Hands-on workflow

From repository to first architecture map: a practical codebase mapping workflow

Use the repository as evidence, an indexer as a jump start, and engineering judgment to turn the result into a map that explains how the system works.

A new codebase rarely comes with a trustworthy map. A README may describe the intended system, while deployments and source code reveal how it actually runs. Starting from an empty canvas can be daunting, but treating an automatically generated diagram as ground truth is risky too. The most useful first map is a reviewed hypothesis: grounded in source, focused on a clear boundary, and corrected with people who know the system.

The open-source tld project includes source indexing commands intended to help generate a codebase map and watch repository changes. The repository README points to tld doctor for checking source-indexing prerequisites and tld index --help for current options. Consult those commands in the version you install, since language support and flags can evolve.

1. Decide what the map should explain

Choose a scope before indexing. “The whole company platform” is usually too broad for a first pass. A better target is one repository, one deployable application, or one request path such as checkout or document upload. Write a question for the map: Which processes handle this workflow? Where does data persist? Which external systems are called?

This question prevents an index from becoming a catalog of every package. It also helps you decide what counts as a meaningful result. A map of one product path might need a browser client, API service, queue worker, database, and payment provider, while leaving utilities and tests out of the high-level view.

2. Establish the code and deployment context

Before opening an indexer, inspect the repository’s top-level directories, build files, deployment manifests, and current README. Note the languages, executable entry points, infrastructure definitions, and generated directories. Identify the commit or branch you are mapping so that later reviewers can relate findings to the same source state.

If the tool reports missing parser prerequisites, follow its diagnostic output instead of assuming all languages will be understood. An indexer’s supported language subset is a technical constraint, and generated output can be incomplete when parts of the repository are not parsed.

3. Generate a first pass, then inspect it

Use the installed CLI help to select the repository indexing workflow. The project documents tld index for indexing a repository, generating a codebase map, or watching changes. It also describes source-grounded elements as a way to jump-start diagramming. These features can reduce initial manual entry, but generated nodes and edges still need interpretation.

Look for the shape of the result rather than trying to perfect every label immediately. Are the apparent entry points plausible? Do the major modules align with service or package boundaries? Are there unexpected connections that might be generated code, test wiring, or generic utility calls? Record uncertainty rather than quietly turning a guess into an architectural fact.

4. Validate the map with two kinds of evidence

First compare it with runtime and deployment evidence. Check service manifests, container definitions, infrastructure configuration, and environment variables. Source dependencies do not always correspond to network dependencies, and a package boundary is not automatically a deployable boundary.

Then review the map with someone who operates or changes the system. Ask them to walk through a real workflow and correct the ownership, data flow, and external system names. They may explain that an apparently central module is only a compatibility layer, or that a queue consumer runs as a separate process. Capture the explanation in labels or notes when it helps the next reader.

5. Shape the result for readers

Organize the first view around the question you chose. Keep only the main elements and relationships there. If a service contains enough internal structure to merit more detail, describe it in its own view rather than adding every module to the overview. tlDiagram’s documented model lets an element have its own view, supporting a nested way to explore systems. Use this structure only where the extra depth answers a reader’s question.

Choose precise labels. “Database” is less useful than “Orders database” if ownership or data domain matters. Label connections with the purpose or interaction that distinguishes them, but avoid cluttering them with low-value implementation details. Add a short note when an important caveat cannot be expressed by the diagram’s structure alone.

6. Make it maintainable

Decide where the diagram source belongs and who reviews meaningful changes. The project documents local YAML synchronization with its self-hosted UI and cloud version, and its CLI can inspect or update diagram data. Teams can keep selected architecture changes near code review, but should not make routine implementation patches carry irrelevant diagram churn.

Start with a narrow maintenance rule: update the map when a change alters a boundary, an important dependency, or the workflow the view explains. Revisit the map after a few changes and remove detail that nobody uses. A small, accurate map that helps answer a recurring question is a stronger starting point than a comprehensive output nobody trusts.

For current indexing workflows, see the tlDiagram CLI documentation and the open-source tld repository.