/chat" do |req| stream do |out| Server-Sent Events, as the model writes reply req.params "q" { |chunk| out << chunk } end end grenat serve reads a mailbox — Gmail, Microsoft 365, any IMAP server — and hands each new email to its handler, then marks it seen or moves it; every field of it is untrusted. on email Credentials.fetch :support, :imap url , every: 1.minute, move to: "Done" do |email| answer = reply email.text .check { |a| a.size < 2000 }? puts " {email.attachments.size} attachments, answer ready: {answer.size} characters" end struct Passage table :passages id: Int? text: String embedding: Vector 1024 end migration "001 create passages" do |db| db.migrate "CREATE TABLE passages id {db.primary key}, text TEXT NOT NULL, embedding {db.vector 1024 } NOT NULL " end def index parts: Array String uses llm, db vectors = embed :docs, parts one request for many texts parts.each with index { |text, i| Passage.create text:, embedding: vectors i } end def search question: String - Array Passage uses llm, db.read Passage.nearest :embedding, embed :docs, question , limit: 3 pgvector, or brute force on SQLite end php def restart server: SshSession - Bool uses ssh "api.acme.com" server.run "systemctl", "restart", "shop" .ok? an argument vector: no shell injection end def main uses ssh "api.acme.com" , env server = Ssh.connect "deploy@api.acme.com", key: Credentials.fetch :deploy, :ssh key puts restart server end test "only this week's releases" do freeze time "2026-10-05T08:00:00Z" do mock http "GET https://api.github.com/repos/rust-lang/rust/releases", json: {tag name: "1.95.0", published at: "2026-10-01T10:00:00Z"}, {tag name: "1.94.0", published at: "2026-08-20T10:00:00Z"}, assert equal "1.95.0" , recent releases "rust-lang/rust" assert equal "Bearer test-github-token", Http.requests.last "headers" "Authorization" end end test "the agent reads the handbook, then answers" do File.write "./handbook/refunds.md", "Refunds: within 30 days." mock :smart, replies: call :read page, name: "refunds.md" , "Refunds are possible within 30 days.", assert equal "Refunds are possible within 30 days.", answer "Can I get a refund?" .trust end test "a model answer out of bounds is refused" do mock :fast, replies: {title: "Rust 2.0", bullets: "only one" } assert raises CheckError do headline "…" end end test "the chat streams its answer" do mock :fast, replies: "Hello, Ada" assert equal "Hello, Ada", request :get, "/chat?q=hi" "events" .first "data" end test "the passage about refunds is found" do mock embed :docs vectors made from the texts' words index "A refund is asked for within 30 days.", "Invoices export to CSV." assert equal "A refund is asked for within 30 days.", search "How do I get a refund?" .first&.text end Other doubles: mock shell , mock ssh , mock mcp , mock transcribe , mock env , mock mail raise: "SMTP down" , mock credentials , cassette real calls recorded once, then replayed , with human approve all | deny all , deliver webhook , Jobs.perform , Mail.deliveries . config/models.yml — the first model is the default one fast: provider: anthropic anthropic, openai, gemini, mistral, xai, openrouter, groq, deepseek, together, ollama name: claude-haiku-4-5 smart: provider: openai name: gpt-5 docs: provider: voyage embeddings: voyage, openai, gemini, mistral, ollama name: voyage-3.5 kind: embedding dimensions: 1024 grenat credentials edit config/credentials.yml.enc, AES-256-GCM, key in config/master.key grenat credentials edit --env production one per environment, chosen by GRENAT ENV Keys are read from the credentials openai: {api key: …} , else from the provider's variable OPENAI API KEY … . Anthropic agents use prompt caching by default cache: true extends it to prompts and conversations . grenat new <name a package: grenat.toml, src/, tests/ grenat new --app <name an application: database, models, routes, src/app.grn, tests/ grenat generate agent|workflow|record|tool|eval <name field:Type… a part of the application, with its tests alias: grenat g grenat check <file.grn … names, types, effects, taint and secrets grenat run --log --unchecked --no-jit <file.grn args… check, then run main grenat test <file.grn … the test blocks, offline mocks and cassettes grenat eval <file.grn name the eval blocks, against the real models, scored grenat serve --listen host:port routes, webhooks, schedules, mailboxes, exposed tools and agents, job workers grenat console --listen host:port --token <token the operations console: approvals, jobs, journals, costs, evals grenat migrate apply the migrations the database