Публічний реєстрПомірний
Звіт про здоров'я програмного забезпеченнясхема 0.27.0 · метрики 1.13.0 · 2026-07-25 14:08 UTC
luizfernandolj / mlquantify
A Python Quantification Library
luizfernandolj/mlquantify має індекс здоров’я 63 зі 100, що відповідає смузі «Помірний». Найвищий показник — Vitality (83/100), найнижчий — AI Readiness (33/100). Останнє оновлення було 22 дні тому. Більшість нещодавньої роботи виконує один учасник.
63
загалом / 100Індекс здоров'я програмного забезпечення
Метрики згруповано у зважені категорії на шкалі 1–100. Загальна оцінка починається як їхнє середнє; коли публічні дані активують Політику юрисдикцій високого ризику, рейтинг коригується й отримує верхню межу 49 («Під ризиком»). Готовність до ШІ не входить до індексу.
63
Відмінний85-100Зразковий; відповідає практично всім перевіреним критеріям
Добрий70-84Здоровий; незначні прогалини
Помірний50-69Прийнятний, але з помітними прогалинами; рекомендовано перевірку
У зоні ризику30-49Суттєві слабкі місця; впровадження потребує обережності
Критичний1-29Серйозні проблеми (покинутий, єдиний мейнтейнер, без базової гігієни)
Профіль оцінок
Кожна вісь — окрема категорія. Форма важить більше, ніж середнє: здоровий об'єкт заповнює всю фігуру, тоді як профіль із піками та провалами означає, що сила в одному вимірі маскує ризик в іншому.
Власність
Luiz FernandoОсобистий обліковий запис
7 підписників20 публічних репозиторіївз квіт. 2021 р.Unioeste
Цей репозиторій належить особистому обліковому запису. Проєкт з єдиним власником несе більший ризик безперервності, ніж підтримуваний організацією.
Пакетні екосистеми
| Реєстр | Пакет | Версія | Завантажень / міс | Версії | Остання публікація | Теги |
|---|---|---|---|---|---|---|
| PyPI | mlquantify | 0.5.1 | 2 674 | 51 | 28 днів тому | pythonmachine-learningquantificationquantify |
Метрики за категоріями
Життєздатність
Чи живий проєкт — чи пишеться код і чи виходять релізи?
83
Активність розробки
72Добрий
Як обчислюється оцінка
| 28.8/36 | Свіжість push — останній push 22 дн. тому |
| 15.2/36 | Ритм комітів — 22/52 тижнів із комітами |
| 18/18 | Обсяг комітів — 251 комітів за останній рік |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
Використані вхідні дані
| commits_last_year | 251 |
| human_commit_share | 1 |
| days_since_last_push | 22 |
| active_weeks_last_year | 22 |
Дисципліна релізів
100Відмінний
Як обчислюється оцінка
| 27/27 | Випускає релізи — опубліковано 40 релізів |
| 36/36 | Свіжість релізів — останній реліз 28 дн. тому |
| 27/27 | Ритм релізів — реліз кожні ~15,6 дн. |
| 0/10 | OpenSSF Scorecard: Signed-Releases — немає даних |
Використані вхідні дані
| releases_count | 40 |
| latest_release_tag | v0.5.1 |
| releases_from_tags | ні |
| days_since_latest_release | 28 |
| mean_days_between_releases | 15,6 |
Виключено з оцінювання (немає даних або не застосовно): OpenSSF Scorecard: Signed-Releases. Залишкові ваги перенормовано.
Спільнота та впровадження
Чи має проєкт користувачів, завантаження, увагу та влаштовані умови для контриб’юторів?
