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Software-GesundheitsberichtSchema 0.14.0 · Metriken 1.13.0 · 2026-07-19 01:06 UTC

computational-cell-analytics / micro-sam

Segment Anything for Microscopy

Jupyter Notebook · PythonMIT★ 701 Sterne⑂ 105 Forksseit Mai 2023Auf GitHub ansehen ↗

computational-cell-analytics/micro-sam erreicht einen Gesundheitsindex von 71 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Vitality (92/100) ab, am schwächsten bei AI Readiness (25/100). Zuletzt vor 1 Tag aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.

71
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.

71
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

86 Follower36 öffentliche Reposseit Juni 2022

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

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlicht
PyPImicro_sam1.8.6-7vor 1 Tag

Metriken nach Kategorie

Vitalität

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

92Exzellent · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 1 Tagen
22.8/36Commit-Rhythmus — 33/52 Wochen mit Commits
18/18Commit-Volumen — 157 Commits im letzten Jahr
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 21 issue activity found in the last 90 days -- score normalized to 10
Verwendete Eingangsdaten
commits_last_year157
human_commit_share
days_since_last_push1
active_weeks_last_year33

Release-Disziplin

100Exzellent
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 48 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 1 Tagen
27/27Release-Rhythmus — ein Release etwa alle 15,5 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count48
latest_release_tagv1.8.6
releases_from_tagsnein
days_since_latest_release1
mean_days_between_releases15,5
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?

60Mittel · 18 % des Gesamtindex
Wie die Bewertung erfolgt
46.2/60Stars — 701 Stars
16.8/25Forks — 105 Forks
5/15Watcher — 9 Watcher
Verwendete Eingangsdaten
forks105
stars701
watchers9
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?

69Mittel · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
9.1/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 60 % der Commits
13.5/13.5Breite der Beitragenden — 20 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor1
contributors_sampled20
top_contributor_share0,597
Wie die Bewertung erfolgt
40.5/46.8Issue-Lösungsquote — 87 % der Issues geschlossen
35.5/38.3PR-Annahme — 827/892 entschiedene PRs gemergt
6/15OpenSSF Scorecard: Code-Review — Found 13/27 approved changesets -- score normalized to 4
Verwendete Eingangsdaten
merged_prs827
open_issues52
closed_issues336
issue_closed_ratio0,866
closed_unmerged_prs65
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
13.9/25Reichweite des Inhabers — 86 Follower von computational-cell-analytics
19.7/25Kontohistorie — 36 öffentliche Repos, Kontoalter ca. 4 Jahre
Verwendete Eingangsdaten
followers86
owner_typeOrganization
is_verified
owner_logincomputational-cell-analytics
public_repos36
account_age_days1.508

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 1 Tagen
20/20Versionshistorie — 7 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagesmicro_sam
ecosystemspypi
any_deprecatednein
min_days_since_publish1

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

77Gut · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 6 Workflow(s)
24/24Tests vorhanden
0/16Linter-Konfiguration
0/9.6Pre-Commit-Hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 27 out of 27 merged PRs checked by a CI test -- score normalized to 10
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_confignein
has_precommit_confignein

Dokumentation

90Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://computational-cell-analytics.github.io/micro-sam/
10/10Repository-Beschreibung
10/10Topics — 9 Topics
0/10Wiki
Verwendete Eingangsdaten
topicsmicroscopy-images, segment-anything, segmentation, cell-segmentation, napari, nuclei-segmentation, mitochondria-segmentation, micro-sam, bioimage-analysis
has_wikinein
homepagehttps://computational-cell-analytics.github.io/micro-sam/
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

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

53Mittel · 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 — 27 out of 27 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
3/7.5Code-Review — Found 13/27 approved changesets -- score normalized to 4
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 21 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
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — keine Daten
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5,3
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.