has not seen grenat credentials edit|show --env <environment the application's encrypted secrets grenat build --native --release <file.grn -o <executable an executable --native: without the interpreter; --release: optimized by LLVM grenat fmt --check <file.grn | dir … the canonical layout grenat lsp the language server grenat update the latest commits of git dependencies grenat parse | tokens <file.grn the syntax tree, the tokens grenat --version setter init add a Facetfile to the current package setter new <name create a facet a library to share setter add <name "~ 1.2" use a facet from the indexes or --path <dir , --git <url --tag <tag setter install | update | list install and build trusted native facets , update, list setter publish tag this facet's version for the indexes | Variable | Effect | |---|---| | ANTHROPIC API KEY , OPENAI API KEY , … | a provider's key, when the credentials have none | | GRENAT LOG=1 | log every model, tool, HTTP and SSH call, and what the JIT compiled same as --log | | GRENAT RECORD=1 | record every cassette again, with real calls | | GRENAT ENV | the environment development by default : which credentials | | GRENAT MASTER KEY | the credentials' key, rather than config/master.key | | GRENAT CONSOLE TOKEN | the token of grenat console rather than --token | | GRENAT JIT=0 | interpret everything same as --no-jit | | GRENAT HOME | where grenat build finds lib/grenat/libgrenat {host,standalone}.a | | CC | the linker of grenat build default: cc | llms.txt https://github.com/itsmedit/grenat/blob/main/llms.txt is a reference of about 4,000 tokens written for models: the syntax, the effects, taint, agents, workflows, the standard library, the test doubles and the mistakes to avoid. Every code block in it passes grenat check and grenat test . It was measured: agents were given two real tasks — a support agent tools, a ticket opened after human approval, a structured answer and a weekly release digest GitHub, a validated summary, email, resumption after a crash without calling the model again — once in Python with the official Anthropic SDK, once in Grenat with llms.txt as its only documentation, twice each. Every program passes its tests. | Average of 2 runs | Python | Grenat | |---|---|---| | Tokens, support agent | 79,700 | 43,000 −46% | | Tokens, weekly digest | 38,300 | 45,000 +18% | | Tokens, both tasks | 118,000 | 88,000 −25% | | Lines of program, support / digest | 237 / 207 | 64 / 79 | The agent loop, structured answers, approvals and journaled steps are part of the language, so the code a model writes is 2.5 to 3.5 times shorter; where a task is mostly plumbing HTTP, dates, email , Python's familiarity still pays. The latest release, v0.1.2, has phases 0 to 11; phases 12 to 15 are on main . Phase 15 — email in : on email reads a mailbox Gmail, Microsoft 365, any IMAP server, over TLS; app passwords or OAuth tokens under grenat serve , each new email — its PDFs and images ready for a prompt — handled once then marked seen or moved, a failing one retried then flagged, every field untrusted, a crafted email flagged before it is parsed; deliver email hands a handler messages in tests. Phase 14 — the gaps LLMs found : a benchmark of models writing Grenat from llms.txt showed what they reach for. Time Time.parse for ISO 8601, Time.iso , Time.date , Time.weekday , Time.at , Time.now - 7.days , freeze time in tests , Ruby's everyday methods s 0, 4 , s 1.. , flatten , each slice , reduce :+ , transform values , format , then … , test doubles Http.requests to assert what was sent, mock env , mock mail raise: , and email held to the net effect by the checker. Phase 13 — what agents need in production : embeddings and search by meaning embed , Vector n fields, nearest , pgvector or brute force , prompt caching Anthropic breakpoints placed by Grenat, cached tokens in the ledger and the console , streaming blocks receiving the answer as it is written, Server-Sent Events from routes , and audio Audio.read , transcribe , audio in prompts . Phase 12 — libraries in other languages : native facets Rust code called as ordinary functions, behind a versioned ABI , bridge facets Ruby or Python functions in a sandboxed process over JSON-RPC — no interpreter embedded , and two official facets: sheets Excel, OpenDocument, CSV and html CSS selectors, links, tables . Phase 11 — reaching servers : Ssh.connect , commands as argument vectors, upload , download , SFTP list , read , write , rename … , host keys always verified; proxies for Http SOCKS5, SOCKS4, HTTP and for SSH. Phase 10 — configured, not coded : secrets encrypted per environment as with Rails grenat credentials edit , as Secret values the language keeps away from models and logs; models of ten providers in config/models.yml , each reached by the right connector with its key found in the credentials — the provider's name is enough. Phase 9 — agents operated from a browser : grenat console , open source like the rest — approvals waiting for a human, jobs and their workflow journals retry , what the models cost by agent, workflow and day, eval scores over time, failures and refusals, MCP servers. The runtime records what it shows in the application's database. Phase 8 — applications of agents , in the language and its toolchain, with no framework on top: routes, records and migrations SQLite and PostgreSQL , jobs, approvals that wait days for a human in the database, tools and agents served to other programs over MCP and HTTP expose , and generators — grenat new --app , then grenat generate agent|workflow|record|tool|eval , each part with its tests. Phase 7 — agents in production , measured by ten real use cases examples/usecases : an HTTP client, databases, email, a sandboxed Shell , MCP servers, PDFs and images, conversations with long-term memory, the Batch API, schedules and webhooks grenat serve , and facets — libraries installed by setter from a Facetfile . Phase 6 — ecosystem : programs of several files and packages grenat.toml , path and git dependencies, grenat.lock , a language server grenat lsp , compile-time macros, and release builds optimized by LLVM grenat build --release . Phase 5 — production-ready : workflows are durable — each step is journaled, and an interrupted run resumes where it stopped, without paying twice for a model call. Tests never reach a real model: mock gives the model's replies as plain values, cassette records real calls once and replays them. eval measures quality on a dataset, with judge an LLM as a judge , and fails under a threshold. Phase 4 — native code : functions over numbers, strings, arrays and structs are compiled to machine code by a Cranelift JIT when the program loads — fib 35 runs in 0.05 s, about 1.7× Rust with the same overflow semantics, 200× faster than the interpreter. Objects are reference counted, Perceus style: no garbage collector, no leak, in-place updates of uniquely owned values. grenat build compiles a program ahead of time into a standalone executable. Tasks are M:N green threads: 100,000 concurrent tasks fit in ~1 GB on a few OS threads. Agents are actors one message at a time, deadlocks detected, supervision with restarts , and parallel map and race run truly in parallel. Before running anything, grenat checks names, types, effects and taint: an unvalidated model answer that reaches the network is a compile-time error . macOS or Linux, with Homebrew: brew install itsmedit/grenat/grenat Any Linux with glibc Ubuntu 20.04+, Debian 11+, Fedora, RHEL 9, Amazon Linux 2023… or macOS, without a package manager — the install script puts grenat and setter in ~/.grenat in /usr/local as root , checks the archive's SHA-256, and adds them to your PATH : curl -sSL https://github.com/itsmedit/grenat/releases/latest/download/install.sh | sh options: sh -s -- --version v0.1.1 | --prefix DIR | --no-modify-path | --uninstall A fresh EC2 instance Amazon Linux 2023 , for instance: sudo dnf install -y gcc the C linker grenat build uses run, test and serve need none curl -sSL https://github.com/itsmedit/grenat/releases/latest/download/install.sh | sh exec $SHELL -l a new shell, with grenat on the PATH grenat new --app hello && cd hello && grenat test apt or dnf , with the packages of a release: curl -LO https://github.com/itsmedit/grenat/releases/download/v0.1.2/grenat 0.1.2 amd64.deb sudo apt install ./grenat 0.1.2 amd64.deb Ubuntu, Debian arm64: arm64.deb sudo dnf install https://github.com/itsmedit/grenat/releases/download/v0.1.2/grenat-0.1.2-1.x86 64.rpm Fedora, RHEL, Amazon Linux aarch64: .aarch64.rpm Docker — the official image, for amd64 and arm64, with a C linker for grenat build : docker run --rm -v "$PWD":/app ghcr.io/itsmedit/grenat test docker run --rm -v "$PWD":/app -p 3000:3000 ghcr.io/itsmedit/grenat serve --listen 0.0.0.0:3000 your application's image FROM ghcr.io/itsmedit/grenat:0.1.2 COPY . /app CMD "serve", "--listen", "0.0.0.0:3000" From the sources Rust, and a C linker: Xcode's command line tools on macOS : cargo install --locked --path crates/grenat cli && cargo install --locked --path crates/grenat setter cargo build --release -p grenat host -p grenat standalone the libraries grenat build links mkdir -p ~/.cargo/lib/grenat && cp target/release/libgrenat {host,standalone}.a ~/.cargo/lib/grenat/ Alpine musl is not supported by the binaries: use a glibc distribution, or the Docker image. cargo build target/debug/grenat run examples/basics.grn the core language, no LLM target/debug/grenat run --log examples/fib.grn native code: see what the JIT compiled target/debug/grenat run --log examples/objects.grn strings, arrays, structs, natively target/debug/grenat build examples/objects.grn && ./objects a standalone executable needs cc target/debug/grenat build --native examples/objects.grn without the interpreter: ~0.5 MB target/debug/grenat build --native --release examples/fib.grn optimized by LLVM needs clang export ANTHROPIC API KEY=sk-ant-… or, in an application: grenat credentials edit target/debug/grenat run --log examples/explorer.grn crates/grenat parser a real agent target/debug/grenat run examples/support desk.grn examples/tickets.jsonl multi-agent + approval target/debug/grenat new --app desk && cd desk an application: database, models, routes, tests grenat generate agent triage a part and its tests also workflow, record, tool, eval grenat generate record doc text:String "embedding:Vector 1536 " a record searched by meaning grenat migrate && grenat test && grenat serve grenat console its operations console: http://127.0.0.1:4000 target/debug/grenat new hello && cd hello a package: grenat.toml, Facetfile, src/, tests/ setter add http tools a facet library from an index, like a gem grenat run && grenat test in a package, no file to name target/debug/grenat check examples/ .grn names, types, effects, taint target/debug/grenat fmt examples canonical layout --check: only report target/debug/grenat test examples/triage.grn test blocks: mocks and cassettes, never a real model target/debug/grenat eval examples/triage.grn eval blocks: the real model, scored on a dataset cargo test ~950 tests: unit, integration, CLI, HTTP, MCP, SSH, JIT, build scripts/test-linux.sh the same suite on Linux, in Docker Two facets ship with Grenat, in facets/ https://github.com/itsmedit/grenat/blob/main/facets : native code the application trusts explicitly, built by setter install . Facetfile facet "sheets", path: "../grenat/facets/sheets", native: true facet "html", path: "../grenat/facets/html", native: true require "sheets" require "html" def main uses fs.read, fs.write, net "acme.io" orders = Sheets.records "orders.xlsx", sheet: "2026" .trust .xlsx, .xls, .ods, CSV big = orders.select { |o| o "total" .to f 1000.0 } Sheets.write csv "big orders.csv", Sheets.table big, "id", "customer", "total" page = Http.get "https://acme.io/pricing" .body prices = table records page, "table.prices" untrusted, as the page puts prices.size end See facets/sheets https://github.com/itsmedit/grenat/blob/main/facets/sheets/README.md and facets/html https://github.com/itsmedit/grenat/blob/main/facets/html/README.md . A facet can ship Rust code, as a gem ships C: a crate depending on grenat ext , whose exported functions Grenat calls as ordinary ones. The application trusts it explicitly — it runs outside Grenat's sandbox — and setter install builds it and writes its declarations: /// Reads a sheet: a line per row, cells separated by commas. grenat ext::export effects = "fs.read" pub fn read sheet path: String - Result<Vec<Vec<String , String { … } Facetfile facet "sheets", "~ 0.1", native: true generated: native def read sheet path: String - ~Array Array String uses fs.read def main uses fs.read puts read sheet "sales.csv" .trust .size end Types and effects are checked like any call's; the result is untrusted unless the function is pure , and no secret is ever handed to native code see SPEC.md , phase 12 . A facet can also ship Ruby or Python functions — no interpreter is embedded in Grenat: the facet's server is a separate process, speaking JSON-RPC 2.0 on its standard input and output, with a helper library Grenat ships standard library only : bridge/server.rb, started by bridge command = "ruby", "bridge/server.rb" in grenat.toml require "grenat/bridge" Grenat::Bridge.export :slug, params: {title: :string}, returns: :string, pure: true do |title:| title.downcase.gsub / ^a-z0-9 +/, "-" end Grenat::Bridge.run python Facetfile facet "texts", "~ 0.1", bridge: true generated: native def slug title: String - String pure def main puts slug "Hello, World" end In Python, @export on an annotated function, then run from grenat bridge import export, run . The