50
Популярність і впровадження
16Критичний
Як обчислюється оцінка
| 15.5/60 | Зірки — 10 зірок |
| 0/25 | Форки — 1 форків |
| 0/15 | Спостерігачі — 1 спостерігачів |
Використані вхідні дані
| forks | 1 |
| stars | 10 |
| watchers | 1 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Здоров'я спільноти
85Відмінний
Як обчислюється оцінка
| 22.5/22.5 | README |
| 22.5/22.5 | Ліцензія — визнана ліцензія (BSD-3-Clause) |
| 18/18 | Настанови CONTRIBUTING |
| 13.5/13.5 | Кодекс поведінки |
| 0/7.2 | Шаблон issue |
| 0/6.3 | Шаблон PR |
Використані вхідні дані
| has_readme | так |
| has_license | так |
| has_contributing | так |
| has_issue_template | ні |
| has_code_of_conduct | так |
| has_pull_request_template | ні |
Впровадження в екосистемі (завантаження)
57Помірний
Як обчислюється оцінка
| 45.7/80 | Щомісячні завантаження — 2 674 завантажень/місяць у pypi |
| 0/20 | Залежні пакети в реєстрі — ця екосистема цього не повідомляє |
Використані вхідні дані
| packages | mlquantify |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 2 674 |
Виключено з оцінювання (немає даних або не застосовно): Залежні пакети в реєстрі. Залишкові ваги перенормовано.
Сталість та врядування
Чи переживе проєкт своїх людей — бас-фактор, реактивність, хто за ним стоїть і як супроводжуються пакети?
54
Стійкість мейнтейнерів (бас-фактор)
15Критичний
Як обчислюється оцінка
| 9/54 | Бас-фактор — на 1 контриб’ютор(ів) припадає половина всіх комітів |
| 0.2/22.5 | Розподіл комітів — головний контриб’ютор — автор 99% комітів |
| 2.7/13.5 | Широта контриб’юторів — 2 контриб’юторів |
| 3/10 | OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3 |
Використані вхідні дані
| bus_factor | 1 |
| contributors_sampled | 2 |
| top_contributor_share | 0,989 |
Реактивність на issue та PR
72Добрий
Як обчислюється оцінка
| 0/46.8 | Вирішення issue — немає issue або даних |
| 38.2/38.3 | Прийняття PR — злито 1/1 вирішених PR |
| 0/15 | OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0 |
Використані вхідні дані
| merged_prs | 1 |
| open_issues | 0 |
| closed_issues | 0 |
| issue_closed_ratio | — |
| closed_unmerged_prs | 0 |
Виключено з оцінювання (немає даних або не застосовно): Вирішення issue. Залишкові ваги перенормовано.
Власність та опіка
46У зоні ризику
Як обчислюється оцінка
| 10/30 | Підтримка власника — особистий (користувацький) обліковий запис |
| 0/20 | Верифікований домен — не застосовно до користувацьких облікових записів |
| 6.5/25 | Охоплення власника — 7 підписників у luizfernandolj |
| 20.2/25 | Послужний список — 20 публічних репозиторіїв, вік облікового запису ~5 р. |
Використані вхідні дані
| followers | 7 |
| owner_type | User |
| is_verified | — |
| owner_login | luizfernandolj |
| public_repos | 20 |
| account_age_days | 1 922 |
Виключено з оцінювання (немає даних або не застосовно): Верифікований домен. Залишкові ваги перенормовано.
Супровід пакетів
100Відмінний
Як обчислюється оцінка
| 25/25 | Опубліковано й доступно — 1 пакет(ів) у pypi |
| 35/35 | Свіжість публікацій — остання публікація 28 дн. тому |
| 20/20 | Історія версій — 51 опублікованих версій |
| 20/20 | Не застарілий — активний, не deprecated і не yanked |
Використані вхідні дані
| packages | mlquantify |
| ecosystems | pypi |
| any_deprecated | ні |
| min_days_since_publish | 28 |
Інженерна якість
Чи наявні базові інженерні практики та документація?
72
Інженерні практики
60Помірний
Як обчислюється оцінка
| 24/24 | Процеси CI — 3 процес(ів) CI |
| 24/24 | Наявні тести |
| 0/16 | Конфігурація лінтера |
| 0/9.6 | Pre-commit-хуки |
| 0/6.4 | .editorconfig |
| 0/20 | OpenSSF Scorecard: CI-Tests — немає даних |
Використані вхідні дані
| has_ci | так |
| has_tests | так |
| has_editorconfig | ні |
| has_linter_config | ні |
| has_precommit_config | ні |
Виключено з оцінювання (немає даних або не застосовно): OpenSSF Scorecard: CI-Tests. Залишкові ваги перенормовано.
