Öffentliches RegisterMittel
Software-GesundheitsberichtSchema 0.17.0 · Metriken 1.13.0 · 2026-07-21 04:14 UTC
deepinsight / insightface
State-of-the-art 2D and 3D Face Analysis Project
deepinsight/insightface erreicht einen Gesundheitsindex von 58 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Community & Adoption (79/100) ab, am schwächsten bei AI Readiness (39/100). Zuletzt vor 58 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.
58
gesamt / 100Software-Gesundheitsindex
Metriken werden auf einer Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr Mittel; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze 49 (Gefährdet). AI Readiness liegt außerhalb.
58
Exzellent85-100Vorbildlich; erfüllt im Wesentlichen alle geprüften Kriterien
Gut70-84Gesund; geringfügige Lücken
Mittel50-69Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Gefährdet30-49Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-29Schwerwiegende Probleme (aufgegeben, nur ein Maintainer, keine Hygiene)
Bewertungsprofil
Jede Achse ist eine Kategorie. Die Form zählt mehr als der Durchschnitt — ein gesundes Projekt füllt die gesamte Fläche, während ein Profil aus Spitzen und Kratern bedeutet, dass Stärke in einer Dimension Risiken in einer anderen verdeckt.
Eigentümerschaft
Deep InsightOrganisation
683 Follower12 öffentliche Reposseit Aug. 2016
Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.
Paket-Ökosysteme
| Registry | Paket | Version | Downloads / Monat | Versionen | Zuletzt veröffentlicht |
|---|---|---|---|---|---|
| PyPI | insightface | 1.0.1 | 1.257.753 | 30 | vor 58 Tagen |
Metriken nach Kategorie
Vitalität
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
46
Entwicklungsaktivität
50Mittel
Wie die Bewertung erfolgt
| 18/36 | Push-Aktualität — letzter Push vor 58 Tagen |
| 5.5/36 | Commit-Rhythmus — 8/52 Wochen mit Commits |
| 16.3/18 | Commit-Volumen — 65 Commits im letzten Jahr |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10 |
Verwendete Eingangsdaten
| commits_last_year | 65 |
| human_commit_share | — |
| days_since_last_push | 58 |
| active_weeks_last_year | 8 |
Release-Disziplin
40Gefährdet
Wie die Bewertung erfolgt
| 27/27 | Liefert Releases aus — 1 Releases veröffentlicht |
| 0/36 | Release-Aktualität — letztes Release vor 1.205 Tagen |
| 12.6/27 | Release-Rhythmus — Rhythmus unbekannt (nur ein Release) |
| 0/10 | OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases. |
Verwendete Eingangsdaten
| releases_count | 1 |
| latest_release_tag | v0.7 |
| releases_from_tags | nein |
| days_since_latest_release | 1.205 |
| mean_days_between_releases | — |
Community & Verbreitung
Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?
79
Popularität & Verbreitung
100Exzellent
Wie die Bewertung erfolgt
| 60/60 | Stars — 29.293 Stars |
| 25/25 | Forks — 6.063 Forks |
| 15/15 | Watcher — 523 Watcher |
Verwendete Eingangsdaten
| forks | 6.063 |
| stars | 29.293 |
| watchers | 523 |
| growth_state | organic |
| growth_factor_pct | 100 |
Community-Gesundheit
40Gefährdet
Wie die Bewertung erfolgt
| 22.5/22.5 | README |
| 0/22.5 | Lizenz — keine Lizenzdatei erkannt |
| 0/18 | CONTRIBUTING-Leitfaden |
| 13.5/13.5 | Verhaltenskodex |
| 0/7.2 | Issue-Vorlage |
| 0/6.3 | PR-Vorlage |
Verwendete Eingangsdaten
| has_readme | ja |
| has_license | nein |
| has_contributing | nein |
| has_issue_template | nein |
| has_code_of_conduct | ja |
| has_pull_request_template | nein |
Ökosystem-Verbreitung (Downloads)
100Exzellent
Wie die Bewertung erfolgt
| 80/80 | Downloads pro Monat — 1.257.753 Downloads/Monat über pypi |
| 0/20 | Abhängige in der Registry — von diesem Ökosystem nicht ausgewiesen |
Verwendete Eingangsdaten
| packages | insightface |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 1.257.753 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Abhängige in der Registry. Die verbleibenden Gewichte wurden renormalisiert.
