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Software-GesundheitsberichtSchema 0.27.0 · Metriken 1.13.0 · 2026-07-27 20:58 UTC

octo-models / octo

Octo is a transformer-based robot policy trained on a diverse mix of 800k robot trajectories.

PythonMIT★ 1.721 Sterne⑂ 274 Forksseit Dez. 2023Auf GitHub ansehen ↗

octo-models/octo erreicht einen Gesundheitsindex von 31 von 100 und liegt damit im Bereich Gefährdet. Am stärksten schneidet es bei Engineering Quality (91/100) ab, am schwächsten bei Vitality (18/100). Zuletzt vor 726 Tagen aktualisiert. 2 Mitwirkende tragen den Großteil der jüngsten Arbeit.

31
gesamt / 100
Gefährdet

Software-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.

31
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)
VitalitätCommunity &VerbreitungNachhaltigkeit &GovernanceEngineering-QualitätSicherheitAI Readiness

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.

Abandonment Policy applies a 60% multiplier to weighted overall health and gives it a ceiling of 49.

Eigentümerschaft

octo-modelsOrganisation
30 Follower2 öffentliche Reposseit Dez. 2023

Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlicht
PyPIoctoverweist auf ein anderes Repo — nicht bewertet0.3.01956vor 4793 Tagen

Metriken nach Kategorie

Vitalität

Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?

18Kritisch · 22 % des Gesamtindex
Wie die Bewertung erfolgt
0/36Push-Aktualität — letzter Push vor 726 Tagen
0/36Commit-Rhythmus — 0/52 Wochen mit Commits
0/18Commit-Volumen — 0 Commits im letzten Jahr
0/10OpenSSF Scorecard: Maintained — keine Daten
Verwendete Eingangsdaten
commits_last_year0
human_commit_share1
days_since_last_push726
active_weeks_last_year0

Release-Disziplin

44Gefährdet
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 2 Releases veröffentlicht
0/36Release-Aktualität — letztes Release vor 794 Tagen
12.6/27Release-Rhythmus — ein Release etwa alle 157,3 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count2
latest_release_tagv1.5
releases_from_tagsnein
days_since_latest_release794
mean_days_between_releases157,3

Community & Verbreitung

Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?

66Mittel · 18 % des Gesamtindex
Wie die Bewertung erfolgt
52.5/60Stars — 1.721 Stars
20.3/25Forks — 274 Forks
7/15Watcher — 19 Watcher
Verwendete Eingangsdaten
forks274
stars1.721
watchers19
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (MIT)
0/18CONTRIBUTING-Leitfaden
0/13.5Verhaltenskodex
0/7.2Issue-Vorlage
0/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingnein
has_issue_templatenein
has_code_of_conductnein
has_pull_request_templatenein

Nachhaltigkeit & Governance

Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?

56Mittel · 24 % des Gesamtindex
Wie die Bewertung erfolgt
25.2/54Bus-Faktor — 2 Beitragende decken die Hälfte aller Commits ab
16.6/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 26 % der Commits
13.5/13.5Breite der Beitragenden — 13 Beitragende
0/10OpenSSF Scorecard: Contributors — keine Daten
Verwendete Eingangsdaten
bus_factor2
contributors_sampled13
top_contributor_share0,262
Wie die Bewertung erfolgt
16/46.8Issue-Lösungsquote — 34 % der Issues geschlossen
32.1/38.3PR-Annahme — 26/31 entschiedene PRs gemergt
0/15OpenSSF Scorecard: Code-Review — keine Daten
Verwendete Eingangsdaten
merged_prs26
open_issues88
closed_issues46
issue_closed_ratio0,343
closed_unmerged_prs5
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
10.7/25Reichweite des Inhabers — 30 Follower von octo-models
8.7/25Kontohistorie — 2 öffentliche Repos, Kontoalter ca. 2 Jahre
Verwendete Eingangsdaten
followers30
owner_typeOrganization
is_verified
owner_loginocto-models
public_repos2
account_age_days957

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

91Exzellent · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 1 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration — .flake8
9.6/9.6Pre-Commit-Hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — keine Daten
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_configja
has_precommit_configja

Dokumentation

90Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://octo-models.github.io/
10/10Repository-Beschreibung
0/10Topics
10/10Wiki
Verwendete Eingangsdaten
topics
has_wikija
homepagehttps://octo-models.github.io/
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?

