# starred for turning GitHub stars into an Awesome-style list > starred is a Python command-line tool that turns a GitHub user's starred repositories into a grouped Markdown list, with optional language or topic grouping and direct repository updates. It fits developers who want their bookmark collection published as a refreshed README. **maguowei/starred** — Create and maintain your own Awesome-style list from GitHub stars! - Repository: https://github.com/maguowei/starred - Website: https://github.com/maguowei/awesome-stars - Stars: 1,960 · Forks: 97 - Language: Python - License: MIT - Published: 2026-10-16 · Updated: 2026-10-16 · Language: en - Canonical page: https://hysenlabs.com/projects/maguowei-starred ## Why starred turns bookmarks into a publishable list starred addresses a specific organizational problem: GitHub stars are useful as personal bookmarks, but they do not form a readable reference page on their own. The project converts those starred repositories into a Markdown document structured like an Awesome-style list. Its intended users are GitHub users who already maintain a meaningful collection of starred projects and want that collection exposed as a README. The default output groups repositories by language. A second mode groups them by GitHub repository topics, which can be more appropriate when a user's interests cross programming languages. Categories can also be sorted alphabetically. This is useful when automatic output needs a predictable table of contents, although the README does not document custom category names, ordering rules beyond alphabetical sorting, or hand-edited metadata. There are two delivery paths. Redirecting standard output produces a local Markdown file. Supplying a target repository asks starred to create or update a file there. The README also directs users to a template repository with a scheduled GitHub Actions workflow, which provides a more repeatable publishing model than manually running the command each time. The distinction matters. starred does not claim to discover repositories from trends, assess their quality, or replace editorial curation. It derives its list from stars that a user has already chosen. The generated page therefore represents that user's saved interests rather than an independently researched catalog. ## The starred CLI data flow and grouping choices The documented flow starts with a GitHub personal access token and a required `--username`. The `starred` command then retrieves repositories associated with those stars and prepares Markdown for standard output or a target repository. The README describes this operation as generating a Markdown list from starred repositories, but it does not document pagination, rate-limit handling, retry behavior, or the exact API calls used internally. The package metadata shows that the implementation depends on `click`, `requests`, `github3.py`, `gql`, and `aiohttp`. That dependency set is consistent with a command-line interface connected to GitHub, including both REST-style and GraphQL client libraries. However, the README does not map each dependency to a specific request, so the exact internal sequence should not be inferred beyond the user-visible collection, grouping, rendering, and update flow. Language grouping is the default. Passing `--topic` changes the grouping basis to repository topics, while `--topic_limit` sets a topic popularity threshold with a documented default of `500`. The README does not define precisely how that number is counted, so users who need exact inclusion rules should inspect the generated output before publishing it. Passing `--sort` sorts categories alphabetically. There is no documented option for sorting repositories within each category. Private repositories can be included with `--private`. That option changes the visibility of the source collection and therefore has access-control implications for the generated output. The README does not say whether starred prevents private repository links or descriptions from being written into a public target repository, so token scope and generated content require direct review. ## Installing starred and generating the first README starred requires Python 3.10 or later. The README gives `pip install starred` as the normal installation path for generating a first list: ```bash pip install starred ``` After installation, create a GitHub personal access token as described in the README and expose it through `GITHUB_TOKEN`. Then pass the GitHub username and redirect the generated Markdown into `README.md`. The `--sort` option makes category headings alphabetical. ```bash export GITHUB_TOKEN= starred --username --sort > README.md ``` The output file should contain the generated Markdown list. Inspect it locally before committing it, particularly if `--private` is used, because the README does not state what filtering or warning behavior applies to private entries. The console interface is available through the same command name. This is useful for confirming that installation succeeded and reviewing the documented options: ```bash starred --help ``` For contributors, the README documents `uv` as the development environment. Dependency synchronization installs the project and its development dependency group, after which the CLI help command can be invoked through `uv run`. ```bash uv sync --dev uv run starred --help ``` The README does not document a rollback procedure for a generated file or repository commit. It also does not state whether an interrupted direct update can leave a partial commit. For a first run, local redirection is therefore the less ambiguous path because the writer controls where the output file goes. ## Publishing generated lists through a GitHub repository starred can write its result directly to a GitHub repository. The documented command names the target with `--repository` and requests category sorting with `--sort`. According to the README, starred creates the repository when it does not already exist, then updates its `README.md`. ```bash export GITHUB_TOKEN= starred --username --repository awesome-stars --sort ``` The target filename defaults to `README.md`. The CLI also exposes `--filename` for a different file, `--message` for the commit message, and `--repository` for the target name. The README does not document conflict handling for unrelated local changes, retries after a failed API call, or a dry-run mode. A dry run is also absent from the documented common options. For recurring publication, the README directs users to create a repository from the linked `awesome-stars` template. The template includes a scheduled