Документація
90Відмінний
Як обчислюється оцінка
| 30/30 | README |
| 25/25 | Каталог документації |
| 15/15 | Сайт документації / домашня сторінка — https://luizfernandolj.github.io/mlquantify/ |
| 10/10 | Опис репозиторію |
| 10/10 | Теми — 4 тем |
| 0/10 | Wiki |
Використані вхідні дані
| topics | machine-learning, prevalence-estimation, python, quantification |
| has_wiki | ні |
| homepage | https://luizfernandolj.github.io/mlquantify/ |
| has_readme | так |
| has_docs_dir | так |
| has_description | так |
Безпека
Чи міцні видимі практики безпеки й ланцюга постачання, без непослабленої пов’язаності з юрисдикціями високого ризику?
54
Стан безпеки
43У зоні ризику
Як обчислюється оцінка
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — branch protection not enabled on development/release branches |
| 0/2.5 | CI-Tests — немає даних |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 0/7.5 | Code-Review — Found 0/30 approved changesets -- score normalized to 0 |
| 0.8/2.5 | Contributors — project has 1 contributing companies or organizations -- score normalized to 3 |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 0/7.5 | Dependency-Update-Tool — no update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | Ліцензія — license file detected |
| 7.5/7.5 | Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| 5/5 | Packaging — packaging workflow detected |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 0/5 | SAST — no SAST tool detected |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — немає даних |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Використані вхідні дані
| source | openssf_scorecard |
| checks_evaluated | 16 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 2 |
| scorecard_aggregate | 4,3 |
Виключено з оцінювання (немає даних або не застосовно): ci_tests, signed_releases. Залишкові ваги перенормовано.
Сповіщення про залежності
100Відмінний
Як обчислюється оцінка
| 35/35 | Прямі залежності без відомих сповіщень — жодна пряма залежність не має відомих сповіщень |
| 25/25 | Непрямі залежності без відомих сповіщень — жодна непряма залежність не має відомих сповіщень |
| 0/40 | Немає задавнених сповіщень — жодне сповіщення не має дати публікації |
Використані вхідні дані
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 10 |
| unassessed_packages | 0 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
Виключено з оцінювання (немає даних або не застосовно): Немає задавнених сповіщень. Залишкові ваги перенормовано. Звірено з runtime-замиканням залежностей pypi:mlquantify@0.5.1 — тим, що тягне за собою встановлення опублікованого пакета, — 10 пакетів. Досяжність не аналізується.
Готовність до ШІ
Наскільки репозиторій оснащений для розробки та супроводу за участі ШІ-агентів? Незалежний, експериментальний бейдж — вага 0.0, тож він подається окремо і не впливає на загальний індекс здоров'я.
33
Контекст і настанови для агентів
4Критичний
Як обчислюється оцінка
| 0/45 | Інструкції для агентів — немає CLAUDE.md / AGENTS.md / правил редактора |
| 0/15 | Машиночитана документація (llms.txt) |
| 3.7/40 | Читабельна історія комітів — намір зазначено у 7 з 100 людських комітів (структурований заголовок або пояснювальний текст) |
Використані вхідні дані
| has_llms_txt | ні |
| legible_history_share | 0,07 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Цикл верифікації (збірка / тести / перевірка типів)
44У зоні ризику
Як обчислюється оцінка
| 18/18 | Розгортання однією командою — docs/Makefile |
| 22/22 | Автоматизовані тести |
| 0/11 | Конфігурація лінтера / форматера |
| 0/11 | Статична перевірка типів |
| 0/10 | Відтворюване середовище |
| 4/10 | Підтверджена практика роботи з агентами — 2 з останніх 100 комітів створено агентом або з його зазначенням |
| 0/8 | Автоматизоване супроводження — автоматичних оновлень залежностей не виявлено |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Використані вхідні дані
| has_nix | ні |
| has_tests | так |
| lockfiles | — |
| has_dockerfile | ні |
| typed_language | ні |
| bootstrap_files | docs/Makefile |
| has_devcontainer | ні |
| has_linter_config | ні |
| typecheck_configs | — |
| agent_commit_share | 0,02 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Читабельність коду для моделей
55Помірний
Як обчислюється оцінка
| 0/45 | Типізований код — Python без конфігурації перевірки типів |
| 55/55 | Керовані розміри файлів — 0/133 файлів вихідного коду понад 60 КБ |
Використані вхідні дані
| primary_language | Python |
| largest_source_bytes | 51 515 |
| source_files_sampled | 133 |
| oversized_source_files | 0 |
Машиночитні інтерфейси
40У зоні ризику
Як обчислюється оцінка
| 0/40 | Схема API (OpenAPI/GraphQL/proto) |
| 0/20 | Сервер MCP |
| 40/40 | Придатні до запуску приклади — examples |
Використані вхідні дані
| example_dirs | examples |
| has_mcp_signal | ні |
| api_schema_files | — |
Ключові факти
10зірок GitHub
2контриб'юторів
251комітів за останні 12 місяців
22днів від останнього пушу
40релізів
1бас-фактор
0відкритих issue
PyPIпакетних екосистем
Попередження щодо збору даних
- Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
Докладніше
OpenSSF Scorecard 4.3 / 10
4.3сукупно
Незалежна, не прив'язана до інструментів оцінка безпеки від відкритого проєкту OpenSSF Scorecard. Кожна перевірка винагороджує практику безпеки, а не інструмент конкретного постачальника. Перевірки, які Scorecard не зміг визначити, позначено н/д і виключено з оцінки безпеки (вони ніколи не зараховуються як нуль).
| 10 | Binary-Artifacts | no binaries found in the repo |
| 0 | Branch-Protection | branch protection not enabled on development/release branches |
| н/д | CI-Tests | no pull request found |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 0 | Code-Review | Found 0/30 approved changesets -- score normalized to 0 |
| 3 | Contributors | project has 1 contributing companies or organizations -- score normalized to 3 |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 0 | Dependency-Update-Tool | no update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 10 | Maintained | 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| 10 | Packaging | packaging workflow detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | no SAST tool detected |
| 0 | Security-Policy | security policy file not detected |
| н/д | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
Прямі залежності 6
| Реєстр | Пакет | Обмеження версії | Маніфест |
|---|---|---|---|
| PyPI | scikit-learn | >=1.1 | pyproject.toml |
| PyPI | numpy | >=1.23 | pyproject.toml |
| PyPI | scipy | >=1.8 | pyproject.toml |
| PyPI | joblib | >=1.1 | pyproject.toml |
| PyPI | tqdm | >=4.60 | pyproject.toml |
| PyPI | pandas | >=1.4 | pyproject.toml |
Усі залежності 10
Повний розв'язаний набір залежностей із графа залежностей GitHub: 6 прямих і 4 непрямих (транзитивних) пакетів. Транзитивне замикання є повним, коли в репозиторії закомічено lockfile.
| Реєстр | Пакет | Версія | Зв'язок |
|---|---|---|---|
| PyPI | joblib | — | пряма |
| PyPI | numpy | — | пряма |
| PyPI | pandas | — | пряма |
| PyPI | scikit-learn | — | пряма |
| PyPI | scipy | — | пряма |
| PyPI | tqdm | — | пряма |
| PyPI | cython | — | непряма |
| PyPI | matplotlib | — | непряма |
| PyPI | setuptools | — | непряма |
| PyPI | torch | — | непряма |
Сповіщення про залежності 0
Встановлення pypi:mlquantify@0.5.1 тягне 10 пакетів, прямих і транзитивних: 0 мають відомі сповіщення, з них 0 — прямі залежності.
Жодне відоме сповіщення не стосується оцінених залежностей.
Сповіщення означає, що версія, записана в графі залежностей, потрапляє в уражений діапазон. Досяжність не аналізується, а граф містить піниї розробки й тестування — знахідка може стосуватися інструментів, а не поставленого коду.
Звіт у форматі JSON машиночитний
{
"data": {
"repo": {
"topics": [
"machine-learning",
"prevalence-estimation",
"python",
"quantification"
],
"is_fork": false,
"size_kb": 114551,
"has_wiki": false,
"homepage": "https://luizfernandolj.github.io/mlquantify/",
"languages": {
"Cython": 4327,
"Python": 812730
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"max_points": 6.3
}
]
},
{
"key": "ecosystem_adoption",
"band": "moderate",
"name": "Ecosystem adoption (downloads)",
"note": "Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"registry_dependents"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 57,
"inputs": {
"packages": [
"mlquantify"
],
"dependents": null,
"ecosystems": "pypi",
"total_downloads": null,
"monthly_downloads": 2674
},
"components": [
{
"key": "monthly_downloads",
"name": "Monthly downloads",
"detail": "2,674 downloads/month across pypi",
"points": 45.7,
"status": "partial",
"details": [
{
"code": "downloads_monthly",
"params": {
"count": 2674,
"ecosystems": "pypi"
}
}
],
"max_points": 80
},
{
"key": "registry_dependents",
"name": "Registry dependents",
"detail": "not reported by this ecosystem",
"points": 0,
"status": "excluded",
"details": [
{
"code": "not_reported_by_this_ecosystem",
"params": {}
}
],
"max_points": 20
}
]
}
],
"description": "Does the project have users, downloads, attention, and a welcoming setup for contributors?"