Nachhaltigkeit & Governance
Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?
61
Maintainer-Resilienz (Bus-Faktor)
39Gefährdet
Wie die Bewertung erfolgt
| 9/54 | Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab |
| 6.2/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 72 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 60 Beitragende |
| 10/10 | OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations |
Verwendete Eingangsdaten
| bus_factor | 1 |
| contributors_sampled | 60 |
| top_contributor_share | 0,723 |
Reaktionsfähigkeit bei Issues & PRs
49Gefährdet
Wie die Bewertung erfolgt
| 25/46.8 | Issue-Lösungsquote — 53 % der Issues geschlossen |
| 24.2/38.3 | PR-Annahme — 109/172 entschiedene PRs gemergt |
| 0/15 | OpenSSF Scorecard: Code-Review — Found 0/2 approved changesets -- score normalized to 0 |
Verwendete Eingangsdaten
| merged_prs | 109 |
| open_issues | 1.223 |
| closed_issues | 1.399 |
| issue_closed_ratio | 0,534 |
| closed_unmerged_prs | 63 |
Wie die Bewertung erfolgt
| 30/30 | Organisatorische Trägerschaft — im Besitz einer Organisation |
| 0/20 | Verifizierte Domain |
| 20.4/25 | Reichweite des Inhabers — 683 Follower von deepinsight |
| 20.1/25 | Kontohistorie — 12 öffentliche Repos, Kontoalter ca. 9 Jahre |
Verwendete Eingangsdaten
| followers | 683 |
| owner_type | Organization |
| is_verified | — |
| owner_login | deepinsight |
| public_repos | 12 |
| account_age_days | 3.626 |
Paketpflege
100Exzellent
Wie die Bewertung erfolgt
| 25/25 | Veröffentlicht & auflösbar — 1 Paket(e) auf pypi |
| 35/35 | Veröffentlichungsaktualität — letzte Veröffentlichung vor 58 Tagen |
| 20/20 | Versionshistorie — 30 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
Verwendete Eingangsdaten
| packages | insightface |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 58 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
55
Engineering-Praktiken
48Gefährdet
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 1 Workflow(s) |
| 24/24 | Tests vorhanden |
| 0/16 | Linter-Konfiguration |
| 0/9.6 | Pre-Commit-Hooks |
| 0/6.4 | .editorconfig |
| 0/20 | OpenSSF Scorecard: CI-Tests — 0 out of 2 merged PRs checked by a CI test -- score normalized to 0 |
Verwendete Eingangsdaten
| has_ci | ja |
| has_tests | ja |
| has_editorconfig | nein |
| has_linter_config | nein |
| has_precommit_config | nein |
Dokumentation
65Mittel
Wie die Bewertung erfolgt
| 30/30 | README |
| 0/25 | Dokumentationsverzeichnis |
| 15/15 | Dokumentations-/Homepage-Site — https://insightface.ai |
| 10/10 | Repository-Beschreibung |
| 10/10 | Topics — 10 Topics |
| 0/10 | Wiki |
Verwendete Eingangsdaten
| topics | face-recognition, face-detection, mxnet, face-alignment, age-estimation, arcface, retinaface, pytorch, oneflow, paddlepaddle |
| has_wiki | nein |
| homepage | https://insightface.ai |
| has_readme | ja |
| has_docs_dir | nein |
| has_description | ja |
Sicherheit
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
50
Sicherheitslage
38Gefährdet
Wie die Bewertung erfolgt
| 6.8/7.5 | Binary-Artifacts — binaries present in source code |
| 0/7.5 | Branch-Protection — branch protection not enabled on development/release branches |
| 0/2.5 | CI-Tests — 0 out of 2 merged PRs checked by a CI test -- score normalized to 0 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 0/7.5 | Code-Review — Found 0/2 approved changesets -- score normalized to 0 |
| 2.5/2.5 | Contributors — project has 5 contributing companies or organizations |
| 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 |
| 0/2.5 | Lizenz — license file not detected |
| 7.5/7.5 | Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10 |
| 0/5 | Packaging — keine Daten |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 0/5 | SAST — SAST tool is not run on all commits -- score normalized to 0 |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — Project has not signed or included provenance with any releases. |
| 7.5/7.5 | Token-Permissions — GitHub workflow tokens follow principle of least privilege |
| 3.8/7.5 | Vulnerabilities — 5 existing vulnerabilities detected |
Verwendete Eingangsdaten
| source | openssf_scorecard |
| checks_evaluated | 17 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 1 |
| scorecard_aggregate | 3,8 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): packaging. Die verbleibenden Gewichte wurden renormalisiert.