25Kritisch · 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
0/11Lint-/Format-Konfiguration
0/11Statische Typprüfung
0/10Reproduzierbare Umgebung
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
lockfiles
has_dockerfilenein
typed_languagenein
bootstrap_files
has_devcontainernein
has_linter_confignein
typecheck_configs
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
0/45Typprüfbarer Code — Jupyter Notebook ohne Typprüfungs-Konfiguration
54.3/55Handhabbare Dateigrößen — 3/247 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languageJupyter Notebook
largest_source_bytes87.623
source_files_sampled247
oversized_source_files3
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
0/20MCP-Server
40/40Lauffähige Beispiele — examples, notebooks
Verwendete Eingangsdaten
example_dirsexamples, notebooks
has_mcp_signalnein
api_schema_files

Eckdaten

701GitHub-Sterne
20Mitwirkende
157Commits, letzte 12 Monate
1Tage seit letztem Push
48Releases
1Bus-Faktor
52offene Issues
PyPIPaket-Ökosysteme

Weitere Details

OpenSSF Scorecard 5.3 / 10
5.3Gesamtwert

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 · 2026-07-19 01:05 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-Tests27 out of 27 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
4Code-ReviewFound 13/27 approved changesets -- score normalized to 4
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 21 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
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
k. A.Signed-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direkte Abhängigkeiten 30
RegistryPaketVersionsvorgabeManifest
PyPIbioimage-cpp>=0.3setup.cfg
PyPIbioimageio.coresetup.cfg
PyPIh5pysetup.cfg
PyPIimagecodecssetup.cfg
PyPIimageiosetup.cfg
PyPIjoblibsetup.cfg
PyPIkorniasetup.cfg
PyPImagicguisetup.cfg
PyPImatplotlibsetup.cfg
PyPInapari>=0.7setup.cfg
PyPInatsortsetup.cfg
PyPInetworkxsetup.cfg
PyPInumpysetup.cfg
PyPIpandassetup.cfg
PyPIpoochsetup.cfg
PyPIPyQt6setup.cfg
PyPIpython-elf>=0.9setup.cfg
PyPIscikit-imagesetup.cfg
PyPIscikit-learnsetup.cfg
PyPIsegment-anythingsetup.cfg
PyPIsuperqtsetup.cfg
PyPItimmsetup.cfg
PyPItorch>=2.5setup.cfg
PyPItorch-em>=0.9setup.cfg
PyPItorchvisionsetup.cfg
PyPItqdmsetup.cfg
PyPItrackastra>=0.5.3setup.cfg
PyPIxarraysetup.cfg
PyPIxxhashsetup.cfg
PyPIzarrsetup.cfg
Alle Abhängigkeiten 41

