Öffentliches RegisterGut
Software-GesundheitsberichtSchema 0.27.0 · Metriken 2.1.0 · 2026-08-01 00:13 UTC
Azure-Player / azure.datafactory.tools
Tools for deploying Data Factory (v2) in Microsoft Azure
Azure-Player/azure.datafactory.tools erreicht einen Gesundheitsindex von 73 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Engineering Quality (78/100) ab, am schwächsten bei AI Readiness (19/100). Zuletzt vor 23 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.
73
gesamt / 100Software-Gesundheitsindex
Metriken werden auf einer standardisierten Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr gewichtetes Mittel, kalibriert auf die Verteilung des öffentlichen Registers, sodass die Stufen Perzentilbedeutung tragen; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze Gefährdet von 34.
73
Außergewöhnlich93-100Die Spitzengruppe des Registers (≈ obere 5 %); erfüllt im Wesentlichen alle geprüften Kriterien
Exzellent80-92Durchgehend stark; geringfügige Lücken
Gut65-79Gesund; Lücken sind begrenzt und beherrschbar
Mittel50-64Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Schwach35-49Wesentliche Schwächen in mehreren Bereichen
Gefährdet20-34Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-19Schwerwiegende 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.
Der gewichtete Gesamtwert 64 wird auf der veröffentlichten Indexskala auf 73 kalibriert (Register-Kalibrierung 2026-08-02).
Eigentümerschaft
AzurePlayerOrganisation
58 Follower22 öffentliche Reposseit Aug. 2017
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?
74
Entwicklungsaktivität
62Mittel
Wie die Bewertung erfolgt
| 28.8/36 | Push-Aktualität — letzter Push vor 23 Tagen |
| 6.2/36 | Commit-Rhythmus — 9/52 Wochen mit Commits |
| 16.6/18 | Commit-Volumen — 70 Commits im letzten Jahr |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10 |
Verwendete Eingangsdaten
| commits_last_year | 70 |
| human_commit_share | 1 |
| days_since_last_push | 23 |
| active_weeks_last_year | 9 |
Release-Disziplin
92Exzellent
Wie die Bewertung erfolgt
| 27/27 | Liefert Releases aus — 49 Releases veröffentlicht |
| 36/36 | Release-Aktualität — letztes Release vor 23 Tagen |
| 19.8/27 | Release-Rhythmus — ein Release etwa alle 68,6 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — keine Daten |
Verwendete Eingangsdaten
| releases_count | 49 |
| latest_release_tag | v1.18.0 |
| releases_from_tags | nein |
| days_since_latest_release | 23 |
| mean_days_between_releases | 68,6 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: Signed-Releases. Die verbleibenden Gewichte wurden renormalisiert.
Community & Verbreitung
Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?
63
Popularität & Verbreitung
61Mittel
Wie die Bewertung erfolgt
| 39.1/60 | Stars — 259 Stars |
| 15.9/25 | Forks — 82 Forks |
| 6/15 | Watcher — 13 Watcher |
Verwendete Eingangsdaten
| forks | 82 |
| stars | 259 |
| watchers | 13 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community-Gesundheit
65Gut
Wie die Bewertung erfolgt
| 22.5/22.5 | README |
| 22.5/22.5 | Lizenz — anerkannte Lizenz (MIT) |
| 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 | ja |
| readme_badges | — |
| has_contributing | nein |
| has_issue_template | nein |
| has_code_of_conduct | ja |
| readme_badge_services | — |
| has_pull_request_template | nein |
Nachhaltigkeit & Governance
Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?
57
Maintainer-Resilienz (Bus-Faktor)
34Gefährdet
Wie die Bewertung erfolgt
| 9/54 | Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab |
| 1.4/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 94 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 16 Beitragende |
| 10/10 | OpenSSF Scorecard: Contributors — project has 4 contributing companies or organizations |
Verwendete Eingangsdaten
| bus_factor | 1 |
| contributors_sampled | 16 |
| top_contributor_share | 0,937 |
Wie die Bewertung erfolgt
| 39.3/42 | Issue-Lösungsquote — 94 % der Issues geschlossen |
| 27.7/30 | PR-Annahme — 119/129 entschiedene PRs gemergt |
| 0/13 | Newcomer PR acceptance — kein PR eines Erstbeitragenden in 30 Tagen entschieden |
| 0/15 | OpenSSF Scorecard: Code-Review — Found 0/8 approved changesets -- score normalized to 0 |
Verwendete Eingangsdaten
| merged_prs | 119 |
| open_issues | 17 |
| closed_issues | 244 |
| prs_merged_7d | — |
| prs_decided_7d | — |
| prs_merged_30d | — |
| prs_decided_30d | — |
| issue_closed_ratio | 0,935 |
| closed_unmerged_prs | 10 |
| first_time_authors_30d | — |
| first_time_prs_merged_30d | — |
| first_time_prs_decided_30d | — |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): newcomer_pr_acceptance. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
| 30/30 | Organisatorische Trägerschaft — im Besitz einer Organisation |
| 0/20 | Verifizierte Domain |
| 12.7/25 | Reichweite des Inhabers — 58 Follower von Azure-Player |
| 21.9/25 | Kontohistorie — 22 öffentliche Repos, Kontoalter ca. 8 Jahre |
Verwendete Eingangsdaten
| followers | 58 |
| owner_type | Organization |
| is_verified | — |
| owner_login | Azure-Player |
| public_repos | 22 |
| account_age_days | 3.275 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
78
Engineering-Praktiken
64Mittel
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 3 Workflow(s) |
| 24/24 | Tests vorhanden |
| 0/16 | Linter-Konfiguration |
| 0/9.6 | Pre-Commit-Hooks |
| 0/6.4 | .editorconfig |
| 16/20 | OpenSSF Scorecard: CI-Tests — 7 out of 8 merged PRs checked by a CI test -- score normalized to 8 |
Verwendete Eingangsdaten
| has_ci | ja |
| has_tests | ja |
| has_editorconfig | nein |
| has_linter_config | nein |
| has_precommit_config | nein |
Dokumentation
100Außergewöhnlich
Wie die Bewertung erfolgt
| 30/30 | README |
| 25/25 | Dokumentationsverzeichnis |
| 15/15 | Dokumentations-/Homepage-Site — https://azureplayer.net/adftools |
| 10/10 | Repository-Beschreibung |
| 10/10 | Topics — 10 Topics |
| 10/10 | Wiki |
Verwendete Eingangsdaten
| topics | azure-data-factory, adftools, publish, data-factory, ci-cd, cicd, deploy, deployment, devops, powershell-module |
| has_wiki | ja |
| homepage | https://azureplayer.net/adftools |
| has_readme | ja |
| has_docs_dir | ja |
| has_description | ja |
Sicherheit
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
54
Sicherheitslage
54Mittel
Wie die Bewertung erfolgt
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — keine Daten |
| 2/2.5 | CI-Tests — 7 out of 8 merged PRs checked by a CI test -- score normalized to 8 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 0/7.5 | Code-Review — Found 0/8 approved changesets -- score normalized to 0 |
| 2.5/2.5 | Contributors — project has 4 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 |
| 2.5/2.5 | Lizenz — license file detected |
| 7.5/7.5 | Maintained — 30 commit(s) and 8 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 — keine Daten |
| 6.8/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Verwendete Eingangsdaten
| source | openssf_scorecard |
| checks_evaluated | 15 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 3 |
| scorecard_aggregate | 5,4 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection, packaging, signed_releases. Die verbleibenden Gewichte wurden renormalisiert.
AI Readiness
Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Trägt ein bewusst kleines Gewicht (4 %): Agenten-Tooling ist ein echtes Pflegesignal, doch ein Repository ohne jedes Signal kann weiterhin 100/100 erreichen.
19
AI-Agentenkontext & Leitlinien
24Gefährdet
Wie die Bewertung erfolgt
| 0/45 | Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln |
| 0/15 | Maschinenlesbare Doku (llms.txt) |
| 24/40 | Lesbare Commit-Historie — 45 von 100 menschlichen Commits benennen ihre Absicht (strukturierter Betreff oder erläuternder Text) |
Verwendete Eingangsdaten
| has_llms_txt | nein |
| legible_history_share | 0,45 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
AI-Verify-Loop (Build / Test / Typprüfung)
22Gefährdet
Wie die Bewertung erfolgt
| 0/18 | Bootstrap mit einem Befehl |
| 22/22 | Automatisierte Tests |
| 0/11 | Lint-/Format-Konfiguration |
| 0/11 | Statische Typprüfung |
| 0/10 | Reproduzierbare Umgebung |
| 0/10 | Belegte Agentenpraxis — keine von Agenten verfassten Commits unter den letzten 100 |
| 0/8 | Automatisierte Wartung — keine automatisierten Abhängigkeits-Updates beobachtet |
| 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 | nein |
| typed_language | nein |
| bootstrap_files | — |
| has_devcontainer | nein |
| has_linter_config | nein |
| typecheck_configs | — |
| agent_commit_share | 0 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
AI-Code-Lesbarkeit für Modelle
1Kritisch
Wie die Bewertung erfolgt
| 0/45 | Typprüfbarer Code — PowerShell ohne Typprüfungs-Konfiguration |
| 0/55 | Handhabbare Dateigrößen — keine Quelldateien erkannt |
Verwendete Eingangsdaten
| primary_language | PowerShell |
| largest_source_bytes | — |
| source_files_sampled | 0 |
| oversized_source_files | 0 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Handhabbare Dateigrößen. Die verbleibenden Gewichte wurden renormalisiert.
Eckdaten
259GitHub-Sterne
16Mitwirkende
70Commits, letzte 12 Monate
23Tage seit letztem Push
49Releases
1Bus-Faktor
17offene Issues
—Paket-Ökosysteme
Warnungen zur Datenerhebung
- Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
Weitere Details
Stern- und Fork-Verlauf 0 ★ / 82 ⇿
0Sterne
82Forks
46Releases
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.
Major 0Minor 7Patch 8
Jeder Punkt umfasst 6 Tage.
OpenSSF Scorecard 5.4 / 10
5.4Gesamtwert
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).
| 10 | Binary-Artifacts | no binaries found in the repo |
| k. A. | Branch-Protection | internal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md |
| 8 | CI-Tests | 7 out of 8 merged PRs checked by a CI test -- score normalized to 8 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 0 | Code-Review | Found 0/8 approved changesets -- score normalized to 0 |
| 10 | Contributors | project has 4 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 |
| 10 | License | license file detected |
| 10 | Maintained | 30 commit(s) and 8 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 |
| k. A. | Signed-Releases | no releases found |
| 9 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
Alle Abhängigkeiten 0
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 0 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|
Abhängigkeits-Advisories nicht bewertet
Der Advisory-Abgleich konnte für diesen Bericht nicht ausgeführt werden: No resolved dependencies to assess
JSON-Rohbericht maschinenlesbar
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"kind": "other",
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"kind": "other",
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},
{
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"kind": "other",
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"kind": "other",
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"kind": "other",
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{
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{
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{
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{
"key": "issue_template",
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{
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],
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},
{
"key": "governance",
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"value": 57,
"weight": 0.23,
"metrics": [
{
"key": "maintainer_resilience",
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],
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{
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{
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],
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{
"key": "openssf_scorecard_contributors",
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}
]
},
{
"key": "responsiveness",
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"notes": [
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"params": {
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},
{
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"closed_issues": 244,
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},
"components": [
{
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{
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}
],
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},
{
"key": "pr_acceptance",
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"detail": "119/129 decided PRs merged",
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"details": [
{
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}
],
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},
{
"key": "newcomer_pr_acceptance",
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{
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}
]
},
{
"key": "stewardship",
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"note": null,
"notes": [],
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"inputs": {
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"owner_type": "Organization",
"is_verified": null,
"owner_login": "Azure-Player",
"public_repos": 22,
"account_age_days": 3275
},
"components": [
{
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{
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}
],
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{
"key": "verified_domain",
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"points": 0,
"status": "missed",
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},
{
"key": "owner_reach",
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"points": 12.7,
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{
"code": "owner_followers",
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},
{
"key": "track_record",
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"status": "partial",
"details": [
{
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},
{
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}
],
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},
{
"key": "engineering",
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"name": "Engineering Quality",
"value": 78,
"weight": 0.19,
"metrics": [
{
"key": "engineering_practices",
"band": "moderate",
"name": "Engineering practices",
"note": null,
"notes": [],
"value": 64,
"inputs": {
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"details": [
{
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}
],
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},
{
"key": "tests_present",
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"points": 24,
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{
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{
"key": "pre_commit_hooks",
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{
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"details": [],
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{
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}
]
},
{
"key": "documentation",
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"name": "Documentation",
"note": null,
"notes": [],
"value": 100,
"inputs": {