Abhängigkeits-Advisories
100Exzellent
Wie die Bewertung erfolgt
| 35/35 | Direkte Abhängigkeiten ohne bekannte Advisories — keine direkte Abhängigkeit trägt ein bekanntes Advisory |
| 25/25 | Indirekte Abhängigkeiten ohne bekannte Advisories — keine indirekte Abhängigkeit trägt ein bekanntes Advisory |
| 0/40 | Keine offenen Advisories — kein Advisory trägt ein Veröffentlichungsdatum |
Verwendete Eingangsdaten
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 21 |
| unassessed_packages | 0 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Keine offenen Advisories. Die verbleibenden Gewichte wurden renormalisiert. Abgeglichen wurde die Laufzeit-Abhängigkeitshülle von pypi:insightface@1.0.1 — das, was die Installation des veröffentlichten Pakets nach sich zieht — mit 21 Paketen. Erreichbarkeit wird nicht analysiert.
AI Readiness
Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Ein unabhängiges, experimentelles Badge — Gewicht 0,0, es wird eigenständig ausgewiesen und verändert den Gesamt-Gesundheitswert nicht.
39
AI-Agentenkontext & Leitlinien
1Kritisch
Wie die Bewertung erfolgt
| 0/45 | Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln |
| 0/15 | Maschinenlesbare Doku (llms.txt) |
| 0/40 | Lesbare Commit-Historie — keine Daten |
Verwendete Eingangsdaten
| has_llms_txt | nein |
| legible_history_share | — |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lesbare Commit-Historie. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
| 18/18 | Bootstrap mit einem Befehl — detection/retinaface/Makefile |
| 22/22 | Automatisierte Tests |
| 0/11 | Lint-/Format-Konfiguration |
| 0/11 | Statische Typprüfung |
| 10/10 | Reproduzierbare Umgebung — Dockerfile |
| 0/10 | Belegte Agentenpraxis — keine Daten |
| 0/8 | Automatisierte Wartung — keine Daten |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Verwendete Eingangsdaten
| has_nix | nein |
| has_tests | ja |
| lockfiles | — |
| has_dockerfile | ja |
| typed_language | nein |
| bootstrap_files | detection/retinaface/Makefile |
| has_devcontainer | nein |
| has_linter_config | nein |
| typecheck_configs | — |
| agent_commit_share | — |
| toolchain_manifests | — |
| dependency_bot_commit_share | — |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Belegte Agentenpraxis, Automatisierte Wartung. Die verbleibenden Gewichte wurden renormalisiert.
AI-Code-Lesbarkeit für Modelle
54Mittel
Wie die Bewertung erfolgt
| 0/45 | Typprüfbarer Code — Python ohne Typprüfungs-Konfiguration |
| 54.5/55 | Handhabbare Dateigrößen — 11/1.205 Quelldateien über 60 KB |
Verwendete Eingangsdaten
| primary_language | Python |
| largest_source_bytes | 804.116 |
| source_files_sampled | 1.205 |
| oversized_source_files | 11 |
Maschinenlesbare AI-Schnittstellen
40Gefährdet
Wie die Bewertung erfolgt
| 0/40 | API-Schema (OpenAPI/GraphQL/proto) |
| 0/20 | MCP-Server |
| 40/40 | Lauffähige Beispiele — example, examples, notebooks, sample |
Verwendete Eingangsdaten
| example_dirs | example, examples, notebooks, sample |
| has_mcp_signal | nein |
| api_schema_files | — |
Eckdaten
29.293GitHub-Sterne
60Mitwirkende
65Commits, letzte 12 Monate
58Tage seit letztem Push
1Releases
1Bus-Faktor
1.223offene Issues
PyPIPaket-Ökosysteme
Weitere Details
Stern- und Fork-Verlauf 29.293 ★ / 0 ⇿
29.293Sterne
Wann jeder Stern und Fork hinzugefügt wurde, von GitHub erfasst und nach Tagen gruppiert. Das kumulierte Wachstum steht direkt über den täglichen Zugängen, aus denen es besteht, sodass beide gegeneinander lesbar sind: stetiger organischer Zuwachs sieht ganz anders aus als ein abrupter, kurzlebiger Ausschlag. Wo dieser Unterschied messbar ist, wird er als Wachstumsauthentizität ausgewiesen.
Es wird nur die jüngste Historie angezeigt — dieses Repository überschreitet das Erfassungsfenster, sodass die früheste Historie nicht erfasst wird.
OpenSSF Scorecard 3.8 / 10
3.8Gesamtwert
Unabhängige, werkzeugneutrale Sicherheitsbewertung durch das quelloffene OpenSSF Scorecard. Jede Prüfung honoriert eine Sicherheits-Praxis, nicht das Werkzeug eines bestimmten Anbieters. Prüfungen, die Scorecard nicht ermitteln konnte, sind mit k. A. markiert und vom Sicherheitswert ausgeschlossen (nie als null gezählt).
| 9 | Binary-Artifacts | binaries present in source code |
| 0 | Branch-Protection | branch protection not enabled on development/release branches |
| 0 | CI-Tests | 0 out of 2 merged PRs checked by a CI test -- score normalized to 0 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 0 | Code-Review | Found 0/2 approved changesets -- score normalized to 0 |
| 10 | Contributors | project has 5 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 0 | Dependency-Update-Tool | no update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 0 | License | license file not detected |
| 10 | Maintained | 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10 |
| k. A. | Packaging | packaging workflow not detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 0 | Security-Policy | security policy file not detected |
| 0 | Signed-Releases | Project has not signed or included provenance with any releases. |
| 10 | Token-Permissions | GitHub workflow tokens follow principle of least privilege |
| 5 | Vulnerabilities | 5 existing vulnerabilities detected |
Alle Abhängigkeiten 53
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 53 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|---|---|---|
| PyPI | albumentations | — | indirekt |
| PyPI | argparse | — | indirekt |
| PyPI | asynctest | — | indirekt |
| PyPI | autotorch | — | indirekt |
| PyPI | cityscapesscripts | — | indirekt |
| PyPI | cmake | — | indirekt |
| PyPI | codecov | — | indirekt |
| PyPI | cython | — | indirekt |
| PyPI | easydict | — | indirekt |
| PyPI | easydict | 1.9 | indirekt |
| PyPI | filelock | — | indirekt |
| PyPI | flake8 | — | indirekt |
| PyPI | gputil | — | indirekt |
| PyPI | horovod | — | indirekt |
| PyPI | imagecorruptions | — | indirekt |
| PyPI | interrogate | — | indirekt |
| PyPI | isort | 4.3.21 | indirekt |
| PyPI | kwarray | — | indirekt |
| PyPI | loguru | — | indirekt |
| PyPI | matplotlib | — | indirekt |
| PyPI | mmcv | — | indirekt |
| PyPI | mmlvis | — | indirekt |
| PyPI | mmpycocotools | — | indirekt |
| PyPI | modelscope | — | indirekt |
| PyPI | mxboard | 0.1.0 | indirekt |
| PyPI | numpy | — | indirekt |
| PyPI | onnx | — | indirekt |
| PyPI | onnxruntime | — | indirekt |
| PyPI | opencv-python | — | indirekt |
| PyPI | opencv-python | 4.2.0.34 | indirekt |
| PyPI | pillow | — | indirekt |
| PyPI | plotly | — | indirekt |
| PyPI | pyhocon | — | indirekt |
| PyPI | pytest | — | indirekt |
| PyPI | recommonmark | — | indirekt |
| PyPI | requests | — | indirekt |
| PyPI | scikit-image | — | indirekt |
| PyPI | scikit-learn | — | indirekt |
| PyPI | scipy | — | indirekt |
| PyPI | six | — | indirekt |
| PyPI | sklearn | — | indirekt |
| PyPI | sphinx | — | indirekt |
| PyPI | sphinx-markdown-tables | — | indirekt |
| PyPI | sphinx-rtd-theme | — | indirekt |
| PyPI | terminaltables | — | indirekt |
| PyPI | torch | — | indirekt |
| PyPI | torchvision | — | indirekt |
| PyPI | tqdm | — | indirekt |
| PyPI | tqdm | 4.48.2 | indirekt |
| PyPI | ubelt | — | indirekt |
| PyPI | vtk | — | indirekt |
| PyPI | xdoctest | — | indirekt |
| PyPI | yapf | — | indirekt |
Abhängigkeits-Advisories 0
Die Installation von pypi:insightface@1.0.1 zieht 21 Pakete nach sich, direkt und transitiv: 0 tragen bekannte Advisories, davon 0 direkte Abhängigkeiten.