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 30 direkte und 11 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPIbioimage-cppdirekt
PyPIbioimageio-coredirekt
PyPIh5pydirekt
PyPIimagecodecsdirekt
PyPIimageiodirekt
PyPIjoblibdirekt
PyPIkorniadirekt
PyPImagicguidirekt
PyPImatplotlibdirekt
PyPInaparidirekt
PyPInatsortdirekt
PyPInetworkxdirekt
PyPInumpydirekt
PyPIpandasdirekt
PyPIpoochdirekt
PyPIpyqt6direkt
PyPIpython-elfdirekt
PyPIscikit-imagedirekt
PyPIscikit-learndirekt
PyPIsegment-anythingdirekt
PyPIsuperqtdirekt
PyPItimmdirekt
PyPItorchdirekt
PyPItorch-emdirekt
PyPItorchvisiondirekt
PyPItqdmdirekt
PyPItrackastradirekt
PyPIxarraydirekt
PyPIxxhashdirekt
PyPIzarrdirekt
PyPIbuildindirekt
PyPIcoverageindirekt
PyPIline-profilerindirekt
PyPIpdocindirekt
PyPIpytestindirekt
PyPIpytest-covindirekt
PyPIpytest-qtindirekt
PyPIsetuptoolsindirekt
PyPIsnakevizindirekt
PyPItabulateindirekt
PyPItwineindirekt
JSON-Rohbericht maschinenlesbar
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            "name": "Community health",
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            "notes": [],
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              "has_readme": true,
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              "has_contributing": false,
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              {
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                "detail": "recognized license (MIT)",
                "points": 22.5,
                "status": "met",
                "details": [
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                  {
                    "code": "license_spdx",
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              {
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        "description": "Does the project have users, downloads, attention, and a welcoming setup for contributors?"
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      {
        "key": "governance",
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        "name": "Sustainability & Governance",
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        "weight": 0.24,
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              "bus_factor": 1,
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                "key": "bus_factor",
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                "key": "commit_distribution",
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                "key": "openssf_scorecard_contributors",
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                "details": [],
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          },
          {
            "key": "responsiveness",
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            "note": null,
            "notes": [],
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              "merged_prs": 827,
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                "key": "issue_resolution",
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                "detail": "87% of issues closed",
                "points": 40.5,
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                    "code": "issues_closed_share",
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                      "share": 87
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                "max_points": 46.75
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                "key": "pr_acceptance",
                "name": "PR acceptance",
                "detail": "827/892 decided PRs merged",
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                "status": "partial",
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                    "code": "decided_prs_merged",
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              {
                "key": "openssf_scorecard_code_review",
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          },
          {
            "key": "stewardship",
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            "note": null,
            "notes": [],
            "value": 64,
            "inputs": {
              "followers": 86,
              "owner_type": "Organization",
              "is_verified": null,
              "owner_login": "computational-cell-analytics",
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            "components": [
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                "key": "ownership_backing",
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                "status": "met",
                "details": [
                  {
                    "code": "owner_organization",
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                ],
                "max_points": 30
              },
              {
                "key": "verified_domain",
                "name": "Verified domain",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "owner_reach",
                "name": "Owner reach",
                "detail": "86 followers of computational-cell-analytics",
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                "status": "partial",
                "details": [
                  {
                    "code": "owner_followers",
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                  }
                ],
                "max_points": 25
              },
              {
                "key": "track_record",
                "name": "Track record",
                "detail": "36 public repos, account ~4 yr old",
                "points": 19.7,
                "status": "partial",
                "details": [
                  {
                    "code": "public_repos",
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                      "count": 36
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                  },
                  {
                    "code": "account_age_years",
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                      "years": 4
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                ],
                "max_points": 25
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            ]
          },
          {
            "key": "package_maintenance",
            "band": "excellent",
            "name": "Package maintenance",
            "note": null,
            "notes": [],
            "value": 100,
            "inputs": {
              "packages": [
                "micro_sam"
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              "ecosystems": "pypi",
              "any_deprecated": false,
              "min_days_since_publish": 1
            },
            "components": [
              {
                "key": "published_resolvable",
                "name": "Published & resolvable",
                "detail": "1 package(s) on pypi",
                "points": 25,
                "status": "met",
                "details": [
                  {
                    "code": "packages_published",
                    "params": {
                      "count": 1,
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                ],
                "max_points": 25
              },
              {
                "key": "publish_recency",
                "name": "Publish recency",
                "detail": "latest publish 1 days ago",
                "points": 35,
                "status": "met",
                "details": [
                  {
                    "code": "publish_recency",
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                ],
                "max_points": 35
              },
              {
                "key": "version_history",
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                "detail": "7 published versions",
                "points": 20,
                "status": "met",
                "details": [
                  {
                    "code": "published_versions",
                    "params": {
                      "count": 7
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                  }
                ],
                "max_points": 20
              },
              {
                "key": "not_deprecated",
                "name": "Not deprecated",
                "detail": "active, not deprecated or yanked",
                "points": 20,
                "status": "met",
                "details": [
                  {
                    "code": "package_not_deprecated",
                    "params": {}
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                ],
                "max_points": 20
              }
            ]
          }
        ],
        "description": "Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?"
      },
      {
        "key": "engineering",
        "band": "good",
        "name": "Engineering Quality",
        "value": 77,
        "weight": 0.2,
        "metrics": [
          {
            "key": "engineering_practices",
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            "note": null,
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            "components": [
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                "key": "ci_workflows",
                "name": "CI workflows",
                "detail": "6 workflow(s)",
                "points": 24,
                "status": "met",
                "details": [
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                    "code": "ci_workflows",
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                      "count": 6
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                ],
                "max_points": 24
              },
              {
                "key": "tests_present",
                "name": "Tests present",
                "detail": null,
                "points": 24,
                "status": "met",
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                "max_points": 24
              },
              {
                "key": "linter_config",
                "name": "Linter config",
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                "points": 0,
                "status": "missed",
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              },
              {
                "key": "pre_commit_hooks",
                "name": "Pre-commit hooks",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 9.6
              },
              {
                "key": "editorconfig",