GitHub Actions workflow. Its workflow permissions must be set to `Read and write permissions`, and the workflow is run manually once before its schedule is changed. The README identifies `.github/workflows/schedules.yml` at line 5 as the location for the schedule. This setup reduces repeated local commands, but it transfers part of the trust boundary to GitHub Actions. The generated repository becomes the published copy, and its token needs write access for that file. The template is convenient, while the CLI remains more appropriate for controlled local generation and review. ## Topic grouping, private stars, and content boundaries The default language grouping is easy to understand, but it does not necessarily reflect the reason a repository was starred. A Python framework may be starred for deployment, documentation, or observability rather than for the Python language itself. Topic grouping addresses that problem by switching the organization basis with `--topic`, but it introduces filtering through `--topic_limit`, whose default is `500`. The README does not explain whether topics are combined, whether a repository can appear under several topics, or how missing topics are handled. It also does not say whether starred falls back to language grouping when a repository has no eligible topics. Those omissions limit how confidently users can predict the output. A user with a small or specific collection may need to inspect the Markdown before every publication. `--private` is the most consequential documented option. Including private repositories can make the generated output suitable for an internal audience, but the same output could expose repository names, descriptions, or links if sent to a public target. The README does not document an output visibility check. Reviewing the generated content and confirming the token's access before using `--private` is therefore necessary. The tool also has an editorial limitation. Stars indicate bookmarks, not verified recommendations. A repository may have been starred for temporary research, may no longer be relevant, or may not deserve a public endorsement. starred does not document freshness checks, descriptions, minimum quality thresholds, or a way to exclude individual starred repositories. It automates assembly, not curation. ## starred versus a manually maintained Awesome list The main alternative is a manually maintained Awesome-style README whose categories, descriptions, links, and ordering are edited by a person. The starred template shows the automated approach by refreshing a generated file, while a conventional list leaves those decisions in source control and in the editor's notes. The approaches serve different purposes. A manual list can explain why each project belongs and can remove irrelevant stars, but every addition or removal requires editorial work and a commit. starred can regenerate the structure from a user's existing stars, but its output inherits the quality and organization of those bookmarks. It also exposes only the grouping controls documented by the CLI. This is not a feature-by-feature comparison with another command-line package. It is a workflow comparison. Choose manual maintenance when descriptions, selective inclusion, and stable ordering matter more than automation. Choose starred when the source of truth is already a GitHub starring account and the desired result is a grouped, generated Markdown page. The repository uses the MIT license, and `pyproject.toml` identifies the package as `starred`, version `4.3.0`, with Python `>=3.10`. The license file should be reviewed for its actual terms. The package metadata also identifies the operating system as independent and lists Python 3.12, 3.13, and 3.14 as supported classifiers. ## Release history, maintenance signals, and upgrade work The latest listed release is v4.3.0 from 2023-01-14. Earlier releases are v4.2.0 from 2022-05-08 and v4.1.0 from 2022-05-07. The repository is not archived, and its last push was on 2026-08-04. The release history therefore shows a substantial gap between the latest listed release and the latest repository push, so the package version should not be assumed to reflect every repository change. The README's installation path is short because the project is distributed as a Python package. The development path uses `uv sync --dev`, while source tarball installation uses `uv build` followed by installation of the generated archive: ```bash uv build pip install dist/starred-.tar.gz ``` The `` text represents the documented filename pattern rather than a concrete release filename. `pyproject.toml` selects Hatchling as the build backend, and its project script entry is `starred = "starred.starred:starred"`. Upgrades may involve Python compatibility changes because the package requires `>=3.10` and declares newer Python classifiers. The README does not provide a migration guide, detailed changelog, supported GitHub API version, or rollback procedure. Users should treat version changes as ordinary package upgrades with output verification, especially when an existing README is managed automatically. ## Conclusion starred is appropriate for developers who want a generated README based on GitHub stars, but it is a poor fit for a manually curated resource list where descriptions and category membership require editorial judgment. Verify token permissions, repository scope, grouping thresholds, and the generated file in the target repository before enabling a scheduled workflow. For starred specifically, the latest listed release is v4.3.0 and the last push was on 2026-08-04. ## FAQ ### How do I install starred? Install it with `pip install starred`. The README requires Python 3.10 or later. ### How do I group starred repositories by topic? Run `starred` with the `--topic` option. The documented `--topic_limit` option controls a topic popularity threshold and defaults to `500`. ### Can starred update a README automatically? Yes. The `--repository` option targets a GitHub repository, and the README says the `awesome-stars` template includes a scheduled GitHub Actions workflow. ## Sources - [License: MIT](https://github.com/maguowei/starred/blob/main/LICENSE) - [maguowei/starred on GitHub](https://github.com/maguowei/starred) - [Project website](https://github.com/maguowei/awesome-stars) - [README](https://github.com/maguowei/starred/blob/main/README.md) - [Releases](https://github.com/maguowei/starred/releases) --- Hysen Labs editorial analysis, written from the project's own repository and release notes. Cite the canonical page: https://hysenlabs.com/projects/maguowei-starred