},
{
"key": "governance",
"band": "moderate",
"name": "Sustainability & Governance",
"value": 54,
"weight": 0.24,
"metrics": [
{
"key": "maintainer_resilience",
"band": "critical",
"name": "Maintainer resilience (bus factor)",
"note": null,
"notes": [],
"value": 15,
"inputs": {
"bus_factor": 1,
"contributors_sampled": 2,
"top_contributor_share": 0.989
},
"components": [
{
"key": "bus_factor",
"name": "Bus factor",
"detail": "1 contributor(s) cover half of all commits",
"points": 9,
"status": "partial",
"details": [
{
"code": "bus_factor",
"params": {
"count": 1
}
}
],
"max_points": 54
},
{
"key": "commit_distribution",
"name": "Commit distribution",
"detail": "top contributor authored 99% of commits",
"points": 0.2,
"status": "partial",
"details": [
{
"code": "top_contributor_share",
"params": {
"share": 99
}
}
],
"max_points": 22.5
},
{
"key": "contributor_breadth",
"name": "Contributor breadth",
"detail": "2 contributors",
"points": 2.7,
"status": "partial",
"details": [
{
"code": "contributors_sampled",
"params": {
"count": 2
}
}
],
"max_points": 13.5
},
{
"key": "openssf_scorecard_contributors",
"name": "OpenSSF Scorecard: Contributors",
"detail": "project has 1 contributing companies or organizations -- score normalized to 3",
"points": 3,
"status": "partial",
"details": [],
"max_points": 10
}
]
},
{
"key": "responsiveness",
"band": "good",
"name": "Issue & PR responsiveness",
"note": "Excluded from scoring (no data or not applicable): Issue resolution. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"issue_resolution"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 72,
"inputs": {
"merged_prs": 1,
"open_issues": 0,
"closed_issues": 0,
"issue_closed_ratio": null,
"closed_unmerged_prs": 0
},
"components": [
{
"key": "issue_resolution",
"name": "Issue resolution",
"detail": "no issues or no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_issues_or_data",
"params": {}
}
],
"max_points": 46.75
},
{
"key": "pr_acceptance",
"name": "PR acceptance",
"detail": "1/1 decided PRs merged",
"points": 38.2,
"status": "met",
"details": [
{
"code": "decided_prs_merged",
"params": {
"merged": 1,
"decided": 1
}
}
],
"max_points": 38.25
},
{
"key": "openssf_scorecard_code_review",
"name": "OpenSSF Scorecard: Code-Review",
"detail": "Found 0/30 approved changesets -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
}
]
},
{
"key": "stewardship",
"band": "at_risk",
"name": "Ownership & stewardship",
"note": "Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"verified_domain"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 46,
"inputs": {
"followers": 7,
"owner_type": "User",
"is_verified": null,
"owner_login": "luizfernandolj",
"public_repos": 20,
"account_age_days": 1922
},
"components": [
{
"key": "ownership_backing",
"name": "Ownership backing",
"detail": "personal (user) account",
"points": 10,
"status": "partial",
"details": [
{
"code": "owner_personal",
"params": {}
}
],
"max_points": 30
},
{
"key": "verified_domain",
"name": "Verified domain",
"detail": "not applicable to user accounts",
"points": 0,
"status": "excluded",
"details": [
{
"code": "not_applicable_to_user_accounts",
"params": {}
}
],
"max_points": 20
},
{
"key": "owner_reach",
"name": "Owner reach",
"detail": "7 followers of luizfernandolj",
"points": 6.5,
"status": "partial",
"details": [
{
"code": "owner_followers",
"params": {
"count": 7,
"login": "luizfernandolj"
}
}
],
"max_points": 25
},
{
"key": "track_record",
"name": "Track record",
"detail": "20 public repos, account ~5 yr old",
"points": 20.2,
"status": "partial",
"details": [
{
"code": "public_repos",
"params": {
"count": 20
}
},
{
"code": "account_age_years",
"params": {
"years": 5
}
}
],
"max_points": 25
}
]
},
{
"key": "package_maintenance",
"band": "excellent",
"name": "Package maintenance",
"note": null,
"notes": [],
