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Software-GesundheitsberichtSchema 0.12.0 · Metriken 1.13.0 · 2026-07-18 14:05 UTC

zarr-developers / zarr-python

An implementation of chunked, compressed, N-dimensional arrays for Python.

PythonMIT★ 2.021 Sterne⑂ 429 Forksseit Dez. 2015Auf GitHub ansehen ↗

zarr-developers/zarr-python erreicht einen Gesundheitsindex von 86 von 100 und liegt damit im Bereich Exzellent. Am stärksten schneidet es bei Vitality (99/100) ab, am schwächsten bei AI Readiness (49/100). Zuletzt vor 1 Tag aktualisiert. 3 Mitwirkende tragen den Großteil der jüngsten Arbeit.

86
gesamt / 100
Exzellent

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.

86
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

Zarr DevelopersOrganisation
219 Follower44 öffentliche Reposseit Jan. 2018

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

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlichtTags
PyPIzarr3.2.1-116vor 74 Tagenpythoncompressedndimensional-arrayszarr

Metriken nach Kategorie

Vitalität

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

99Exzellent · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 1 Tagen
33.9/36Commit-Rhythmus — 49/52 Wochen mit Commits
18/18Commit-Volumen — 366 Commits im letzten Jahr
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
Verwendete Eingangsdaten
commits_last_year366
human_commit_share
days_since_last_push1
active_weeks_last_year49

Release-Disziplin

100Exzellent
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 100 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 74 Tagen
27/27Release-Rhythmus — ein Release etwa alle 32,7 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count100
latest_release_tagv3.2.1
releases_from_tagsnein
days_since_latest_release74
mean_days_between_releases32,7
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?

88Exzellent · 18 % des Gesamtindex
Wie die Bewertung erfolgt
53.6/60Stars — 2.021 Stars
21.9/25Forks — 429 Forks
8.8/15Watcher — 40 Watcher
Verwendete Eingangsdaten
forks429
stars2.021
watchers40
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (MIT)
18/18CONTRIBUTING-Leitfaden
13.5/13.5Verhaltenskodex
0/7.2Issue-Vorlage
6.3/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
has_issue_templatenein
has_code_of_conductja
has_pull_request_templateja

Nachhaltigkeit & Governance

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

78Gut · 24 % des Gesamtindex
Wie die Bewertung erfolgt
36/54Bus-Faktor — 3 Beitragende decken die Hälfte aller Commits ab
14.9/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 34 % der Commits
13.5/13.5Breite der Beitragenden — 100 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 139 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor3
contributors_sampled100
top_contributor_share0,337
Wie die Bewertung erfolgt
34.7/46.8Issue-Lösungsquote — 74 % der Issues geschlossen
30.2/38.3PR-Annahme — 1.844/2.339 entschiedene PRs gemergt
9/15OpenSSF Scorecard: Code-Review — Found 15/24 approved changesets -- score normalized to 6
Verwendete Eingangsdaten
merged_prs1.844
open_issues390
closed_issues1.123
issue_closed_ratio0,742
closed_unmerged_prs495
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
16.8/25Reichweite des Inhabers — 219 Follower von zarr-developers
24/25Kontohistorie — 44 öffentliche Repos, Kontoalter ca. 8 Jahre
Verwendete Eingangsdaten
followers219
owner_typeOrganization
is_verified
owner_loginzarr-developers
public_repos44
account_age_days3.118

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 74 Tagen
20/20Versionshistorie — 116 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packageszarr
ecosystemspypi
any_deprecatednein
min_days_since_publish74

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

92Exzellent · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 16 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

Dokumentation

90Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://zarr.readthedocs.io
10/10Repository-Beschreibung
10/10Topics — 4 Topics
0/10Wiki
Verwendete Eingangsdaten
topicszarr, ndimensional-arrays, compressed, python
has_wikinein
homepagehttps://zarr.readthedocs.io
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

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

70Gut · 16 % des Gesamtindex
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — keine Daten
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
4.5/7.5Code-Review — Found 15/24 approved changesets -- score normalized to 6
2.5/2.5Contributors — project has 139 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Lizenz — license file detected
7.5/7.5Maintained — 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
4.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
1.5/5SAST — SAST tool is not run on all commits -- score normalized to 3
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — keine Daten
6.8/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0.8/7.5Vulnerabilities — 9 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate7
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection, 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? Ein unabhängiges, experimentelles Badge — Gewicht 0,0, es wird eigenständig ausgewiesen und verändert den Gesamt-Gesundheitswert nicht.

