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Software-GesundheitsberichtSchema 0.11.0 · Metriken 1.13.0 · 2026-07-17 08:49 UTC

PrimeIntellect-ai / prime

Official CLI and Python SDK for Prime Intellect - access GPU compute, remote sandboxes, RL environments, and distributed training infrastructure for AI development at scale.

PythonMIT★ 223 Sterne⑂ 49 Forksseit Dez. 2024Auf GitHub ansehen ↗

PrimeIntellect-ai/prime erreicht einen Gesundheitsindex von 72 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Vitality (95/100) ab, am schwächsten bei AI Readiness (46/100). Zuletzt heute aktualisiert. 2 Mitwirkende tragen den Großteil der jüngsten Arbeit.

72
gesamt / 100
Gut

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.

72
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.

Eigentümerschaft

Prime IntellectOrganisation
920 Follower59 öffentliche Reposseit Okt. 2023

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

Metriken nach Kategorie

Vitalität

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

95Exzellent · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 0 Tagen
34.6/36Commit-Rhythmus — 50/52 Wochen mit Commits
18/18Commit-Volumen — 579 Commits im letzten Jahr
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Verwendete Eingangsdaten
commits_last_year579
human_commit_share
days_since_last_push0
active_weeks_last_year50
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 100 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 0 Tagen
27/27Release-Rhythmus — ein Release etwa alle 6,4 Tage
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Verwendete Eingangsdaten
releases_count100
latest_release_tagv0.6.18
releases_from_tagsnein
days_since_latest_release0
mean_days_between_releases6,4

Community & Verbreitung

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

53Mittel · 18 % des Gesamtindex
Wie die Bewertung erfolgt
38.1/60Stars — 223 Stars
14/25Forks — 49 Forks
3.9/15Watcher — 6 Watcher
Verwendete Eingangsdaten
forks49
stars223
watchers6
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?

71Gut · 24 % des Gesamtindex
Wie die Bewertung erfolgt
25.2/54Bus-Faktor — 2 Beitragende decken die Hälfte aller Commits ab
13.2/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 41 % der Commits
13.5/13.5Breite der Beitragenden — 31 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor2
contributors_sampled31
top_contributor_share0,413
Wie die Bewertung erfolgt
38.7/46.8Issue-Lösungsquote — 83 % der Issues geschlossen
31/38.3PR-Annahme — 590/729 entschiedene PRs gemergt
13.5/15OpenSSF Scorecard: Code-Review — Found 27/30 approved changesets -- score normalized to 9
Verwendete Eingangsdaten
merged_prs590
open_issues5
closed_issues24
issue_closed_ratio0,828
closed_unmerged_prs139
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
21.3/25Reichweite des Inhabers — 920 Follower von PrimeIntellect-ai
18.5/25Kontohistorie — 59 öffentliche Repos, Kontoalter ca. 2 Jahre
Verwendete Eingangsdaten
followers920
owner_typeOrganization
is_verified
owner_loginPrimeIntellect-ai
public_repos59
account_age_days1.005

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

76Gut · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 6 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration
9.6/9.6Pre-Commit-Hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_configja
has_precommit_configja
Wie die Bewertung erfolgt
30/30README
0/25Dokumentationsverzeichnis
0/15Dokumentations-/Homepage-Site
10/10Repository-Beschreibung
0/10Topics
10/10Wiki
Verwendete Eingangsdaten
topics
has_wikija
homepage
has_readmeja
has_docs_dirnein
has_descriptionja

Sicherheit

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

57Mittel · 16 % des Gesamtindex
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
3.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 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
6.8/7.5Code-Review — Found 27/30 approved changesets -- score normalized to 9
2.5/2.5Contributors — project has 5 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Lizenz — license file detected
7.5/7.5Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
1/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 2
5/5SAST — SAST tool is run on all commits
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
6/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 75 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate5,7

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.

