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Software-GesundheitsberichtSchema 0.27.0 · Metriken 1.13.0 · 2026-07-27 17:08 UTC

xang1234 / stock-screener

Stock scanner with multiple fundamental and technical criteria. Features 80+ filters, AI chatbot (Groq/DeepSeek/Gemini), theme discovery, and StockBee-style breadth indicators.

Python · JavaScriptApache-2.0★ 255 Sterne⑂ 84 Forksseit Jan. 2026Auf GitHub ansehen ↗

xang1234/stock-screener erreicht einen Gesundheitsindex von 64 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Vitality (87/100) ab, am schwächsten bei Security (25/100). Zuletzt heute aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.

64
gesamt / 100
Mittel

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.

64
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

D TPersönliches Konto
60 Follower37 öffentliche Reposseit Okt. 2016

Dieses Repository gehört einem persönlichen Konto. Ein Projekt mit nur einem Eigentümer trägt ein höheres Kontinuitätsrisiko als ein organisationsgetragenes.

Metriken nach Kategorie

Vitalität

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

87Exzellent · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 0 Tagen
15.9/36Commit-Rhythmus — 23/52 Wochen mit Commits
18/18Commit-Volumen — 2.025 Commits im letzten Jahr
0/10OpenSSF Scorecard: Maintained — keine Daten
Verwendete Eingangsdaten
commits_last_year2.025
human_commit_share1
days_since_last_push0
active_weeks_last_year23

Release-Disziplin

100Exzellent
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 12 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 14 Tagen
27/27Release-Rhythmus — ein Release etwa alle 9,2 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count12
latest_release_tagv1.4.0
releases_from_tagsnein
days_since_latest_release14
mean_days_between_releases9,2

Community & Verbreitung

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

64Mittel · 18 % des Gesamtindex
Wie die Bewertung erfolgt
39/60Stars — 255 Stars
16/25Forks — 84 Forks
2.7/15Watcher — 4 Watcher
Verwendete Eingangsdaten
forks84
stars255
watchers4
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (Apache-2.0)
18/18CONTRIBUTING-Leitfaden
0/13.5Verhaltenskodex
0/7.2Issue-Vorlage
0/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
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?

52Mittel · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
1.4/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 94 % der Commits
4.1/13.5Breite der Beitragenden — 3 Beitragende
0/10OpenSSF Scorecard: Contributors — keine Daten
Verwendete Eingangsdaten
bus_factor1
contributors_sampled3
top_contributor_share0,94
Wie die Bewertung erfolgt
37.7/46.8Issue-Lösungsquote — 81 % der Issues geschlossen
37.2/38.3PR-Annahme — 275/283 entschiedene PRs gemergt
0/15OpenSSF Scorecard: Code-Review — keine Daten
Verwendete Eingangsdaten
merged_prs275
open_issues7
closed_issues29
issue_closed_ratio0,806
closed_unmerged_prs8
Wie die Bewertung erfolgt
10/30Organisatorische Trägerschaft — persönliches (Nutzer-)Konto
0/20Verifizierte Domain — für Nutzerkonten nicht anwendbar
12.8/25Reichweite des Inhabers — 60 Follower von xang1234
23.5/25Kontohistorie — 37 öffentliche Repos, Kontoalter ca. 9 Jahre
Verwendete Eingangsdaten
followers60
owner_typeUser
is_verified
owner_loginxang1234
public_repos37
account_age_days3.582
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Verifizierte Domain. Die verbleibenden Gewichte wurden renormalisiert.

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

84Gut · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 6 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration — eslint.config.js
0/9.6Pre-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_confignein

Dokumentation

90Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://xang1234.github.io/stock-screener/
10/10Repository-Beschreibung
10/10Topics — 11 Topics
0/10Wiki
Verwendete Eingangsdaten
topicscanslim, market-breadth, minervini, stock-analysis, stock-screener, trading, finance, investment, trading-automation, nasdaq-stocks, nyse-stocks
has_wikinein
homepagehttps://xang1234.github.io/stock-screener/
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

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

25Kritisch · 16 % des Gesamtindex

Sicherheitslage

25Kritisch
Wie die Bewertung erfolgt
0/30Sicherheitsrichtlinie (SECURITY.md)
0/25Dependabot-Konfiguration
25/25Lockfiles für Abhängigkeiten — package-lock.json
0/20CodeQL-Workflow
Verwendete Eingangsdaten
sourcefile_signals
lockfilespackage-lock.json
manifestsbackend/requirements-runtime.txt, backend/requirements-server.txt, backend/requirements-test.txt, backend/requirements-theme-ml.txt, backend/requirements.txt, frontend/package.json
has_codeql_workflownein
has_security_policynein
has_dependabot_confignein

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
0/15Maschinenlesbare Doku (llms.txt)
40/40Lesbare Commit-Historie — 85 von 100 menschlichen Commits benennen ihre Absicht (strukturierter Betreff oder erläuternder Text)
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share0,85
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes12.734
Wie die Bewertung erfolgt
18/18Bootstrap mit einem Befehl — Makefile
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration — eslint.config.js
0/11Statische Typprüfung
10/10Reproduzierbare Umgebung — Dockerfile, lockfile
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
lockfilespackage-lock.json
has_dockerfileja
typed_languagenein
bootstrap_filesMakefile
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
54.2/55Handhabbare Dateigrößen — 19/1.365 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes124.092
source_files_sampled1.365
oversized_source_files19
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

255GitHub-Sterne
3Mitwirkende
2.025Commits, letzte 12 Monate
0Tage seit letztem Push
12Releases
1Bus-Faktor
7offene Issues
npm, PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • 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
  • OpenSSF Scorecard did not return a usable result (2026/07/27 17:07:18 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 ★ / 84 ⇿
0Sterne
84Forks
12Releases

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.

02040608010084132026-022026-052026-07
Major 1Minor 4Patch 2
Direkte Abhängigkeiten 18
RegistryPaketVersionsvorgabeManifest
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Alle Abhängigkeiten nicht erhoben

Der aufgelöste Abhängigkeitssatz konnte für diesen Bericht nicht erhoben werden: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

JSON-Rohbericht maschinenlesbar
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                "key": "codeql_workflow",
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                "points": 0,
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                "details": [],
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              }
            ]
          },
          {
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            "notes": [
              {
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                "params": {}
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              "policy_countries": [
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                "Iran",
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              "review_only_matches": 0,
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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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        "weight": 0,
        "metrics": [
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                "details": [],
                "max_points": 15
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          {
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            "band": "moderate",
            "name": "Verify loop (build / test / typecheck)",
            "note": null,
            "notes": [],
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            "inputs": {
              "has_nix": false,
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              "typed_language": false,
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              {
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                "status": "met",
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              {
                "key": "static_type_checking",
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                "points": 0,
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                "details": [],
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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",
                "details": [
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              {
                "key": "automated_maintenance",
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                "detail": "no automated dependency updates observed",
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                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "OpenSSF Scorecard unavailable",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
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                ],
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            "key": "ai_code_legibility",
            "band": "moderate",
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            "notes": [],
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              "source_files_sampled": 1365,
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              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python without a type-check config",
                "points": 0,
                "status": "missed",
                "details": [
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                    "code": "no_typecheck_config_language",
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                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "19/1365 source files over 60KB",
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          },
          {
            "key": "ai_interfaces",
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              "has_mcp_signal": true,
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              {
                "key": "mcp_server",
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              {
                "key": "runnable_examples",
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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",
    "GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository",
    "OpenSSF Scorecard did not return a usable result (2026/07/27 17:07:18 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": "2026-07-27T17:08:22.888047Z",
  "schema_version": "0.27.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/x/xang1234/stock-screener.svg",
  "full_name": "xang1234/stock-screener",
  "license_state": "standard",
  "license_spdx": "Apache-2.0"
}

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.

Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken.