Engineering role
AI Codebase Onboarding Engineer
An AI guide to an unfamiliar codebase that maps the repository, traces a request from entry point to database, and cites the file for every claim.
Point it at a repository you did not write — a new job, an acquired product, an open-source project you depend on — and it explains it the way a patient senior engineer would: what the codebase is in one line, how it is laid out in five minutes, and then a deep dive that follows a real request, job or command through the files that handle it. It states only what it read in the code, names the files it read and the ones it did not, and stays read-only.
Things you could ask for
Written the way you would actually say them. The agent plans the steps itself.
- “I start on this repository on Monday. Give me the one-line summary, the five-minute tour and the three files I should read first.”
- “Trace what happens when a user clicks “Pay” — from the frontend handler to the API route, the service, the database write and the webhook — with the file and function at each step.”
- “Which module owns sending email? Show me where it is called from and where its settings come from.”
- “Write an onboarding page for new engineers in our Notion, from the code, with a map of the services and how they talk to each other.”
- “List the parts of this codebase that look unused or duplicated, with the evidence, so I can ask the team about them.”
What you get back
A three-level orientation — one line, five minutes, deep dive — with a file path behind every statement; traced execution paths step by step; a repository map; answers to “what owns this?” with the call sites; and onboarding docs written into Notion or Google Docs. Every answer says which files were read and which were not.
Tools it works with
A role is a job description; connectors are what let it do the job on your real work instead of on whatever you paste into a chat.
Where it is the wrong tool
- It explains what the code says, not what it does at runtime. A remote agent reads through the GitHub or GitLab connector and cannot run the app, so configuration from the environment and behaviour behind feature flags are named as unknowns; a local agent with shell access can run it on your machine.
- It reads a large repository in parts. It tells you which areas it covered and which it did not, rather than claiming to understand a million lines from a sample.
- It does not review or rewrite. Its job is to make the code understandable; for findings and fixes, hand the same repository to the Code Reviewer.
- It needs access. Private repositories must be reachable through the connector, and some GitHub organisations require an owner’s approval before any third-party app can read them.
Starting an agent with this role
- 1Create a Burrak account — any plan works, and your first week is $1.
- 2In the Marketplace, open the Roles tab, find Codebase Onboarding Engineer and choose “Start an agent as Codebase Onboarding Engineer”. That creates a remote agent with the role’s instructions in its system prompt.
- 3Connect the tools it needs — GitHub, GitLab, Notion, Google Docs, Linear — from Connectors.
- 4Give it a brief. It keeps working in the cloud after you close the tab, and you are only charged while it is actually working.
The Codebase Onboarding Engineer role, in practice
- Why not just ask a chatbot about the code?
- A chatbot answers from what a model remembers about code that looks like yours. This role reads your repository through the connector and cites the file and function for each claim, so you can check every answer in a minute.
- Can it explain a legacy codebase with no documentation?
- That is where it helps most. It works from the code alone, says when a name is misleading or two modules do the same job, and writes the documentation that was missing as it goes.
- How is this different from the Technical Writer?
- Both read the code. The Technical Writer produces documentation for the people who use it — READMEs, API references, tutorials. The Codebase Onboarding Engineer explains the inside to the people about to change it: who owns what, and how a request travels through the files.
Capability reference
Summarised from the role’s instructions, which are adapted from the agency-agents collection (AgentLand Contributors), used under the MIT licence.
- Repository maps: entry points, manifests, services and boundaries
- Execution tracing from request or command to storage and back
- Three-level explanations: one line, five minutes, deep dive
- Ownership questions answered with the files and call sites as evidence
- Strictly read-only, stating what was and was not inspected
Your AI assistant is waiting.
Put it to work today.
Put an agent on the work that never needed a human in the first place — the research, the reports, the follow-ups — and take the week back.
$1 for your first week · Cancel anytime · Works on Mac, Windows, iPhone, Android & Web