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tok

tok is a plain-text language for process models. One short text file describes a BPMN 2.0 process — pools, lanes, events, tasks, gateways, flows and data — together with the DMN decisions it uses, the forms people fill in and the parameters needed to simulate it. The tok tool checks the model and turns it into everything else: BPMN 2.0 XML with an automatic diagram layout (opens in Camunda Modeler and bpmn.io), SVG pictures, DMN files, Camunda forms and simulation results.

The guide · Playground · Language on one page · BPMN symbols · Report an issue

tok 1.0 "Interlibrary loan"

pool library "University library"
  lane reader "Reader"
    start need "Book needed"
    user order "Place an order"
  lane librarian "Librarian"
    user catalogues "Search the catalogues"
    xor available "Available locally?"
    user point "Point to the copy"
    send request "Order from another library" message="Order"
    end pointed "Copy pointed out"
    end ordered "Order placed"

pool other "Lending library"

flow need -> order -> catalogues -> available
flow available -> point "yes"
flow available -> request "no"
flow point -> pointed
flow request -> ordered

message request -> other "Order"

The diagram tok draws from the model above

Start here

You want to Start with
model processes pip install tok-lang, then the chapters Getting started and Process basics of the guide; the playground needs no installation
learn BPMN with tok (students) the guide from the beginning, the symbol catalogue and the cheat sheet
run models on Camunda 8 the chapter Executable models of the guide and docs/conformance-camunda.md
work with an AI agent the agent bundle tok-lang-bpm/tok-agent (skill and MCP server), docs/mcp.md
check models in continuous integration the action tok-lang-bpm/setup-tok
use tok from Python, R, Julia, JavaScript or C docs/python.md, r/tokr, docs/julia.md, docs/playground.md, docs/c-api.md
implement or extend the language docs/spec.md, the conformance corpus conformance/, CONTRIBUTING.md

The tok project

Repository What it holds
tok-lang-bpm/tok this repository: the language, the engine, every package, the editor support, the MCP server and the documentation
tok-lang-bpm/tok-agent the agent bundle: the skill tok-modelling and the MCP configuration, installable as a plugin
tok-lang-bpm/setup-tok GitHub Action: installs tok and checks the models of a repository
tok-lang-bpm/tok-lang-bpm.github.io the guide (a book) and the playground at https://tok-lang-bpm.github.io/

Packages: tok-lang (PyPI), tok-cli, tok-core, tok-bpmn, tok-sim, tok-lsp, tok-mcp (crates.io), tokr (CRAN, and R-universe), Tok (Julia General registry), tok for VS Code (Visual Studio Marketplace and Open VSX).

Why a text language

  • Readable and reviewable. Every line starts with a keyword and describes one element. Changes show up as clear diffs in version control.
  • Made for people and for AI agents. The whole language fits on one page (tok cheatsheet). An agent can write a model, run tok check --json (or call the check tool of the MCP server, tok mcp), read the line-numbered diagnostics and fix them, without ever touching XML or coordinates.
  • Standards on the outside. tok is a notation for BPMN 2.0 and DMN, not a replacement. Everything you write is exported to the OMG formats that modelling tools and process engines read; tok import converts existing BPMN and DMN files back to text.
  • Executable and measurable. The same file can carry the details Camunda 8 needs to run the process, and the times, resources and probabilities a simulation needs to estimate cycle times and workloads.
  • Simple to implement. A line-based grammar with six token types. Python, Rust and Julia implementations pass the same conformance corpus byte for byte.

Install

The tok command is the Rust engine. It comes with the Python package tok-lang (Python 3.8 or newer; wheels for Windows x64, Linux x86_64 and aarch64, macOS; on Windows use py -m pip if pip is not on the path):

pip install tok-lang
tok --version

On a platform without a wheel pip builds the engine from the source archive, which needs Rust 1.99 or newer. The command alone, from crates.io or from a checkout of the repository:

cargo install tok-cli                 # the program tok
cd rust && cargo build --release -p tok-cli      # target/release/tok

Every way reads every version of the language, 0.1 to 1.0. The package also keeps the pure-Python implementation frozen at language 0.3, the reference of the parity tests: TOK_ENGINE=python tok … runs it (docs/python.md).

The package also runs the MCP server for AI agents: tok mcp (docs/mcp.md). The R package tokr (install.packages("tokr")), the Julia package Tok.jl (below), the language server tok-lsp and the MCP server as a program of its own (cargo install tok-lsp tok-mcp) and the VS Code extension tok are described under Tools.

Julia

Tok.jl gives the whole language to Julia through the C interface of the engine, keeps an independent implementation of the core of the specification, and adds a native simulator for large experiments and the calibration of simulation parameters on event logs:

using Pkg; Pkg.add(["Tok", "tok_jll"])    # or Pkg.add(url="https://github.com/tok-lang-bpm/tok", subdir="julia/Tok.jl")
using Tok
text = read("model.tok", String)
Tok.Engine.check(text)                                  # the engine: every layer of the language
m = Tok.Sim.model(text)                                 # native simulation (julia -t auto)
e = Tok.Sim.experiment([m, Tok.Sim.scenario(m; name="+1", resources=Dict("staff" => 3))]; replications=200)
Tok.Sim.summarize(e)
f = Tok.Fit.fit(text, Tok.Fit.read_xes("log.xes"))      # calibration on an event log
Tok.Fit.apply(text, f)                                  # the document with the fitted parameters

The engine library is found through TOK_LIBTOK, the package tok_jll, or the repository build (cargo build --release -p tok-capi); see docs/julia.md.