"value": 100,
"inputs": {
"packages": [
"mlquantify"
],
"ecosystems": "pypi",
"any_deprecated": false,
"min_days_since_publish": 28
},
"components": [
{
"key": "published_resolvable",
"name": "Published & resolvable",
"detail": "1 package(s) on pypi",
"points": 25,
"status": "met",
"details": [
{
"code": "packages_published",
"params": {
"count": 1,
"ecosystems": "pypi"
}
}
],
"max_points": 25
},
{
"key": "publish_recency",
"name": "Publish recency",
"detail": "latest publish 28 days ago",
"points": 35,
"status": "met",
"details": [
{
"code": "publish_recency",
"params": {
"days": 28
}
}
],
"max_points": 35
},
{
"key": "version_history",
"name": "Version history",
"detail": "51 published versions",
"points": 20,
"status": "met",
"details": [
{
"code": "published_versions",
"params": {
"count": 51
}
}
],
"max_points": 20
},
{
"key": "not_deprecated",
"name": "Not deprecated",
"detail": "active, not deprecated or yanked",
"points": 20,
"status": "met",
"details": [
{
"code": "package_not_deprecated",
"params": {}
}
],
"max_points": 20
}
]
}
],
"description": "Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?"
},
{
"key": "engineering",
"band": "good",
"name": "Engineering Quality",
"value": 72,
"weight": 0.2,
"metrics": [
{
"key": "engineering_practices",
"band": "moderate",
"name": "Engineering practices",
"note": "Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"openssf_scorecard_ci_tests"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 60,
"inputs": {
"has_ci": true,
"has_tests": true,
"has_editorconfig": false,
"has_linter_config": false,
"has_precommit_config": false
},
"components": [
{
"key": "ci_workflows",
"name": "CI workflows",
"detail": "3 workflow(s)",
"points": 24,
"status": "met",
"details": [
{
"code": "ci_workflows",
"params": {
"count": 3
}
}
],
"max_points": 24
},
{
"key": "tests_present",
"name": "Tests present",
"detail": null,
"points": 24,
"status": "met",
"details": [],
"max_points": 24
},
{
"key": "linter_config",
"name": "Linter config",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 16
},
{
"key": "pre_commit_hooks",
"name": "Pre-commit hooks",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 9.6
},
{
"key": "editorconfig",
"name": ".editorconfig",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 6.4
},
{
"key": "openssf_scorecard_ci_tests",
"name": "OpenSSF Scorecard: CI-Tests",
"detail": "no pull request found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 20
}
]
},
{
"key": "documentation",
"band": "excellent",
"name": "Documentation",
"note": null,
"notes": [],
"value": 90,
"inputs": {
"topics": [
"machine-learning",
"prevalence-estimation",
"python",
"quantification"
],
"has_wiki": false,
"homepage": "https://luizfernandolj.github.io/mlquantify/",
"has_readme": true,
"has_docs_dir": true,
"has_description": true
},
"components": [
{
"key": "readme",
"name": "README",
"detail": null,
"points": 30,
"status": "met",
"details": [],
"max_points": 30
},
{
"key": "documentation_directory",
"name": "Documentation directory",
"detail": null,
"points": 25,
"status": "met",
"details": [],
"max_points": 25
},
{
"key": "documentation_homepage_site",
"name": "Documentation / homepage site",
"detail": "https://luizfernandolj.github.io/mlquantify/",
"points": 15,
"status": "met",
"details": [],
"max_points": 15
},
{
"key": "repository_description",
"name": "Repository description",
"detail": null,
"points": 10,
"status": "met",
"details": [],
"max_points": 10
},
{
"key": "topics",
"name": "Topics",
"detail": "4 topics",
"points": 10,
"status": "met",
"details": [
{
"code": "topics_count",
"params": {
"count": 4
}
}
],
"max_points": 10
},
{
"key": "wiki",
"name": "Wiki",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
}
]
}
],
"description": "Are baseline engineering and documentation practices in place?"
},
{
"key": "security",
"band": "moderate",
"name": "Security",
"value": 54,
"weight": 0.16,
"metrics": [
{
"key": "security_posture",
"band": "at_risk",
"name": "Security posture",
"note": "Excluded from scoring (no data or not applicable): CI-Tests, Signed-Releases. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"ci_tests",
"signed_releases"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 43,
"inputs": {
"source": "openssf_scorecard",
"checks_evaluated": 16,
"scorecard_version": "v5.5.0",
"checks_inconclusive": 2,
"scorecard_aggregate": 4.3
},
"components": [
{
"key": "binary_artifacts",
"name": "Binary-Artifacts",
"detail": "no binaries found in the repo",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
},
{
"key": "branch_protection",
"name": "Branch-Protection",
"detail": "branch protection not enabled on development/release branches",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "ci_tests",
"name": "CI-Tests",
"detail": "no pull request found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 2.5
},
{
"key": "cii_best_practices",
"name": "CII-Best-Practices",
"detail": "no effort to earn an OpenSSF best practices badge detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 2.5
},
{
"key": "code_review",
"name": "Code-Review",
"detail": "Found 0/30 approved changesets -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "contributors",
"name": "Contributors",
"detail": "project has 1 contributing companies or organizations -- score normalized to 3",
"points": 0.8,
"status": "partial",
"details": [],
"max_points": 2.5
},
{
"key": "dangerous_workflow",
"name": "Dangerous-Workflow",
"detail": "no dangerous workflow patterns detected",
"points": 10,
"status": "met",
"details": [],
"max_points": 10
},
{
"key": "dependency_update_tool",
"name": "Dependency-Update-Tool",
"detail": "no update tool detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "fuzzing",
"name": "Fuzzing",
"detail": "project is not fuzzed",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "license",
"name": "License",
"detail": "license file detected",
"points": 2.5,
"status": "met",
"details": [],
"max_points": 2.5
},
{
"key": "maintained",
"name": "Maintained",
"detail": "30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
},
{
"key": "packaging",
"name": "Packaging",
"detail": "packaging workflow detected",
"points": 5,
"status": "met",
"details": [],
"max_points": 5
},
{
"key": "pinned_dependencies",
"name": "Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "sast",
"name": "SAST",
"detail": "no SAST tool detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "security_policy",
"name": "Security-Policy",
"detail": "security policy file not detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "signed_releases",
"name": "Signed-Releases",
"detail": "no releases found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 7.5
},
{
"key": "token_permissions",
"name": "Token-Permissions",
"detail": "detected GitHub workflow tokens with excessive permissions",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
"detail": "0 existing vulnerabilities detected",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
}
]
},
{
"key": "dependency_advisories",
"band": "excellent",
"name": "Dependency advisories",
"note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:mlquantify@0.5.1 runtime dependency closure — what installing the published package pulls in — 10 packages. Reachability is not analyzed.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"no_advisories_left_outstanding"
]
}
},
{
"code": "weights_renormalized",
"params": {}
},
{
"code": "advisories_scope_published",
"params": {
"package": "pypi:mlquantify@0.5.1",
"assessed": 10
}
},
{
"code": "advisories_reachability",
"params": {}
}
],
"value": 100,
"inputs": {
"source": "osv",
"advisories": 0,
"affected_packages": 0,
"assessed_packages": 10,
"unassessed_packages": 0,
"affected_by_severity": "none",
"direct_affected_packages": 0
},
"components": [
{
"key": "direct_dependencies_free_of_known_advisories",
"name": "Direct dependencies free of known advisories",
"detail": "no direct dependency carries a known advisory",
"points": 35,
"status": "met",
"details": [
{
"code": "no_direct_advisories",
"params": {}
}
],
"max_points": 35
},
{
"key": "indirect_dependencies_free_of_known_advisories",
"name": "Indirect dependencies free of known advisories",
"detail": "no indirect dependency carries a known advisory",
"points": 25,
"status": "met",
"details": [
{
"code": "no_indirect_advisories",
"params": {}
}
],
"max_points": 25
},
{
"key": "no_advisories_left_outstanding",
"name": "No advisories left outstanding",
"detail": "no advisory carries a publication date",
"points": 0,
"status": "excluded",
"details": [
{
"code": "advisories_no_publication_date",
"params": {}
}
],
"max_points": 40
}
]
},
{
"key": "malicious_dependencies",
"band": "excellent",
"name": "Malicious dependencies",
"note": null,
"notes": [],
"value": 100,
"inputs": {
"source": "osv",
"meaning": "reported as a malicious package by the OpenSSF corpus; the remedy is removal or moving off the compromised name, never an upgrade of the same artifact. Versions the registry has since pulled are listed but not scored",
"packages": [],
"red_flag": false,
"assessed_packages": 10,
"malicious_packages": 0,
"direct_malicious_packages": 0,
"withdrawn_malicious_packages": 0,
"installable_malicious_packages": 0
},
"components": [
{
"key": "no_dependency_reported_as_a_malicious_package",
"name": "No dependency reported as a malicious package",
"detail": "no dependency is reported as a malicious package",
"points": 100,
"status": "met",
"details": [
{
"code": "no_malicious_dependencies",
"params": {}
}
],
"max_points": 100
}
]
},
{
"key": "high_risk_jurisdiction_exposure",
"band": "excellent",
"name": "High-Risk Jurisdiction Exposure",
"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
"meaning": "self-published location evidence; not nationality or citizenship",
"red_flag": false,
"exposures": [],
"policy_countries": [
"Russia",
"Iran",
"North Korea"
],
"review_only_matches": 0,
"assessed_self_published_locations": 2
},
"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "at_risk",
"name": "AI Readiness",
"value": 33,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "critical",
"name": "Agent context & guidance",
"note": null,
"notes": [],
"value": 4,
"inputs": {
"has_llms_txt": false,
"legible_history_share": 0.07,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
"name": "Machine-readable docs (llms.txt)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
"name": "Legible commit history",
"detail": "7 of 100 human commits state their intent (structured subject or explanatory body)",
"points": 3.7,
"status": "partial",
"details": [
{
"code": "legible_history",
"params": {
"legible": 7,
"sampled": 100
}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "at_risk",
"name": "Verify loop (build / test / typecheck)",
"note": null,
"notes": [],
"value": 44,
"inputs": {
"has_nix": false,
"has_tests": true,
"lockfiles": [],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [
"docs/Makefile"
],
"has_devcontainer": false,
"has_linter_config": false,
"typecheck_configs": [],
"agent_commit_share": 0.02,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": "docs/Makefile",
"points": 18,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "docs/Makefile"
}
}
],
"max_points": 18
},
{
"key": "automated_tests",
"name": "Automated tests",
"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
"name": "Lint / format config",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
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{
"key": "demonstrated_agent_practice",
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},
{
"key": "automated_maintenance",
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}
],
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},
{
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"detail": "dependency not pinned by hash detected -- score normalized to 0",
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"status": "missed",
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]
},
{
"key": "ai_code_legibility",
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"name": "Code legibility for models",
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"notes": [],
"value": 55,
"inputs": {
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"largest_source_bytes": 51515,
"source_files_sampled": 133,
"oversized_source_files": 0
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Python without a type-check config",
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"status": "missed",
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},
{
"key": "manageable_file_sizes",
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"points": 55,
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]
},
{
"key": "ai_interfaces",
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"name": "Machine-readable interfaces",
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"notes": [],
"value": 40,
"inputs": {
"example_dirs": [
"examples"
],
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},
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{
"key": "api_schema_openapi_graphql_proto",
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},
{
"key": "runnable_examples",
"name": "Runnable examples",
"detail": "examples",
"points": 40,
"status": "met",
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"code": "file_list",
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}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
}
],
"metrics_version": "1.13.0"
},
"warnings": [
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],
"report_type": "repository",
"generated_at": "2026-07-25T14:08:58.686498Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/l/luizfernandolj/mlquantify.svg",
"full_name": "luizfernandolj/mlquantify",
"license_state": "standard",
"license_spdx": "BSD-3-Clause"
}Оцінки — це сигнали, а не гарантії. Вони відображають публічно видимі практики на GitHub — це не аудит коду й не гарантія безпеки.
Відсутні дані виключаються, а ваги перенормовуються — нуль за відсутність ніколи не ставиться. Методологія версіонована й відкрита: метрики v1.13.0, схема v0.27.0 — повна методологія · вікі метрик.
Як окремий результат виглядає на тлі всього реєстру: сукупна статистика — PyPI.