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Yes—a local language model can turn source files into useful project documentation, but the result is an informed reconstruction, not a guaranteed substitute for the original docs. In a September 25, 2026 account, Rich Edmonds describes using Ollama with Qwen 3.6:27b-q4_K_M on several PHP projects. He reports strong results for two small examples and missed details in a larger game. His “nearly perfect” verdict describes those examples, not a measured accuracy rate.
What the local LLM was asked to document
Edmonds’s account covers three projects of different sizes. The model was given project files and asked to document what they did. The reported examples offer a useful illustration of what source-based documentation can recover—and where its limits appeared.
| Example | Source provided | What Edmonds says the model captured |
|---|---|---|
| MyBB affiliate-management plugin | One file | The admin area, retailer and override configuration, URL rewriting on new replies, and caching. |
| Household waste collection site | Four PHP files totaling less than 15 KB, by Edmonds’s account | The dashboard, administration functions, and a JSON endpoint used by Home Assistant. |
| PHP game | 16 files, including controllers, services, and frontend files | Much of the backend functionality, but not every detail. |
For the waste collection site, Edmonds quoted a generated summary: “Based on the attached PHP files, this project is a lightweight, self-hosted web application designed to track and manage household waste collection schedules.” That is an example of the model’s output as reported by Edmonds, not an independent assessment of the description.
Why the small examples were easier to reconstruct
Small, focused projects give a model a more manageable set of source files to interpret. In the waste collection example, Edmonds listed four PHP files: index.php (4.3 KB), sync.php (360 B), api.php (2.1 KB), and admin.php (7.5 KB). He said they totaled less than 15 KB. That compact scope makes it plausible to infer a coherent picture of the application from the files, particularly when code paths and responsibilities are visible in the source.
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The plugin example was narrower still: a single file. Edmonds says the model identified several distinct behaviors, including configuration and reply-time URL rewriting. Such a result can be valuable when original documentation has disappeared, but it remains an interpretation of code. A summary may explain apparent behavior without establishing every operational detail or edge case.
What changed with the 16-file game
The game example shows why the small-project result should not be generalized. Edmonds says the model processed 16 PHP files spanning controllers, services, and frontend code. It captured much of the backend functionality but missed some details. As a project grows, behavior may depend on interactions across files, implicit assumptions, or paths that are not obvious from a quick summary of the code.
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The account does not identify every omission, so it cannot show which kinds of details were most likely to be missed. It does establish that the generated documentation was not complete in this larger example.
What “nearly perfect” does—and does not—establish
“Nearly perfect” is Edmonds’s assessment of selected examples. His September 25, 2026 article does not report a systematic comparison against ground truth, a measured error rate, an independent evaluation, or the complete generated documentation. It also does not provide the full prompts or model-generation settings. The report is a firsthand account, not a benchmark for arbitrary repositories.
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That distinction matters if you are deciding whether to rely on generated documentation. The examples support the narrower conclusion that a local model can infer useful structure and behavior from some source code. They do not establish how often it will omit a feature, misread a dependency, or confidently describe behavior that the code does not support.
Hardware and setup: one reported example, not a requirement
For the waste collection project, Edmonds says he used an AMD Radeon RX 7900 XT with 20 GB of VRAM while running Ollama and Qwen 3.6:27b-q4_K_M. This describes his setup for that example; it is not evidence that the same GPU is necessary, or that the model will perform identically on other hardware. The account does not provide enough configuration detail to derive a general hardware requirement.
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How to use generated documentation safely
Treat the output as a draft map of the codebase, then verify the claims that matter before relying on it. A practical review can focus on whether the documentation matches implementation rather than whether it reads smoothly.
- Check each described behavior against its implementation. Follow the relevant functions and call paths, especially for configuration, data updates, and external endpoints.
- Look for cross-file behavior. Trace how controllers, services, and frontend code connect; the game example shows that a model can miss details even when it captures much of the backend.
- Separate explicit facts from inferred intent. File names and comments can help, but confirm claims about what the application actually does in the executable code.
- Record uncertainty and gaps. If the source does not reveal a behavior or edge case clearly, label it as unknown rather than treating the model’s explanation as proof.
This review is especially important before using generated documentation for maintenance, security decisions, or handoffs: a plausible explanation is not the same as a verified description.
When this approach is useful
Source-to-documentation generation is most promising as a recovery aid for small, self-contained projects or as a starting point for larger ones. It can help orient a maintainer when the README or feature notes are missing, and it may quickly surface likely responsibilities of files and endpoints. For a more complex repository, plan for a human to check omissions and interactions rather than expecting one generated document to serve as complete project history.
Edmonds’s account is a concrete demonstration of that balance: strong reported results on a one-file plugin and a very small PHP site, followed by acknowledged omissions in a 16-file game. Read the full account at World Programming Solutions.
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