Keine bekannten Advisories betreffen die bewerteten Abhängigkeiten.
Ein Advisory bedeutet, dass die im Abhängigkeitsgraphen erfasste Version in den betroffenen Bereich eines Advisories fällt. Erreichbarkeit wird nicht analysiert, und der Graph enthält Entwicklungs- und Test-Pins — ein Fund kann das Werkzeug betreffen und nicht die ausgelieferte Software.
JSON-Rohbericht maschinenlesbar
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"data": {
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"face-recognition",
"face-detection",
"mxnet",
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"age-estimation",
"arcface",
"retinaface",
"pytorch",
"oneflow",
"paddlepaddle"
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"is_fork": false,
"size_kb": 60523,
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},
"ecosystem": {
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"is_deprecated": false,
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"repository_url": "https://github.com/deepinsight/insightface",
"versions_count": 30,
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"dependents_count": null,
"deprecation_note": null,
"maintainers_count": null,
"monthly_downloads": 1257753,
"first_published_at": "2019-08-29T10:20:51.719350Z",
"latest_published_at": "2026-05-23T06:43:00.404106Z",
"latest_version_yanked": null,
"days_since_latest_publish": 58
}
]
},
"popularity": {
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"watchers": 523,
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},
{
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],
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},
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}
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"code": "no_indirect_advisories",
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],
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{
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},
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{
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}
],
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}
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]
}
],
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}
],
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"status": "missed",
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},
{
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]
},
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},
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],
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],
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"has_linter_config": false,
"typecheck_configs": [],
"agent_commit_share": null,
"toolchain_manifests": [],
"dependency_bot_commit_share": null
},
"components": [
{
"key": "one_command_bootstrap",
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"status": "met",
"details": [
{
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}
],
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},
{
"key": "automated_tests",
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"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
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"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
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"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "reproducible_environment",
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"detail": "Dockerfile",
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"details": [
{
"code": "file_list",
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"files": "Dockerfile"
}
}
],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
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"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
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"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 8
},
{
"key": "openssf_scorecard_pinned_dependencies",
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"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
}
]
},
{
"key": "ai_code_legibility",
"band": "moderate",
"name": "Code legibility for models",
"note": null,
"notes": [],
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"inputs": {
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"source_files_sampled": 1205,
"oversized_source_files": 11
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"components": [
{
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"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
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"language": "Python"
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}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
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"points": 54.5,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
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"oversized": 11
}
}
],
"max_points": 55
}
]
},
{
"key": "ai_interfaces",
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"inputs": {
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"api_schema_files": []
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{
"key": "api_schema_openapi_graphql_proto",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "mcp_server",
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"points": 0,
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"details": [],
"max_points": 20
},
{
"key": "runnable_examples",
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"code": "file_list",
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"files": "example, examples, notebooks, sample"
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}
],
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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": [],
"report_type": "repository",
"generated_at": "2026-07-21T04:14:18.935656Z",
"schema_version": "0.17.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/d/deepinsight/insightface.svg",
"full_name": "deepinsight/insightface",
"license_state": "absent",
"license_spdx": null
}Bewertungen sind Signale, keine Garantien. Sie spiegeln öffentlich sichtbare Praxis auf GitHub wider — kein Code-Audit und keine Sicherheitsgarantie.
Fehlende Daten werden ausgeschlossen und die Gewichte neu normiert, nie als null bewertet. Die Methodik ist versioniert und offen: Metriken v1.13.0, Schema v0.17.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken — PyPI.