Публічний реєстр
Звіт про здоров'я програмного забезпеченнясхема 0.27.0 · метрики 1.13.0 · 2026-07-24 20:49 UTC

tensor-systems / droste

Recursive analysis engine for data too large for a context window, built with Recursive Language Models (RLMs).

PythonApache-2.0★ 1 зірка⑂ 0 форківз лип. 2026 р.Переглянути на GitHub ↗

tensor-systems/droste має індекс здоров’я 54 зі 100, що відповідає смузі «Помірний». Найвищий показник — Vitality (71/100), найнижчий — Community & Adoption (33/100). Останнє оновлення — сьогодні. Більшість нещодавньої роботи виконує один учасник.

54
загалом / 100
Помірний

Індекс 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.

54
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)
ЖиттєздатністьСпільнота тавпровадженняСталість таврядуванняІнженернаякістьБезпекаГотовність доШІ

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

tensor-systemsОрганізація
0 підписників4 публічні репозиторіїз лют. 2026 р.

За цим репозиторієм стоїть організація — спільна, підзвітна опіка, здатна пережити будь-якого окремого мейнтейнера.

Пакетні екосистеми

РеєстрПакетВерсіяЗавантажень / місВерсіїОстання публікаціяТеги
PyPIdroste0.20.0-280 днів томуclidata-analysislong-contextrecursive-analysisrecursive-language-modelrlm

Метрики за категоріями

Життєздатність

Чи живий проєкт — чи пишеться код і чи виходять релізи?

71Добрий · 22% загального індексу
Як обчислюється оцінка
36/36Свіжість push — останній push 0 дн. тому
4.8/36Ритм комітів — 7/52 тижнів із комітами
18/18Обсяг комітів — 242 комітів за останній рік
0/10OpenSSF Scorecard: Maintained — project was created within the last 90 days. Please review its contents carefully
Використані вхідні дані
commits_last_year242
human_commit_share1
days_since_last_push0
active_weeks_last_year7
Як обчислюється оцінка
27/27Випускає релізи — опубліковано 28 релізів
36/36Свіжість релізів — останній реліз 0 дн. тому
27/27Ритм релізів — реліз кожні ~1 дн.
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Використані вхідні дані
releases_count28
latest_release_tagv0.20.0
releases_from_tagsні
days_since_latest_release0
mean_days_between_releases1

Спільнота та впровадження

Чи має проєкт користувачів, завантаження, увагу та влаштовані умови для контриб’юторів?

33У зоні ризику · 18% загального індексу
Як обчислюється оцінка
0/60Зірки — 1 зірок
0/25Форки — 0 форків
0/15Спостерігачі — 0 спостерігачів
Використані вхідні дані
forks0
stars1
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Як обчислюється оцінка
22.5/22.5README
22.5/22.5Ліцензія — визнана ліцензія (Apache-2.0)
18/18Настанови CONTRIBUTING
0/13.5Кодекс поведінки
0/7.2Шаблон issue
0/6.3Шаблон PR
Використані вхідні дані
has_readmeтак
has_licenseтак
has_contributingтак
has_issue_templateні
has_code_of_conductні
has_pull_request_templateні

Сталість та врядування

Чи переживе проєкт своїх людей — бас-фактор, реактивність, хто за ним стоїть і як супроводжуються пакети?

53Помірний · 24% загального індексу
Як обчислюється оцінка
9/54Бас-фактор — на 1 контриб’ютор(ів) припадає половина всіх комітів
0/22.5Розподіл комітів — головний контриб’ютор — автор 100% комітів
1.4/13.5Широта контриб’юторів — 1 контриб’юторів
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Використані вхідні дані
bus_factor1
contributors_sampled1
top_contributor_share1
Як обчислюється оцінка
40.6/46.8Вирішення issue — закрито 87% issue
37.9/38.3Прийняття PR — злито 104/105 вирішених PR
0/15OpenSSF Scorecard: Code-Review — Found 0/25 approved changesets -- score normalized to 0
Використані вхідні дані
merged_prs104
open_issues12
closed_issues79
issue_closed_ratio0,868
closed_unmerged_prs1