Use

tok check model.tok              # diagnostics; --lang pl for Polish, --json for programs
tok fmt model.tok -w             # canonical form
tok bpmn model.tok               # model.bpmn with diagram layout
tok svg model.tok                # model.svg
tok export model.tok -o out/     # BPMN, SVG, DMN and forms (executable models for Camunda 8)
tok import diagram.bpmn          # BPMN 2.0 XML to tok
tok sim model.tok --seed 1       # simulation indicators; --log log.csv for the event log
tok eval model.tok DECISION a=1  # evaluate a decision

Tools

Tool What it gives Documentation
tok the command line: check, format, export, import, simulate, evaluate docs/cli.md
tok-lsp language server (LSP 3.17) for any editor: diagnostics, formatting, go to definition, references, rename, outline, hover, completion, the diagram docs/lsp.md
VS Code extension syntax highlighting, the language server, a live diagram preview, export of BPMN and every file editors/vscode
tok mcp, tok-mcp MCP server for AI agents: the tools check, fmt, export, import, sim, eval and the language reference (tok mcp from the Python package, or the program tok-mcp) docs/mcp.md
playground the engine in the browser (WebAssembly): editor, diagnostics, diagram, bpmn-js viewer, simulation, decisions, downloads docs/playground.md
Python, R, Julia tok-lang (Python), tokr (R), Tok.jl (Julia) on the same engine docs/julia.md, r/tokr
C library tokengine with tok.h, for any language that calls C docs/c-api.md
cd rust
cargo build --release -p tok-lsp -p tok-mcp      # target/release/tok-lsp, target/release/tok-mcp
bash tools/playground.sh                          # the playground in rust/target/playground

Documentation

Document Contents
docs/spec.md the language specification (normative)
docs/cheatsheet.md the language on one page
docs/symbols.md every BPMN symbol tok draws, with its tok statement and its support in Camunda 8 (tools/symbols.py)
docs/cli.md command line reference
docs/diagnostics.md diagnostic codes in English and Polish
docs/feel.md FEEL: the subset of languages 0.1–0.6 and the full FEEL of language 0.7
docs/dmn-tck.md DMN TCK conformance results
docs/conformance-camunda.md every BPMN, DMN and FEEL feature of Camunda 8.10, how tok expresses it, the case and the Camunda run that verify it
docs/conformance-bpmn.md every element of the BPMN 2.0.2 and DMN 1.5 metamodels: tok construct, export, import, MIWG and DMN TCK coverage
docs/simulation.md simulation semantics, distributions and outputs
docs/import.md converting BPMN and DMN XML to tok
docs/python.md the Python module tok.api
docs/julia.md Tok.jl: the engine in Julia, the independent core, native simulation, calibration
docs/calibration.md the fit layer: estimating simulation parameters from event logs
docs/c-api.md the C interface of the engine (library tokengine, header tok.h)
docs/lsp.md the language server tok-lsp and its use in VS Code, Neovim, Helix and Emacs
docs/mcp.md the MCP server tok-mcp: tools, resources, configuration of MCP clients
docs/playground.md the browser playground on the WebAssembly build of the engine
docs/fuzzing.md the fuzz targets of the engine, how to run them, what they found
docs/performance.md benchmarks on large generated models and their results
docs/design-1.0.md language 1.0: decisions, deprecations, the compatibility of 1.x (earlier versions: design-0.3.md to design-0.7.md)
docs/roadmap.md the releases from 0.1 to 1.0: full Camunda 8 and BPMN 2.0.2 coverage, Rust engine for Python and R, Julia standalone
docs/changelog.md the changes of every release
skills/tok-modelling a skill that teaches an AI agent to model in tok
examples/ example models

Repository

Folder Contents
python/ reference implementation (package tok-lang, command tok) and its tests
rust/ Rust engine: tok-core, tok-bpmn (BPMN rules, layout, SVG), tok-sim (simulator), tok-cli (native tok), tok-py (Python bindings), tok-capi (C interface), tok-lsp (language server), tok-mcp (MCP server), tok-wasm (WebAssembly build), tok-bench (generated large models and benchmarks); rust/fuzz holds the fuzz targets (a cargo workspace of its own)
editors/vscode VS Code extension: grammar, language client, diagram preview
playground/ the page of the browser playground
r/tokr R package tokr on the Rust engine: diagnostics as data frames, diagrams in the viewer, knitr engine {tok}
julia/Tok.jl Julia package: the engine through the C interface, the independent core, native simulation and calibration; julia/app (the tok application), julia/binarybuilder (the recipe of tok_jll)
conformance/ shared test corpus: input documents and expected outputs for every implementation
docs/, examples/, skills/ documentation, examples, agent skill

tools/check.sh runs every check of a release (Rust, Python, R and Julia tests, engine wheel and its parity with the Python implementation, the native tok program, the C library of the engine, the language and MCP servers, the VS Code extension and the playground) on Linux, macOS or Windows with Git Bash.

The BPMN validation comes from the bpmn.py validator used in the course Modelowanie procesów informacyjnych (Jagiellonian University), shipped here as tok.bpmnlib; its rule messages are in Polish and tok adds English equivalents. The diagram layout and SVG rendering started as a port of bpmn.py and, from 0.4, are developed in the Rust engine (rust/tok-bpmn), in the same style: left to right, pools stacked, lanes as rows.

Contributing and issues

Report problems and ideas in the issues of the GitHub repository. How to build, test and propose changes: CONTRIBUTING.md. Security problems: SECURITY.md. To cite tok, use CITATION.cff; the releases are archived on Zenodo, doi:10.5281/zenodo.23769633 (all versions).

License

GNU General Public License v3.0 or later, see LICENSE.

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