                "name": ".editorconfig",
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                "points": 0,
                "status": "missed",
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                "max_points": 6.4
              },
              {
                "key": "openssf_scorecard_ci_tests",
                "name": "OpenSSF Scorecard: CI-Tests",
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                "points": 20,
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                "max_points": 20
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            ]
          },
          {
            "key": "documentation",
            "band": "excellent",
            "name": "Documentation",
            "note": null,
            "notes": [],
            "value": 90,
            "inputs": {
              "topics": [
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                "cell-segmentation",
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                "nuclei-segmentation",
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              "has_wiki": false,
              "homepage": "https://computational-cell-analytics.github.io/micro-sam/",
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              "has_docs_dir": true,
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            "components": [
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                "key": "readme",
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              },
              {
                "key": "documentation_directory",
                "name": "Documentation directory",
                "detail": null,
                "points": 25,
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              },
              {
                "key": "documentation_homepage_site",
                "name": "Documentation / homepage site",
                "detail": "https://computational-cell-analytics.github.io/micro-sam/",
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                "status": "met",
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                "max_points": 15
              },
              {
                "key": "repository_description",
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                "points": 10,
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              },
              {
                "key": "topics",
                "name": "Topics",
                "detail": "9 topics",
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                "status": "met",
                "details": [
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                ],
                "max_points": 10
              },
              {
                "key": "wiki",
                "name": "Wiki",
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                "status": "missed",
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            ]
          }
        ],
        "description": "Are baseline engineering and documentation practices in place?"
      },
      {
        "key": "security",
        "band": "moderate",
        "name": "Security",
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        "weight": 0.16,
        "metrics": [
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            "key": "security_posture",
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            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
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                }
              },
              {
                "code": "weights_renormalized",
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            ],
            "value": 53,
            "inputs": {
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              "checks_evaluated": 16,
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              "scorecard_aggregate": 5.3
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            "components": [
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                "key": "binary_artifacts",
                "name": "Binary-Artifacts",
                "detail": "no binaries found in the repo",
                "points": 7.5,
                "status": "met",
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              },
              {
                "key": "branch_protection",
                "name": "Branch-Protection",
                "detail": "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",
                "points": 0,
                "status": "excluded",
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                "max_points": 7.5
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              {
                "key": "ci_tests",
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              },
              {
                "key": "cii_best_practices",
                "name": "CII-Best-Practices",
                "detail": "no effort to earn an OpenSSF best practices badge detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "code_review",
                "name": "Code-Review",
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                "status": "partial",
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              {
                "key": "contributors",
                "name": "Contributors",
                "detail": "project has 5 contributing companies or organizations",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "dangerous_workflow",
                "name": "Dangerous-Workflow",
                "detail": "no dangerous workflow patterns detected",
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "dependency_update_tool",
                "name": "Dependency-Update-Tool",
                "detail": "no update tool detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "fuzzing",
                "name": "Fuzzing",
                "detail": "project is not fuzzed",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "license",
                "name": "License",
                "detail": "license file detected",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "30 commit(s) and 21 issue activity found in the last 90 days -- score normalized to 10",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
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              {
                "key": "packaging",
                "name": "Packaging",
                "detail": "packaging workflow detected",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
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                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool is not run on all commits -- score normalized to 0",
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                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "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": [
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                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "0 existing vulnerabilities detected",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
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            ]
          },
          {
            "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,
            "inputs": {
              "meaning": "self-published location evidence; not nationality or citizenship",
              "red_flag": false,
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              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
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              "review_only_matches": 0,
              "assessed_self_published_locations": 6
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            "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": "critical",
        "name": "AI Readiness",
        "value": 25,
        "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": [
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              },
              {
                "code": "weights_renormalized",
                "params": {}
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            ],
            "value": 1,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": null,
              "agent_instruction_files": [],
              "agent_instruction_max_bytes": null
            },
            "components": [
              {
                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "no CLAUDE.md / AGENTS.md / editor rules",
                "points": 0,
                "status": "missed",
                "details": [
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                    "code": "no_agent_instructions",
                    "params": {}
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                ],
                "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": {}
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                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "critical",
            "name": "Verify loop (build / test / typecheck)",
            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
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                }
              },
              {
                "code": "weights_renormalized",
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            ],
            "value": 27,
            "inputs": {
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              "lockfiles": [],
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              "has_linter_config": false,
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              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": null
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 18
              },
              {
                "key": "automated_tests",
                "name": "Automated tests",
                "detail": null,
                "points": 22,
                "status": "met",
                "details": [],
                "max_points": 22
              },
              {
                "key": "lint_format_config",
                "name": "Lint / format config",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": null,
                "points": 0,
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Fehlende Daten werden ausgeschlossen und die Gewichte neu normiert, nie als null bewertet. Die Methodik ist versioniert und offen: Metriken v1.13.0, Schema v0.14.0 — vollständige Methodik · Metriken-Wiki.

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