49Gefährdet · 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/zarr-metadata/src/zarr_metadata/py.typed, src/zarr/py.typed
10/10Reproduzierbare Umgebung — lockfile
0/10Belegte Agentenpraxis — keine Daten
5/8Automatisierte Wartung — Abhängigkeits-Automatisierung konfiguriert, in den erfassten Commits nicht beobachtet
9/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfilesuv.lock
has_dockerfilenein
typed_languagenein
bootstrap_files
has_devcontainernein
has_linter_configja
typecheck_configspackages/zarr-metadata/src/zarr_metadata/py.typed, src/zarr/py.typed
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Belegte Agentenpraxis. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
27/45Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (packages/zarr-metadata/src/zarr_metadata/py.typed, src/zarr/py.typed)
53.7/55Handhabbare Dateigrößen — 8/341 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes213.376
source_files_sampled341
oversized_source_files8
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

2.021GitHub-Sterne
100Mitwirkende
366Commits, letzte 12 Monate
1Tage seit letztem Push
100Releases
3Bus-Faktor
390offene Issues
PyPIPaket-Ökosysteme

Weitere Details

OpenSSF Scorecard 7.0 / 10
7.0Gesamtwert

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 · 2026-07-18 14:04 UTC

10Binary-Artifactsno binaries found in the repo
k. A.Branch-Protectioninternal 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
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
6Code-ReviewFound 15/24 approved changesets -- score normalized to 6
10Contributorsproject has 139 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
9Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
3SASTSAST tool is not run on all commits -- score normalized to 3
0Security-Policysecurity policy file not detected
k. A.Signed-Releasesno releases found
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
1Vulnerabilities9 existing vulnerabilities detected
Direkte Abhängigkeiten 6
RegistryPaketVersionsvorgabeManifest
PyPIpackaging>=22.0pyproject.toml
PyPInumpy>=2pyproject.toml
PyPInumcodecs>=0.14pyproject.toml
PyPIgoogle-crc32c>=1.5pyproject.toml
PyPItyping_extensions>=4.14pyproject.toml
PyPIdonfig>=0.8pyproject.toml
Alle Abhängigkeiten 206

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 14 direkte und 192 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
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PyPIpackagingdirekt
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JSON-Rohbericht maschinenlesbar
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                "key": "openssf_scorecard_contributors",
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            "key": "responsiveness",
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            "components": [
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                "key": "issue_resolution",
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                "key": "pr_acceptance",
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            "inputs": {
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                "key": "ownership_backing",
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              {
                "key": "owner_reach",
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                "key": "track_record",
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        ],
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        ],
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                "key": "code_review",
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                "key": "contributors",
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                "key": "dangerous_workflow",
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              },
              {
                "key": "dependency_update_tool",
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                "key": "fuzzing",
                "name": "Fuzzing",
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              {
                "key": "license",
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              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10",
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              {
                "key": "packaging",
                "name": "Packaging",
                "detail": "packaging workflow detected",
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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": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "no releases found",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 6.8,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "9 existing vulnerabilities detected",
                "points": 0.8,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
            "band": "excellent",
            "name": "High-Risk Jurisdiction Exposure",
            "note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
                "params": {}
              }
            ],
            "value": 100,
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              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
              ],
              "review_only_matches": 0,
              "assessed_self_published_locations": 7
            },
            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
                "detail": "no confirmed policy-scope location match",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "jurisdiction_no_match",
                    "params": {}
                  }
                ],
                "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",
        "band": "at_risk",
        "name": "AI Readiness",
        "value": 49,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "critical",
            "name": "Agent context & guidance",
            "note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "legible_commit_history"
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                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 1,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": null,
              "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": [
                  {
                    "code": "no_agent_instructions",
                    "params": {}
                  }
                ],
                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
              {
                "key": "legible_commit_history",
                "name": "Legible commit history",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "good",
            "name": "Verify loop (build / test / typecheck)",
            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "demonstrated_agent_practice"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 76,
            "inputs": {
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              "has_tests": true,
              "lockfiles": [
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              "typed_language": false,
              "bootstrap_files": [],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
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              ],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
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                "detail": null,
                "points": 0,
                "status": "missed",
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                "max_points": 18
              },
              {
                "key": "automated_tests",
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                "points": 22,
                "status": "met",
                "details": [],
                "max_points": 22
              },
              {
                "key": "lint_format_config",
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                "detail": null,
                "points": 11,
                "status": "met",
                "details": [],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
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                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
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                  }
                ],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
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                "detail": "lockfile",
                "points": 10,
                "status": "met",
                "details": [
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                    "code": "file_list",
                    "params": {
                      "files": "lockfile"
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "dependency automation configured, none observed in the sampled commits",
                "points": 5,
                "status": "partial",
                "details": [
                  {
                    "code": "dependency_bot_config_only",
                    "params": {}
                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 9",
                "points": 9,
                "status": "partial",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "good",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 81,
            "inputs": {
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              "largest_source_bytes": 213376,
              "source_files_sampled": 341,
              "oversized_source_files": 8
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (packages/zarr-metadata/src/zarr_metadata/py.typed, src/zarr/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "packages/zarr-metadata/src/zarr_metadata/py.typed, src/zarr/py.typed",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "8/341 source files over 60KB",
                "points": 53.7,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 341,
                      "oversized": 8
                    }
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                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "at_risk",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "example_dirs": [
                "examples"
              ],
              "has_mcp_signal": false,
              "api_schema_files": []
            },
            "components": [
              {
                "key": "api_schema_openapi_graphql_proto",
                "name": "API schema (OpenAPI/GraphQL/proto)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
                "name": "Runnable examples",
                "detail": "examples",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "examples"
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          }
        ],
        "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": "2026-07-18T14:05:21.532298Z",
  "schema_version": "0.12.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/z/zarr-developers/zarr-python.svg",
  "full_name": "zarr-developers/zarr-python",
  "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 v0.12.0 — vollständige Methodik · Metriken-Wiki.

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