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"adftools",
"publish",
"data-factory",
"ci-cd",
"cicd",
"deploy",
"deployment",
"devops",
"powershell-module"
],
"has_wiki": true,
"homepage": "https://azureplayer.net/adftools",
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{
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{
"key": "documentation_directory",
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"points": 25,
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},
{
"key": "documentation_homepage_site",
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"points": 15,
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},
{
"key": "repository_description",
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"points": 10,
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},
{
"key": "topics",
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"points": 10,
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}
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{
"key": "wiki",
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"points": 10,
"status": "met",
"details": [],
"max_points": 10
}
]
}
],
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},
{
"key": "security",
"band": "moderate",
"name": "Security",
"value": 54,
"weight": 0.16,
"metrics": [
{
"key": "security_posture",
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"name": "Security posture",
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"notes": [
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{
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],
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"scorecard_version": "v5.5.0",
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},
"components": [
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},
{
"key": "branch_protection",
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{
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},
{
"key": "cii_best_practices",
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"points": 0,
"status": "missed",
"details": [],
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{
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"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "contributors",
"name": "Contributors",
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"points": 2.5,
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},
{
"key": "dangerous_workflow",
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"points": 10,
"status": "met",
"details": [],
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},
{
"key": "dependency_update_tool",
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"points": 0,
"status": "missed",
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},
{
"key": "fuzzing",
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"detail": "project is not fuzzed",
"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "license",
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"points": 2.5,
"status": "met",
"details": [],
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},
{
"key": "maintained",
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},
{
"key": "packaging",
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"details": [
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"max_points": 5
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{
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},
{
"key": "sast",
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{
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},
{
"key": "signed_releases",
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{
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"status": "partial",
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{
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}
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},
{
"key": "high_risk_jurisdiction_exposure",
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"notes": [
{
"code": "jurisdiction_evidence_limits",
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],
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"components": [
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{
"code": "jurisdiction_no_match",
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],
"max_points": 100
}
]
}
],
"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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"name": "AI Readiness",
"value": 19,
"weight": 0.04,
"metrics": [
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"key": "ai_agent_context",
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"name": "Agent context & guidance",
"note": null,
"notes": [],
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"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
"key": "agent_instructions",
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"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
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"params": {}
}
],
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},
{
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{
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{
"code": "legible_history",
"params": {
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"sampled": 100
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}
],
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},
{
"key": "ai_verify_loop",
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"name": "Verify loop (build / test / typecheck)",
"note": null,
"notes": [],
"value": 22,
"inputs": {
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"lockfiles": [],
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"toolchain_manifests": [],
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},
"components": [
{
"key": "one_command_bootstrap",
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"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "automated_tests",
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"points": 22,
"status": "met",
"details": [],
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},
{
"key": "lint_format_config",
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"points": 0,
"status": "missed",
"details": [],
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{
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
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{
"key": "reproducible_environment",
"name": "Reproducible environment",
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"points": 0,
"status": "missed",
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{
"key": "demonstrated_agent_practice",
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{
"key": "automated_maintenance",
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"status": "missed",
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{
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{
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{
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],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight: agent tooling is a real maintenance signal, but its absence must never gate the top of the scale (calibration saturates at raw 91, so 100/100 remains reachable with AI Readiness at zero)."
}
],
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},
"warnings": [
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],
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"generated_at": "2026-08-01T00:13:07.952252Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/a/Azure-Player/azure.datafactory.tools.svg",
"full_name": "Azure-Player/azure.datafactory.tools",
"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 v2.1.0, Schema v0.27.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken.