Cline is an open-source AI coding agent focused on real software work. Most developers first encounter Cline as an assistant in the editor or terminal, but Cline is broader than a single interface.
It has both a CLI and an SDK:
The CLI is for running agent workflows directly from the terminal
The SDK is for embedding the same agent runtime inside your own scripts, products, CI jobs, and internal tools
That distinction matters. In the Cline SDK launch post, the team explains that the original product started inside the VS Code extension, and over time the runtime became harder to separate from the IDE around it. The SDK is the answer to that problem: the agent runtime is treated as a shared service rather than an implementation detail hidden inside one app.
That is also why the SDK is more interesting than a thin API wrapper, the same runtime now powers Cline across the CLI and IDE surfaces, while staying open for other teams to embed in their own products. The low-level agent loop stays reusable, and the stateful runtime around it becomes more durable, portable, and product-agnostic.
The SDK documentation describes Cline SDK as an open-source TypeScript framework for building agentic applications. The launch post adds a few more important ideas:
Cline 2.0 is built as a layered TypeScript stack
teams can start with a small surface area and add more runtime pieces later
the runtime is extensible through tools, plugins, MCP servers, skills, and hooks
provider choice is not locked to one model vendor
That makes TypeScript the natural choice for a first project.
In this article, we will build a small release notes generator that uses the Cline SDK to inspect recent git history and turn it into readable markdown.
This release-notes project is small, but it matches the SDK well because it uses the part of Cline that matters most: the runtime for tool-using agents.
We are not trying to rebuild the whole Cline product. We are only borrowing the runtime shape:
define a focused tool
give that tool to an agent
let the agent inspect real project state
turn the result into a useful artifact
That pattern lines up closely with how the Cline team positions the SDK in the launch post: something you can embed in scripts, internal tools, CI workflows, and other product surfaces, not just in an IDE.
The project exposes one command:
It does one job well:
start a Cline agent
give the agent one custom tool,
get_recent_commitslet the tool read recent git history from the current repository
have the agent turn that data into release notes
print the result to stdout
The interesting part is not the CLI itself. The interesting part is the architecture: our application provides a narrow, useful capability, and the Cline runtime decides how to use it.
That is exactly the kind of problem the SDK is meant for. As the launch post puts it, the runtime is no longer supposed to live only inside one UI surface. It is something you can pull into your own stack.
cline-demo/
├── .env.example
├── package.json
├── tsconfig.json
└── src/
├── git.ts
├── index.ts
└── prompt.ts
The Cline SDK requires Node.js 22+.
Install dependencies:
Create your environment file:
Then fill in your OpenAI key:
This project uses Cline’s openai-native provider.
Run it from inside any git repository:
This is the entry point. It does three things:
parses the
--sinceargumentcreates the custom
get_recent_commitstoolruns a Cline
Agentand prints the final result
The core shape is intentionally small:
This is the mental model to remember: your app defines tools, and Cline supplies the agent runtime.
In other words, we are not reimplementing agent orchestration ourselves. We are reusing the same idea Cline uses internally: a runtime that can reason, call tools, and produce a final artifact.
This file keeps the repository access logic out of the main program.
It uses:
git logto collect recent commitsgit show --name-onlyto collect changed file paths per commit
Each commit is returned as structured data:
sha
shortSha
author
date
subject
body
files
That structure matters. It gives the model enough context to infer whether a change is a feature, a fix, a maintenance task, or something that may require an upgrade note.
This file contains the prompt contract.
The system prompt tells the agent to:
call
get_recent_commitsbefore answeringuse only tool evidence
return markdown only
organize the answer into:
Overview
Features
Fixes
Docs / Chore
Upgrade Notes
Keeping the prompt separate makes the project easier to explain and modify. The runtime code stays small, while the output rules live in one place.
The single most important part of the project is the tool definition:
Without this tool, the agent would only be rephrasing whatever text we pasted into the prompt. With the tool, it can actively inspect the repository through a controlled interface.
That is where the SDK becomes interesting: it is not just a text wrapper around a model. It is a runtime for tool-using agents.
And if this project needed to grow later, the SDK already has room for that. The Cline team highlights plugins, custom tools, MCP integration, skills, and multi-agent capabilities as extension points. We are deliberately not using all of that here, but it is useful to know that the simple version and the more advanced version can live on the same foundation.
Release notes sit in a sweet spot for agent automation:
the input is messy but structured enough to inspect
the output has a clear shape
the task is useful in real projects
the problem is narrow enough to understand quickly
In other words, this is not a toy chatbot, but it is also not an overbuilt autonomous system. It is a believable piece of SDLC automation.
Here is the kind of markdown the tool produces:
The CLI version of Cline is about using an agent from the terminal. The SDK version is about embedding that agent into your own software.
That is the main idea behind the Cline SDK launch as well: pull the runtime out of a single product surface, make it reusable, and let other developers build on top of it.
This project shows that idea in a compact form:
define one useful tool
hand it to a Cline agent
let the agent inspect real project data
turn the result into a polished artifact
Once this pattern clicks, the same structure can be reused for PR summaries, changelog drafting, test-plan generation, issue triage, and other software delivery workflows.

