DeepWiki: understand a repository and check the answers

DeepWiki generates repository documentation, architecture diagrams, and source links so you can explore unfamiliar code and ask questions about it. Start with the repository overview, choose one behavior to investigate, and check the cited source before treating an answer as fact. Cognition’s repository wiki guide↗ (opens in a new tab) explains the public and connected-repository versions. fenbs gives you somewhere to keep the findings you have checked, so another assistant can continue the investigation without making you explain it again.

Where do you open the repository wiki?

For a public GitHub repository, open DeepWiki↗ (opens in a new tab) and find the repository you want to understand. You can also submit a public repository URL for indexing. For a private connected repository, Cognition documents access through the Devin sidebar at app.devin.ai/wiki; you need a Devin account and access to that repository.

1. Check the repository owner and name before reading. A fork with a familiar name can contain different code.
2. Read the overview and choose the part that relates to your question, such as request handling, storage, or the user interface.
3. Write down the behavior you need to understand before asking for an explanation.
4. Keep the repository URL beside your notes, along with the revision you eventually verify in the source.

Do not try to understand the whole repository in one sitting. A useful first result is a short map showing where a request enters, where its main work happens, and where the result leaves. That gives you a route through the code without pretending you have reviewed every part of it.

What should you ask before reading individual files?

Begin with a question about a real path through the application. “Explain the architecture” can produce a broad overview, but it leaves you deciding which details matter. “Where does an uploaded file get validated before storage?” gives you a claim you can investigate.

• For a new feature: which parts handle the closest existing behavior, and how do they call one another?
• For a bug: where is this value created, changed, and returned?
• For onboarding: which entry points and tests should I read first to understand this flow?
• For a boundary: where does the code reject an invalid request, and what happens afterward?

Ask for the relevant files and functions with each explanation. Treat an answer as a reading plan: follow the path it suggests, then see whether the code supports the story. Our broader guide to AI in software engineering workflows covers how to fit that investigation into reviewed engineering work.

How do you verify a source-linked answer?

A source link helps you inspect an answer; it does not make every sentence correct. Read enough surrounding code to understand the conditions under which the cited function runs. A check inside a helper means little if the path you care about never calls that helper.

1. Break the answer into small claims, such as “this endpoint validates the account before reading the record.”
2. Open the cited code and confirm that it belongs to the repository and revision you intend to study.
3. Trace callers and relevant conditions. Look for early returns, alternate paths, and configuration that changes the behavior.
4. Find an existing test or run a focused check in your own development environment when the claim concerns actual behavior.
5. Mark the conclusion as confirmed, partly checked, or still a question. Record the evidence behind that label.

For example, finding a permission helper confirms that the helper exists. Confirming access control requires checking that the relevant request reaches it and that a refusal prevents the protected operation. Keeping that distinction clear prevents an architectural summary from becoming an unsupported assurance.

What if an important folder is missing?

Cognition documents a steering file, .devin/wiki.json, at the repository root. It must contain both repo_notes and at least one pages entry. The pages list replaces automatic planning, so it needs to name every page you want, rather than only the missing section. These requirements are in the DeepWiki configuration documentation↗ (opens in a new tab).

If you maintain the repository, first decide what a newcomer needs to understand. Give each proposed page a clear purpose, such as explaining how the API passes work to a background process. Avoid requesting a page for every directory simply because the directory exists.

If you do not maintain it, keep investigating the source directly. An omitted page is a reason to narrow your question or read the missing area yourself. It is not evidence that the folder is unimportant, unused, or safe to ignore.

Can your own assistant ask DeepWiki questions?

Yes. Cognition provides a public, unauthenticated DeepWiki MCP server for public repositories. MCP is a standard way for an AI app to use an outside tool. The documented endpoint is https://mcp.deepwiki.com/mcp; it does not grant unauthenticated access to private repositories. See the DeepWiki MCP documentation↗ (opens in a new tab) for the service boundary.

Use our DeepWiki MCP guide when you want repository research inside another assistant. Keep the same evidence checks there: the conversation may be in a different app, but a generated explanation still needs to agree with the code.

If you are choosing a coding environment as well, Devin Desktop and Devin versus GitHub Copilot cover that separate question. Exploring a repository wiki and choosing the tool that will change the repository are different decisions.

What is worth keeping after the investigation?

Keep a small set of useful conclusions rather than a copy of every answer. Include the question, repository and revision, source paths, what you checked, and the next unresolved point. A future reader should be able to tell where the facts stop and your working theory begins.

• Confirmed finding: name the behavior and the source or test that supports it.
• Open question: say exactly which path or condition still needs investigation.
• Next step: identify the smallest useful check, and who will do it.

Put lasting findings where the next assistant can read them. That is the useful link between repository research and a shared work record; our AI at work guides cover more ways to keep the outcome of an AI session useful.

How to keep checked repository findings with fenbs?

Keep the code findings you checked and the question to answer next. You can carry on from the same point on any device or in another connected AI, without explaining the repository again.

1. Create a free account.
2. Write what you learned, add the source links, and say what you checked. Leave out guesses or mark them clearly.
3. Add a task for the question you still need to answer. Give it one clear next step.
4. If you use Devin for the work, connect Devin to fenbs; its cloud connection requires the relevant administrator permission.
5. Before stopping, save where you left off. Your next connected AI can read it so you can carry on from exactly there, on another device or in another AI.

fenbs keeps the work and its evidence; it does not generate a repository wiki or replace reading the code. If you only need a quick explanation and will not return to the investigation, the wiki and your source review may be enough.