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Software-GesundheitsberichtSchema 0.9.0 · Metriken 1.13.0 · 2026-07-14 07:58 UTC

primeintellect-ai / verifiers

Our library for RL environments + evals

PythonMIT★ 4.340 Sterne⑂ 588 Forksseit Jan. 2025Auf GitHub ansehen ↗

primeintellect-ai/verifiers erreicht einen Gesundheitsindex von 78 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Vitality (96/100) ab, am schwächsten bei Security (50/100). Zuletzt heute aktualisiert. 2 Mitwirkende tragen den Großteil der jüngsten Arbeit.

78
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.

78
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
906 Follower59 öffentliche Reposseit Okt. 2023

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

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlicht
PyPIverifiers0.2.0-203vor 3 Tagen

Metriken nach Kategorie

Vitalität

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

96Exzellent · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 0 Tagen
36/36Commit-Rhythmus — 52/52 Wochen mit Commits
18/18Commit-Volumen — 1.523 Commits im letzten Jahr
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 15 issue activity found in the last 90 days -- score normalized to 10
Verwendete Eingangsdaten
commits_last_year1.523
human_commit_share
days_since_last_push0
active_weeks_last_year52
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 51 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 3 Tagen
27/27Release-Rhythmus — ein Release etwa alle 9,3 Tage
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Verwendete Eingangsdaten
releases_count51
latest_release_tagv0.2.0
releases_from_tagsnein
days_since_latest_release3
mean_days_between_releases9,3

Community & Verbreitung

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

75Gut · 18 % des Gesamtindex
Wie die Bewertung erfolgt
59/60Stars — 4.340 Stars
23.1/25Forks — 588 Forks
8/15Watcher — 28 Watcher
Verwendete Eingangsdaten
forks588
stars4.340
watchers28
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
6.3/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingnein
has_issue_templatenein
has_code_of_conductnein
has_pull_request_templateja

Nachhaltigkeit & Governance

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

77Gut · 24 % des Gesamtindex
Wie die Bewertung erfolgt
25.2/54Bus-Faktor — 2 Beitragende decken die Hälfte aller Commits ab
11.8/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 47 % der Commits
13.5/13.5Breite der Beitragenden — 77 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 10 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor2
contributors_sampled77
top_contributor_share0,474
Wie die Bewertung erfolgt
44.2/46.8Issue-Lösungsquote — 95 % der Issues geschlossen
27.4/38.3PR-Annahme — 1.114/1.555 entschiedene PRs gemergt
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Verwendete Eingangsdaten
merged_prs1.114
open_issues16
closed_issues283
issue_closed_ratio0,946
closed_unmerged_prs441
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
21.3/25Reichweite des Inhabers — 906 Follower von PrimeIntellect-ai
18.4/25Kontohistorie — 59 öffentliche Repos, Kontoalter ca. 2 Jahre
Verwendete Eingangsdaten
followers906
owner_typeOrganization
is_verified
owner_loginPrimeIntellect-ai
public_repos59
account_age_days1.001

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 3 Tagen
20/20Versionshistorie — 203 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagesverifiers
ecosystemspypi
any_deprecatednein
min_days_since_publish3

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

82Gut · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 5 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration
9.6/9.6Pre-Commit-Hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 24 out of 24 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
25/25Dokumentationsverzeichnis
0/15Dokumentations-/Homepage-Site
10/10Repository-Beschreibung
0/10Topics
0/10Wiki
Verwendete Eingangsdaten
topics
has_wikinein
homepage
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

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

50Mittel · 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 — 24 out of 24 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
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 10 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 15 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
4/5SAST — SAST tool is not run on all commits -- score normalized to 8
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
0/7.5Vulnerabilities — 92 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate5

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.

64Mittel · 0 % des Gesamtindex
Wie die Bewertung erfolgt
45/45Agentenanweisungen — AGENTS.md, CLAUDE.md, assets/lab/AGENTS.md, assets/lab/CLAUDE.md, assets/lab/environments/AGENTS.md, environments/AGENTS.md, tests/AGENTS.md, verifiers/envs/AGENTS.md
0/15Maschinenlesbare Doku (llms.txt)
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share
agent_instruction_filesAGENTS.md, CLAUDE.md, assets/lab/AGENTS.md, assets/lab/CLAUDE.md, assets/lab/environments/AGENTS.md, environments/AGENTS.md, tests/AGENTS.md, verifiers/envs/AGENTS.md
agent_instruction_max_bytes7.557
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 — assets/templates/browserbase/cua/tsconfig.json
10/10Reproduzierbare Umgebung — Dockerfile, lockfile
0/10Belegte Agentenpraxis — keine Daten
0/8Automatisierte Wartung — keine Daten
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfilesuv.lock
has_dockerfileja
typed_languagenein
bootstrap_files
has_devcontainernein
has_linter_configja
typecheck_configsassets/templates/browserbase/cua/tsconfig.json
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 (assets/templates/browserbase/cua/tsconfig.json)
54.9/55Handhabbare Dateigrößen — 1/457 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes129.156
source_files_sampled457
oversized_source_files1
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
20/20MCP-Server
0/40Lauffähige Beispiele
Verwendete Eingangsdaten
example_dirs
has_mcp_signalja
api_schema_files

Eckdaten

4.340GitHub-Sterne
77Mitwirkende
1.523Commits, letzte 12 Monate
0Tage seit letztem Push
51Releases
2Bus-Faktor
16offene Issues
PyPIPaket-Ökosysteme

Weitere Details

OpenSSF Scorecard 5.0 / 10
5.0Gesamtwert

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 · 2026-07-14 07:57 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests24 out of 24 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 10 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 15 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
8SASTSAST tool is not run on all commits -- score normalized to 8
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
0Vulnerabilities92 existing vulnerabilities detected
Direkte Abhängigkeiten 26
RegistryPaketVersionsvorgabeManifest
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PyPIdatasets>=3.0.0, <4.7.0pyproject.toml
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PyPIopenai>=1.108.1pyproject.toml
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      }
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}

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