Власність та опіка

36У зоні ризику
Як обчислюється оцінка
30/30Підтримка власника — у власності організації
0/20Верифікований домен
0/25Охоплення власника — 0 підписників у tensor-systems
6/25Послужний список — 4 публічних репозиторіїв, вік облікового запису ~0 р.
Використані вхідні дані
followers0
owner_typeOrganization
is_verified
owner_logintensor-systems
public_repos4
account_age_days171

Супровід пакетів

100Відмінний
Як обчислюється оцінка
25/25Опубліковано й доступно — 1 пакет(ів) у pypi
35/35Свіжість публікацій — остання публікація 0 дн. тому
20/20Історія версій — 28 опублікованих версій
20/20Не застарілий — активний, не deprecated і не yanked
Використані вхідні дані
packagesdroste
ecosystemspypi
any_deprecatedні
min_days_since_publish0

Інженерна якість

Чи наявні базові інженерні практики та документація?

67Помірний · 20% загального індексу
Як обчислюється оцінка
24/24Процеси CI — 2 процес(ів) CI
24/24Наявні тести
0/16Конфігурація лінтера
0/9.6Pre-commit-хуки
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 25 out of 25 merged PRs checked by a CI test -- score normalized to 10
Використані вхідні дані
has_ciтак
has_testsтак
has_editorconfigні
has_linter_configні
has_precommit_configні

Документація

65Помірний
Як обчислюється оцінка
30/30README
25/25Каталог документації
0/15Сайт документації / домашня сторінка
10/10Опис репозиторію
0/10Теми
0/10Wiki
Використані вхідні дані
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has_wikiні
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has_readmeтак
has_docs_dirтак
has_descriptionтак

Безпека

Чи міцні видимі практики безпеки й ланцюга постачання, без непослабленої пов’язаності з юрисдикціями високого ризику?

37У зоні ризику · 16% загального індексу

Стан безпеки

37У зоні ризику
Як обчислюється оцінка
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — немає даних
2.5/2.5CI-Tests — 25 out of 25 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/25 approved changesets -- score normalized to 0
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Ліцензія — license file detected
0/7.5Maintained — project was created within the last 90 days. Please review its contents carefully
0/5Packaging — немає даних
4.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
6/7.5Vulnerabilities — 2 existing vulnerabilities detected
Використані вхідні дані
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate3,7
Виключено з оцінювання (немає даних або не застосовно): branch_protection, packaging. Залишкові ваги перенормовано.

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.

58Помірний · 0% загального індексу
Як обчислюється оцінка
45/45Інструкції для агентів — AGENTS.md, CLAUDE.md
0/15Машиночитана документація (llms.txt)
40/40Читабельна історія комітів — намір зазначено у 81 з 100 людських комітів (структурований заголовок або пояснювальний текст)
Використані вхідні дані
has_llms_txtні
legible_history_share0,81
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes49 235
Як обчислюється оцінка
0/18Розгортання однією командою
22/22Автоматизовані тести
0/11Конфігурація лінтера / форматера
0/11Статична перевірка типів
10/10Відтворюване середовище — lockfile
4/10Підтверджена практика роботи з агентами — 2 з останніх 100 комітів створено агентом або з його зазначенням
0/8Автоматизоване супроводження — автоматичних оновлень залежностей не виявлено
9/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
Використані вхідні дані
has_nixні
has_testsтак
lockfilespackage-lock.json, uv.lock
has_dockerfileні
typed_languageні
bootstrap_files
has_devcontainerні
has_linter_configні
typecheck_configs
agent_commit_share0,02
toolchain_manifests
dependency_bot_commit_share0
Як обчислюється оцінка
0/45Типізований код — Python без конфігурації перевірки типів
54.4/55Керовані розміри файлів — 2/176 файлів вихідного коду понад 60 КБ
Використані вхідні дані
primary_languagePython
largest_source_bytes84 604
source_files_sampled176
oversized_source_files2
Як обчислюється оцінка
0/40Схема API (OpenAPI/GraphQL/proto)
0/20Сервер MCP
40/40Придатні до запуску приклади — examples
Використані вхідні дані
example_dirsexamples
has_mcp_signalні
api_schema_files

Ключові факти

1зірок GitHub
1контриб'юторів
242комітів за останні 12 місяців
0днів від останнього пушу
28релізів
1бас-фактор
12відкритих issue
PyPIпакетних екосистем

Попередження щодо збору даних

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • deps.dev does not index pypi:droste@0.20.0; advisories assessed against the repository dependency graph instead

Докладніше

OpenSSF Scorecard 3.7 / 10
3.7сукупно

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).Scorecard v5.5.0 · 2026-07-24 20:49 UTC

10Binary-Artifactsno binaries found in the repo
н/дBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests25 out of 25 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/25 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintainedproject was created within the last 90 days. Please review its contents carefully
н/дPackagingpackaging workflow not detected
9Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
8Vulnerabilities2 existing vulnerabilities detected
Усі залежності не зібрано

Не вдалося зібрати розв'язаний набір залежностей для цього звіту: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

Звіт у форматі JSON машиночитний
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          "author_login": "shanev",
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          "headline": "Require ModelRelay usage provenance (#192)",
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          "author_login": "shanev",
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          "is_bot": false,
          "headline": "Preserve explicit usage observation fidelity (#189)",
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          "author_login": "shanev",
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          "is_bot": false,
          "headline": "fix: preserve exact callback failure usage (#188)",
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          "author_login": "shanev",
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          "body": "* Window live root transcripts (closes #179)\n\n* Update prompt-pack distribution checks\n\n* Address transcript windowing review feedback",
          "is_bot": false,
          "headline": "Window historical state in live root transcripts (#185)",
          "author_name": "Shane Vitarana",
          "author_login": "shanev",
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          "headline": "feat(trace): preserve cache token usage aggregates (#186)",
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          "body": "* Settle inference budgets from exact token usage\n\nCloses #181\n\n* Preserve structured errors in fail-fast batches\n\n* Preserve partial provider usage counters\n\n* Require terminal Anthropic stream usage\n\n* Preserve native batch errors on structural failure",
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          "headline": "Settle inference budgets from exact token usage (#183)",
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          "body": "The main README should stay short and scannable; per-family caveats\n(BrowseComp-Plus's judge/generation cost split, LongBench-v2 CodeQA's\ncost-bounded sample, OOLONG-Pairs' 504 measurement limit, etc.) were\nalready fully covered in benchmarks/README.md, so the footnotes here\nwere pure duplication. Table numbers are unchanged.",
          "is_bot": false,
          "headline": "docs: move benchmark table footnotes to the benchmark guide (#177)",
          "author_name": "Shane Vitarana",
          "author_login": "shanev",
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          "body": "Percentage comparisons against the RLM paper's own reported numbers\naren't meaningful since the paper used older GPT-5 models, not the\nmodels droste uses. The comparison that matters is droste vs. direct\nmodel usage (same models, apples-to-apples), which stays unchanged.",
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          "is_bot": false,
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          "is_bot": false,
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          "is_bot": false,
          "headline": "benchmarks: publish live OOLONG 131K results as immutable artifacts (…",
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          "oid": "605caa9b8b985ce5fbea09c82d622102dcd86ebc",
          "body": "Adds three new GitHub-hosted ubuntu-latest jobs (test-linux, build-linux,\ndeno-linux) that mirror the existing self-hosted macOS ARM64 jobs step for\nstep, giving the project its first Linux signal since the macOS runner\ncutover. Existing jobs are untouched: same names, runners, and steps, so\nthe bra\n[…]\nlane remains\nthe sole authoritative required lane until the Linux lane demonstrates\nstability, per the policy comment added above the new jobs.\n\nCo-authored-by: Claude Sonnet 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "ci: add independent Linux CI lane on ubuntu-latest (#146) (#165)",
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          "oid": "df2dc386375da01965d1b1de4bac18fad98db02e",
          "body": "* docs: restructure README around hook → mechanism → use cases\n\nLead with the demo instead of the 'not an agent' disclaimer, merge that\ncontrast into 'How it works', add a 'When to reach for it' section with\nmechanism-grounded use cases, move the Trace ABI paragraph and runner\nprotocol details into \n[…]\n\ntransits' overstated the isolation; restore 'does not have to pass\nthrough'.\n\nCo-Authored-By: Claude Fable 5 <noreply@anthropic.com>\n\n---------\n\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "docs: restructure README around hook → mechanism → use cases (#164)",
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          "headline": "test(trace): add canonical execution fixture (#162)",
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          "body": "release: prepare 0.15.4",
          "is_bot": false,
          "headline": "Merge pull request #159 from tensor-systems/release/0.15.4",
          "author_name": "Shane Vitarana",
          "author_login": "shanev",
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          "body": "…rmance\n\ntest: add lifecycle conformance scenarios",
          "is_bot": false,
          "headline": "Merge pull request #158 from tensor-systems/codex/145-lifecycle-confo…",
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          "is_bot": false,
          "headline": "test: add lifecycle conformance scenarios",
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          "author_login": "shanev",
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        {
          "oid": "736cd4a5618e7aab552b3246a491e0b3723ad3ab",
          "body": "…sport\n\nRegister relay fd3 for external Deno launchers",
          "is_bot": false,
          "headline": "Merge pull request #157 from tensor-systems/codex/153-deno-event-tran…",
          "author_name": "Shane Vitarana",
          "author_login": "shanev",
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          "headline": "test: name relay launcher boundaries explicitly",
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          "headline": "fix: register externally inherited relay event fd",
          "author_name": "Shane Vitarana",
          "author_login": "shanev",
          "committed_at": "2026-07-15T23:11:09Z",
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        },
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          "oid": "0bcdc9454318887b656dfcde192269464f945dca",
          "body": "Give relay events a dedicated host descriptor",
          "is_bot": false,
          "headline": "Merge pull request #156 from tensor-systems/codex/153-dedicated-event-fd",
          "author_name": "Shane Vitarana",
          "author_login": "shanev",
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          "headline": "docs: align relay response boundaries",
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          "headline": "docs: make relay migration duties explicit",
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          "headline": "test: reuse canonical corpus in transport probe",
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          "headline": "fix: settle event write failures cleanly",
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          "headline": "fix: distinguish event input from transport failure",
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          "headline": "refactor: make relay startup metadata immutable",
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        },
        {
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          "headline": "test: bind relay lanes to released fixtures",
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          "headline": "test: exercise relay event lane faults",
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        },
        {
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          "headline": "fix: preserve empty preflight event lane",
          "author_name": "Shane Vitarana",
          "author_login": "shanev",
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          "headline": "fix: close event transport review findings",
          "author_name": "Shane Vitarana",
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          "headline": "fix: harden relay event channel failure",
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          "headline": "feat: dedicate relay event descriptor",
          "author_name": "Shane Vitarana",
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          "body": "Release Trace ABI v2 cross-runtime conformance corpus",
          "is_bot": false,
          "headline": "Merge pull request #155 from tensor-systems/release/144-event-abi-0.15.1",
          "author_name": "Shane Vitarana",
          "author_login": "shanev",
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          "headline": "feat(trace): ship cross-runtime conformance corpus (#144)",
          "author_name": "Shane Vitarana",
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          "body": "Release 0.15.0",
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          "headline": "Merge pull request #152 from tensor-systems/release/0.15.0",
          "author_name": "Shane Vitarana",
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                "key": "openssf_scorecard_ci_tests",
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                "key": "fuzzing",
                "name": "Fuzzing",
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            "components": [
              {
                "key": "api_schema_openapi_graphql_proto",
                "name": "API schema (OpenAPI/GraphQL/proto)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
                "name": "Runnable examples",
                "detail": "examples",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "examples"
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          }
        ],
        "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": [
    "Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token",
    "GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository",
    "deps.dev does not index pypi:droste@0.20.0; advisories assessed against the repository dependency graph instead"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-24T20:49:39.894071Z",
  "schema_version": "0.27.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/t/tensor-systems/droste.svg",
  "full_name": "tensor-systems/droste",
  "license_state": "standard",
  "license_spdx": "Apache-2.0"
}

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 статистикаPyPI.