21Kritisch · 16 % des Gesamtindex
Wie die Bewertung erfolgt
0/30Sicherheitsrichtlinie (SECURITY.md)
0/25Dependabot-Konfiguration
0/25Lockfiles für Abhängigkeiten
0/20CodeQL-Workflow
Verwendete Eingangsdaten
sourcefile_signals
lockfiles
manifestspyproject.toml, requirements.txt, setup.py
has_codeql_workflownein
has_security_policynein
has_dependabot_confignein
Wie die Bewertung erfolgt
35/35Direkte Abhängigkeiten ohne bekannte Advisories — keine direkte Abhängigkeit trägt ein bekanntes Advisory
0/25Indirekte Abhängigkeiten ohne bekannte Advisories — transitive Menge in diesem Bereich nicht von Entwicklungs- und Test-Abhängigkeiten trennbar
0/40Keine offenen Advisories — kein Advisory trägt ein Veröffentlichungsdatum
Verwendete Eingangsdaten
sourceosv
advisories0
affected_packages0
assessed_packages12
unassessed_packages14
affected_by_severitynone
direct_affected_packages0
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Indirekte Abhängigkeiten ohne bekannte Advisories, Keine offenen Advisories. Die verbleibenden Gewichte wurden renormalisiert. 12 aufgelöste Abhängigkeiten wurden mit OSV abgeglichen. 14 konnten nicht bewertet werden — keine aufgelöste Version, ein nicht unterstütztes Ökosystem oder außerhalb der ausgewiesenen Paketliste. Dieses Repository veröffentlicht kein Paket, das der Index auflöst; bewertet wurde daher der Abhängigkeitsgraph des Repositorys. Dieser Graph vermischt Entwicklungs- und Test-Pins mit ausgelieferten Abhängigkeiten, daher werden nur die deklarierten Laufzeit-Abhängigkeiten bewertet; transitive Befunde werden als Kontext ausgewiesen und fließen nicht in die Bewertung ein. 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.

34Gefährdet · 0 % des Gesamtindex
Wie die Bewertung erfolgt
0/45Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln
0/15Maschinenlesbare Doku (llms.txt)
14.9/40Lesbare Commit-Historie — 28 von 100 menschlichen Commits benennen ihre Absicht (strukturierter Betreff oder erläuternder Text)
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share0,28
agent_instruction_files
agent_instruction_max_bytes
Wie die Bewertung erfolgt
0/18Bootstrap mit einem Befehl
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration — .flake8
0/11Statische Typprüfung
0/10Reproduzierbare Umgebung
0/10Belegte Agentenpraxis — keine von Agenten verfassten Commits unter den letzten 100
0/8Automatisierte Wartung — keine automatisierten Abhängigkeits-Updates beobachtet
0/10OpenSSF Scorecard: Pinned-Dependencies — keine Daten
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfiles
has_dockerfilenein
typed_languagenein
bootstrap_files
has_devcontainernein
has_linter_configja
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
Wie die Bewertung erfolgt
0/45Typprüfbarer Code — Python ohne Typprüfungs-Konfiguration
55/55Handhabbare Dateigrößen — 0/48 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes36.209
source_files_sampled48
oversized_source_files0
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
0/20MCP-Server
40/40Lauffähige Beispiele — examples, notebooks
Verwendete Eingangsdaten
example_dirsexamples, notebooks
has_mcp_signalnein
api_schema_files

Eckdaten

1.721GitHub-Sterne
13Mitwirkende
0Commits, letzte 12 Monate
726Tage seit letztem Push
2Releases
2Bus-Faktor
88offene Issues
PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi package 'octo' points at a different repository (http://octo.zoni.nl); excluded from ecosystem scoring
  • OpenSSF Scorecard did not return a usable result (2026/07/27 20:58:10 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

Weitere Details

Stern- und Fork-Verlauf 0 ★ / 274 ⇿
0Sterne
274Forks
2Releases

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.