server runs sandboxed in the facet's directory — a clean environment, no network unless a function declares net ; a relative path it is given resolves there, so pass it absolute ones — one per facet, kept alive, each call within a timeout; types, effects, taint and secrets are checked as for native code see SPEC.md , phase 12 . grenat lsp is a language server diagnostics as you type, formatting, hover, go to definition, symbols . In Neovim: vim.filetype.add { extension = { grn = "grenat" } } vim.api.nvim create autocmd "FileType", { pattern = "grenat", callback = function vim.lsp.start { name = "grenat", cmd = { "grenat", "lsp" } } end } | Crate | Role | |---|---| | grenat lexer | tokens, interpolation, heredocs, doc comments | | grenat ast | syntax tree | | grenat parser | recursive descent + Pratt, diagnostics with error recovery | | grenat llm | model providers: the catalog, Anthropic's Messages API and Chat Completions OpenAI, Gemini, Mistral, Ollama… , streaming, prompt caching, embeddings those and Voyage , transcriptions OpenAI's, uploaded as multipart/form-data and audio in prompts OpenAI, Gemini ; mocks, fake embeddings and transcripts, cassettes and a scripted provider for tests | | grenat types | checker: names, types, effects, ~T taint, secrets E0100–E0500 | | grenat codegen | Cranelift: typing, liveness Perceus , translation, boundary; JIT and object files; LLVM IR for release builds | | grenat runtime | reference-counted strings, arrays and records called by native code | | grenat driver | load, check and run a program shared by the CLI and built executables | | grenat host | static library linked into the executables of grenat build | | grenat standalone | static library linked into grenat build --native executables | | grenat report | diagnostic rendering, in the file each error points into | | grenat db | databases: SQLite embedded and PostgreSQL behind one interface; vectors pgvector, or bytes searched by brute force | | grenat mcp | the Model Context Protocol: a client stdio and HTTP , and the server side of expose | | grenat ssh | SSH and SFTP: host keys verified, commands quoted, SOCKS5 proxies, a blocking API; a real server in process for tests | | grenat imap | IMAP over TLS implicit or STARTTLS : password or OAuth XOAUTH2 logins, unseen messages by UID, flags and moves, MIME parsed into what on email gives; a server in process for tests | | grenat serve | triggers: cron schedules, calendar arithmetic, webhook signatures, the HTTP server of grenat serve , streamed responses | | grenat generate | grenat new --app and grenat generate : an application's parts, with their tests | | grenat ops | the operations store: jobs, approvals, model calls, events, eval runs, workflow journals | | grenat console | grenat console : pages and actions of the operations console, and who may use it | | grenat config | the application's configuration: encrypted credentials per environment, config/ .yml | | grenat setter | setter : creates, adds, installs and publishes facets libraries | | grenat package | grenat.toml , require , facets Facetfile , versions, indexes, trusted native code and bridges , path and git dependencies | | grenat ext | the SDK of native facets: Rust functions exported to Grenat behind a versioned JSON ABI, and their manifest | | grenat ext macros | grenat ext::export and derive GrenatType | | grenat native | native facets, Grenat's side: building a facet's library, loading it ABI checked , declaring and calling its functions | | grenat bridge | bridge facets, Grenat's side: a facet's Ruby or Python functions served by a process over JSON-RPC 2.0, described, declared and called | | grenat sandbox | sandboxed processes Shell.run , bridges : an argument vector, a clean environment, no network unless allowed | | grenat fmt | the formatter | | grenat lsp | the language server | | grenat macros | macro expansion: templates of declarations | | grenat green | M:N green threads: scheduler, green locks, channels, timers | | grenat interp | interpreter: values, evaluation, prompts, agents, budgets, taint, capabilities, workflows, test doubles, evals | | grenat cli | the grenat binary | External dependencies: ureq HTTP + rustls , serde json , toml , yaml-rust2 , rusqlite SQLite, compiled in , postgres , russh SSH , imap and mail-parser email in, over rustls with ring , lettre email out , and Cranelift for native code. Your choice of MIT https://github.com/itsmedit/grenat/blob/main/LICENSE-MIT or Apache 2.0 https://github.com/itsmedit/grenat/blob/main/LICENSE-APACHE .