46Gefährdet · 0 % des Gesamtindex
Wie die Bewertung erfolgt
0/45Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln
0/15Maschinenlesbare Doku (llms.txt)
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtnein
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
0/18Bootstrap mit einem Befehl
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration
11/11Statische Typprüfung — packages/prime-evals/src/prime_evals/py.typed, packages/prime-sandboxes/src/prime_sandboxes/py.typed, packages/prime-tunnel/src/prime_tunnel/py.typed, packages/prime/src/prime_cli/py.typed
10/10Reproduzierbare Umgebung — Dockerfile, lockfile
0/10Belegte Agentenpraxis — keine Daten
0/8Automatisierte Wartung — keine Daten
2/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 2
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfilesuv.lock
has_dockerfileja
typed_languagenein
bootstrap_files
has_devcontainernein
has_linter_configja
typecheck_configspackages/prime-evals/src/prime_evals/py.typed, packages/prime-sandboxes/src/prime_sandboxes/py.typed, packages/prime-tunnel/src/prime_tunnel/py.typed, packages/prime/src/prime_cli/py.typed
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.
Wie die Bewertung erfolgt
27/45Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (packages/prime-evals/src/prime_evals/py.typed, packages/prime-sandboxes/src/prime_sandboxes/py.typed, packages/prime-tunnel/src/prime_tunnel/py.typed, packages/prime/src/prime_cli/py.typed)
52.5/55Handhabbare Dateigrößen — 10/219 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes275.849
source_files_sampled219
oversized_source_files10
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
0/20MCP-Server
40/40Lauffähige Beispiele — examples
Verwendete Eingangsdaten
example_dirsexamples
has_mcp_signalnein
api_schema_files

Eckdaten

223GitHub-Sterne
31Mitwirkende
579Commits, letzte 12 Monate
0Tage seit letztem Push
100Releases
2Bus-Faktor
5offene Issues
PyPIPaket-Ökosysteme

Weitere Details

OpenSSF Scorecard 5.7 / 10
5.7Gesamtwert

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).Scorecard v5.5.0 · 2026-07-17 08:48 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
9Code-ReviewFound 27/30 approved changesets -- score normalized to 9
10Contributorsproject has 5 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
2Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
8Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities75 existing vulnerabilities detected
Alle Abhängigkeiten 193

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 193 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
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PyPIidentify2.6.14indirekt
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PyPInest-asyncio1.6.0indirekt
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JSON-Rohbericht maschinenlesbar
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                "key": "issue_template",
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        "key": "governance",
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                "key": "bus_factor",
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                "key": "commit_distribution",
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                "detail": "top contributor authored 41% of commits",
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                "status": "partial",
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                "key": "openssf_scorecard_contributors",
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            "key": "responsiveness",
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            "notes": [],
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                "key": "issue_resolution",
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                "key": "pr_acceptance",
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              {
                "key": "openssf_scorecard_code_review",
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            "key": "stewardship",
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                "key": "owner_reach",
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                "key": "track_record",
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                "key": "tests_present",
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              {
                "key": "linter_config",
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                "key": "openssf_scorecard_ci_tests",
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            ]
          },
          {
            "key": "documentation",
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                "key": "wiki",
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        ],
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                "key": "contributors",
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              {
                "key": "fuzzing",
                "name": "Fuzzing",
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                "status": "missed",
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              {
                "key": "license",
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              },
              {
                "key": "maintained",
                "name": "Maintained",
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                "points": 7.5,
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                "details": [],
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              {
                "key": "packaging",
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                "points": 5,
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              {
                "key": "pinned_dependencies",
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                "key": "sast",
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                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file not detected",
                "points": 0,
                "status": "missed",
                "details": [],
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              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
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                "key": "token_permissions",
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                "status": "partial",
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              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
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                "status": "missed",
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          },
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            "key": "high_risk_jurisdiction_exposure",
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            "notes": [
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                "code": "jurisdiction_evidence_limits",
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            "value": 100,
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              "policy_countries": [
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                "Iran",
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              "review_only_matches": 0,
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            "components": [
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                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
                "detail": "no confirmed policy-scope location match",
                "points": 100,
                "status": "met",
                "details": [
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                "max_points": 100
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        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
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        "key": "ai_readiness",
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        "name": "AI Readiness",
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        "weight": 0,
        "metrics": [
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                "status": "missed",
                "details": [
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                ],
                "max_points": 45
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                "key": "machine_readable_docs_llms_txt",
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                "points": 0,
                "status": "missed",
                "details": [],
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              },
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            "key": "ai_verify_loop",
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            "notes": [
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              {
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            "value": 68,
            "inputs": {
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                "key": "demonstrated_agent_practice",
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                ],
                "max_points": 45
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                "status": "partial",
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          },
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            "notes": [],
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            "inputs": {
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                "points": 0,
                "status": "missed",
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              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
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              },
              {
                "key": "runnable_examples",
                "name": "Runnable examples",
                "detail": "examples",
                "points": 40,
                "status": "met",
                "details": [
                  {
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                    "params": {
                      "files": "examples"
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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": [],
  "report_type": "repository",
  "generated_at": "2026-07-17T08:49:01.018172Z",
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}

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 v0.11.0 — vollständige Methodik · Metriken-Wiki.

Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken.