github_roast
プロファイル分析 · 1.1K 月間訪問数
AIを活用し、公開されているGitHubプロフィールをユーモラスかつウィットに富んだ言葉で「ロースト（いじり）」するツールです。ユーザーのリポジトリ、貢献履歴、コーディング言語を分析し、多言語でパーソナライズされた面白いコメントを生成します。ユーモアのセンスがある開発者に最適です。
製品概要
github_roast 製品概要
AIを活用し、公開されているGitHubプロフィールをユーモラスかつウィットに富んだ言葉で「ロースト（いじり）」するツールです。ユーザーのリポジトリ、貢献履歴、コーディング言語を分析し、多言語でパーソナライズされた面白いコメントを生成します。ユーモアのセンスがある開発者に最適です。
Preview
StarLens 製品概要
AIを活用し、あなたのGitHubプロフィールとスターを付けたリポジトリを分析し、洞察に満ちた要約とウィットに富んだ「ロースト」（いじり）を生成するツールです。あなたのコーディングの興味が、あなた自身について何を明らかにしているのかを、楽しく共有可能な形式で発見しましょう。
Preview
Detailed feature comparison
| Feature | github_roast | StarLens |
|---|---|---|
| 主要カテゴリー | プロファイル分析 | コード分析 |
| 追加日 | 2025-08-04 | 2025-08-11 |
| 価格 | 無料 | 無料 |
| 公式サイト | github-roast.pages.dev | starlens.aisprint.dev |
| 製品タイプ | ウェブサイト | ウェブサイト |
| Performance data | ||
| ユーザー評価 | 未確認 | 未確認 |
| コメント | 0 | 0 |
| 月間訪問数 | 1.1K | 3.4K |
| 月間成長率 | 2.4% | 未確認 |
| お気に入り | 129 | 76 |
| Details | 詳細を見る | 詳細を見る |
github_roast vs StarLens monthly traffic
Compare github_roast and StarLens by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the github_roast vs StarLens monthly traffic comparison, github_roast currently shows 1.1K visits and StarLens shows 3.4K; StarLens has about 3 times the visible traffic of github_roast, an absolute difference of about 2.2K visits. This reflects visible reach, not feature quality or paid users.
Only github_roast has complete third-party traffic details; StarLens uses visits recorded inside ToolMage. These scopes cannot estimate market share directly, and on-site views should not be treated as the product’s total website traffic.
github_roast monthly traffic:
Latest traffic
月間訪問数
1.1K
平均滞在時間
0:10
訪問あたりページ数
1.32
直帰率
70.6%
Data updated 2026-06-15
Monthly traffic trend
- 2025/9: 1.4K 月間訪問数
- 2026/1: 1.6K 月間訪問数
- 2026/2: 695 月間訪問数
- 2026/3: 1.3K 月間訪問数
- 2026/4: 1.1K 月間訪問数
- 2026/5: 1.1K 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 40.96% | 463 |
| 🇨🇦Canada | 18.49% | 209 |
| 🇮🇳India | 14.85% | 168 |
| 🇮🇩Indonesia | 14.8% | 167 |
| 🇧🇷Brazil | 10.9% | 123 |
検索キーワード
github profile roastergithub profile roastinggithub repo roastroast my github
StarLens monthly traffic:
Latest traffic
月間訪問数
3.4K
Traffic-based selection guidance: The current traffic scope is not sufficient for a reliable product ranking. Treat monthly visits as a market-interest signal, then decide using taxonomy, use cases, pricing, and a like-for-like trial rather than reading exposure as product capability.
Usage comparison
Compare the core capabilities of github_roast and StarLens
github_roast Core features
プロファイル分析
ユーモア
StarLens Core features
コード分析
パーソナライズされたコンテンツ
分析
プロフィール強化
Use cases
github_roast Use cases
AI
コード分析
開発者
GitHub
オープンソース
ロースト
面白い
ジェネレーター
ユーモア
プロフィールレビュー
プログラミング
StarLens Use cases
AI
コード分析
開発者
GitHub
オープンソース
ロースト
開発者ツール
大規模言語モデル
n8n
プロフィール分析
weweb
github_roast vs StarLens：In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth github_roast vs StarLens comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. github_roast is primarily listed under “プロファイル分析”, while StarLens is primarily listed under “コード分析”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Primary category (github_roast: プロファイル分析; StarLens: コード分析); Monthly visits (github_roast: 1.1K; StarLens: 3.4K); Favorites (github_roast: 129; StarLens: 76); Website (github_roast: github-roast.pages.dev; StarLens: starlens.aisprint.dev); Added (github_roast: 2025-08-04; StarLens: 2025-08-11). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the github_roast vs StarLens monthly traffic comparison, github_roast currently shows 1.1K visits and StarLens shows 3.4K; StarLens has about 3 times the visible traffic of github_roast, an absolute difference of about 2.2K visits. This reflects visible reach, not feature quality or paid users.
Only github_roast has complete third-party traffic details; StarLens uses visits recorded inside ToolMage. These scopes cannot estimate market share directly, and on-site views should not be treated as the product’s total website traffic.
The current traffic scope is not sufficient for a reliable product ranking. Treat monthly visits as a market-interest signal, then decide using taxonomy, use cases, pricing, and a like-for-like trial rather than reading exposure as product capability.
Product positioning, use cases, and roles
github_roast and StarLens currently overlap in shared tags: AI、コード分析、開発者、GitHub、オープンソース、ロースト. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
github_roast's unique categories/tags are プロファイル分析、ユーモア、面白い、ジェネレーター、プロフィールレビュー、プログラミング; StarLens's are コード分析、パーソナライズされたコンテンツ、分析、プロフィール強化、開発者ツール、大規模言語モデル、n8n、プロフィール分析. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
What ratings, comments, and favorites can tell you
github_roast has no verified rating, 0 comments, 129 favorites, and 104 likes；StarLens has no verified rating, 0 comments, 76 favorites, and 89 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate github_roast first
Put github_roast on the priority trial list when the task aligns with “プロファイル分析” and especially プロファイル分析、ユーモア、面白い、ジェネレーター、プロフィールレビュー、プログラミング. This follows recorded positioning and does not imply unlisted capabilities are absent.
github_roast also currently records: pricing is free, product type is website, 1.1K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
When to evaluate StarLens first
Put StarLens on the priority trial list when the task aligns with “コード分析” and especially コード分析、パーソナライズされたコンテンツ、分析、プロフィール強化、開発者ツール、大規模言語モデル. This follows recorded positioning and does not imply unlisted capabilities are absent.
StarLens also currently records: pricing is free, product type is website, 3.4K on-site monthly views, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
How to validate the recommendation before deciding
The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in github_roast and StarLens, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.
比較 FAQ
How should I choose between github_roast and StarLens?
Compare positioning, pricing, taxonomy, and traffic maturity, then verify the latest details on each official website.
Where does this comparison data come from?
The factual baseline is derived from product, taxonomy, traffic, and community data. Reviewed editorial conclusions show their source and verification date.
What do unknown fields mean?
Unknown means there is not enough reliable evidence; the page does not fill gaps with assumptions.