05010015020025030026382023-122025-042026-07
Major 0Minor 1Patch 0

Jeder Punkt umfasst 3 Tage.

Alle Abhängigkeiten 26

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 26 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPIabsl-pyindirekt
PyPIchex0.1.85indirekt
PyPIdistrax0.1.5indirekt
PyPIeinopsindirekt
PyPIflax0.7.5indirekt
PyPIgymindirekt
PyPIimageioindirekt
PyPIjax0.4.20indirekt
PyPImatplotlibindirekt
PyPIml-collectionsindirekt
PyPIml-dtypes0.2.0indirekt
PyPImoviepyindirekt
PyPInumpy1.24.3indirekt
PyPIoptax0.1.5indirekt
PyPIplotlyindirekt
PyPIpre-commit3.3.3indirekt
PyPIscipyindirekt
PyPItensorflow2.15.0indirekt
PyPItensorflow-datasets4.9.2indirekt
PyPItensorflow-graphics2021.12.3indirekt
PyPItensorflow-hubindirekt
PyPItensorflow-probability0.23.0indirekt
PyPItensorflow-textindirekt
PyPItqdmindirekt
PyPItransformersindirekt
PyPIwandbindirekt
Abhängigkeits-Advisories 0

Dieses Repository veröffentlicht kein vom Index auflösbares Paket, daher wurde sein eigener Abhängigkeitsgraph bewertet – 12 Pakete, darunter auch Entwicklungs- und Test-Pins, die nie ausgeliefert werden: 0 tragen bekannte Advisories, davon 0 direkte. 14 konnten nicht bewertet werden – keine aufgelöste Version, ein nicht unterstütztes Ökosystem, oder außerhalb der ausgewiesenen Paketliste.

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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              {
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              "packages": [],
              "red_flag": false,
              "assessed_packages": 12,
              "malicious_packages": 0,
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                "max_points": 100
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          },
          {
            "key": "high_risk_jurisdiction_exposure",
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          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
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                "max_points": 40
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            "notes": [],
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            "inputs": {
              "has_nix": false,
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              "agent_commit_share": 0,
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              "dependency_bot_commit_share": 0
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            "components": [
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                "key": "one_command_bootstrap",
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                "max_points": 11
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                "key": "static_type_checking",
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                "points": 0,
                "status": "missed",
                "details": [],
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              {
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                "details": [],
                "max_points": 10
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                "key": "demonstrated_agent_practice",
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                "detail": "no agent-authored commits among the last 100",
                "points": 0,
                "status": "missed",
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                "key": "automated_maintenance",
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                "detail": "no automated dependency updates observed",
                "points": 0,
                "status": "missed",
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                "max_points": 8
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                "detail": "OpenSSF Scorecard unavailable",
                "points": 0,
                "status": "excluded",
                "details": [
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                "max_points": 10
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          },
          {
            "key": "ai_code_legibility",
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            "name": "Code legibility for models",
            "note": null,
            "notes": [],
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              "oversized_source_files": 0
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              {
                "key": "type_checkable_code",
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                "detail": "Python without a type-check config",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_typecheck_config_language",
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                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
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                "detail": "0/48 source files over 60KB",
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                "details": [
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                "max_points": 55
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          },
          {
            "key": "ai_interfaces",
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                "key": "api_schema_openapi_graphql_proto",
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                "key": "mcp_server",
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                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
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              {
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                    "code": "file_list",
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                "max_points": 40
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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": [
    "Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token",
    "pypi package 'octo' points at a different repository (http://octo.zoni.nl); excluded from ecosystem scoring",
    "OpenSSF Scorecard did not return a usable result (2026/07/27 20:58:10 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-27T20:58:34.910620Z",
  "schema_version": "0.27.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/o/octo-models/octo.svg",
  "full_name": "octo-models/octo",
  "license_state": "standard",
  "license_spdx": "MIT"
}

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 v0.27.0 — vollständige Methodik · Metriken-Wiki.

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