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Software-GesundheitsberichtSchema 0.12.0 · Metriken 1.13.0 · 2026-07-18 13:40 UTC

langchain-ai / langchain-aws

Build LangChain Applications on AWS

PythonMIT★ 332 Sterne⑂ 297 Forksseit März 2024Auf GitHub ansehen ↗

langchain-ai/langchain-aws erreicht einen Gesundheitsindex von 75 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Vitality (95/100) ab, am schwächsten bei Security (61/100). Zuletzt vor 2 Tagen aktualisiert. 4 Mitwirkende tragen den Großteil der jüngsten Arbeit.

75
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.

75
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

LangChainOrganisation
20.950 Follower251 öffentliche Reposseit März 2023

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?

95Exzellent · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 2 Tagen
34.6/36Commit-Rhythmus — 50/52 Wochen mit Commits
18/18Commit-Volumen — 385 Commits im letzten Jahr
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 11 issue activity found in the last 90 days -- score normalized to 10
Verwendete Eingangsdaten
commits_last_year385
human_commit_share
days_since_last_push2
active_weeks_last_year50
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 100 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 11 Tagen
27/27Release-Rhythmus — ein Release etwa alle 5,4 Tage
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Verwendete Eingangsdaten
releases_count100
latest_release_taglangchain-aws==1.6.2
releases_from_tagsnein
days_since_latest_release11
mean_days_between_releases5,4

Community & Verbreitung

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

75Gut · 18 % des Gesamtindex
Wie die Bewertung erfolgt
40.9/60Stars — 332 Stars
20.6/25Forks — 297 Forks
4.3/15Watcher — 7 Watcher
Verwendete Eingangsdaten
forks297
stars332
watchers7
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
0/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
has_issue_templatenein
has_code_of_conductja
has_pull_request_templatenein

Nachhaltigkeit & Governance

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

78Gut · 24 % des Gesamtindex
Wie die Bewertung erfolgt
43.2/54Bus-Faktor — 4 Beitragende decken die Hälfte aller Commits ab
17.5/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 22 % der Commits
13.5/13.5Breite der Beitragenden — 100 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 6 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor4
contributors_sampled100
top_contributor_share0,222
Wie die Bewertung erfolgt
38.8/46.8Issue-Lösungsquote — 83 % der Issues geschlossen
33.4/38.3PR-Annahme — 649/743 entschiedene PRs gemergt
1.5/15OpenSSF Scorecard: Code-Review — Found 5/26 approved changesets -- score normalized to 1
Verwendete Eingangsdaten
merged_prs649
open_issues63
closed_issues307
issue_closed_ratio0,83
closed_unmerged_prs94
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
25/25Reichweite des Inhabers — 20.950 Follower von langchain-ai
19.8/25Kontohistorie — 251 öffentliche Repos, Kontoalter ca. 3 Jahre
Verwendete Eingangsdaten
followers20.950
owner_typeOrganization
is_verified
owner_loginlangchain-ai
public_repos251
account_age_days1.234

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

61Mittel · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 11 Workflow(s)
24/24Tests vorhanden
0/16Linter-Konfiguration
0/9.6Pre-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_confignein
has_precommit_confignein
Wie die Bewertung erfolgt
30/30README
0/25Dokumentationsverzeichnis
0/15Dokumentations-/Homepage-Site
10/10Repository-Beschreibung
10/10Topics — 4 Topics
0/10Wiki
Verwendete Eingangsdaten
topicsaws, generative-ai, langchain, langchain-python
has_wikinein
homepage
has_readmeja
has_docs_dirnein
has_descriptionja

Sicherheit

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

61Mittel · 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
0.8/7.5Code-Review — Found 5/26 approved changesets -- score normalized to 1
2.5/2.5Contributors — project has 6 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 11 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
1.5/5SAST — SAST tool is not run on all commits -- score normalized to 3
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6,1
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection. 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.

80Gut · 0 % des Gesamtindex
Wie die Bewertung erfolgt
45/45Agentenanweisungen — AGENTS.md, CLAUDE.md
15/15Maschinenlesbare Doku (llms.txt) — llms.txt vorhanden
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtja
legible_history_share
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes7.965
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lesbare Commit-Historie. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
18/18Bootstrap mit einem Befehl — libs/agentcore-codeinterpreter/Makefile, libs/aws/Makefile, libs/langgraph-checkpoint-aws/Makefile
22/22Automatisierte Tests
0/11Lint-/Format-Konfiguration
11/11Statische Typprüfung — libs/aws/langchain_aws/py.typed
10/10Reproduzierbare Umgebung — lockfile
0/10Belegte Agentenpraxis — keine Daten
5/8Automatisierte Wartung — Abhängigkeits-Automatisierung konfiguriert, in den erfassten Commits nicht beobachtet
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfilesuv.lock
has_dockerfilenein
typed_languagenein
bootstrap_fileslibs/agentcore-codeinterpreter/Makefile, libs/aws/Makefile, libs/langgraph-checkpoint-aws/Makefile
has_devcontainernein
has_linter_confignein
typecheck_configslibs/aws/langchain_aws/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 (libs/aws/langchain_aws/py.typed)
53.6/55Handhabbare Dateigrößen — 7/278 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes221.460
source_files_sampled278
oversized_source_files7
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
20/20MCP-Server
40/40Lauffähige Beispiele — notebooks, samples
Verwendete Eingangsdaten
example_dirsnotebooks, samples
has_mcp_signalja
api_schema_files

Eckdaten

332GitHub-Sterne
100Mitwirkende
385Commits, letzte 12 Monate
2Tage seit letztem Push
100Releases
4Bus-Faktor
63offene Issues
Paket-Ökosysteme

Weitere Details

OpenSSF Scorecard 6.1 / 10
6.1Gesamtwert

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 13:39 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
1Code-ReviewFound 5/26 approved changesets -- score normalized to 1
10Contributorsproject has 6 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 11 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
3SASTSAST tool is not run on all commits -- score normalized to 3
10Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Alle Abhängigkeiten 174

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 174 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPIannotated-types0.7.0indirekt
PyPIanthropic0.111.0indirekt
PyPIanthropic0.116.0indirekt
PyPIanyio4.14.0indirekt
PyPIanyio4.14.1indirekt
PyPIast-serialize0.5.0indirekt
PyPIast-serialize0.6.0indirekt
PyPIasync-timeout4.0.3indirekt
PyPIasync-timeout5.0.1indirekt
PyPIaws-sdk-bedrock-runtime0.7.0indirekt
PyPIaws-sdk-signers0.3.0indirekt
PyPIawscrt0.32.2indirekt
PyPIbackports-asyncio-runner1.2.0indirekt
PyPIbeautifulsoup44.15.0indirekt
PyPIbedrock-agentcore1.15.0indirekt
PyPIbedrock-agentcore1.17.0indirekt
PyPIboto31.43.36indirekt
PyPIboto31.43.39indirekt
PyPIboto31.43.40indirekt
PyPIboto3-stubs1.43.35indirekt
PyPIboto3-stubs1.43.39indirekt
PyPIboto3-stubs1.43.40indirekt
PyPIbotocore1.43.36indirekt
PyPIbotocore1.43.39indirekt
PyPIbotocore1.43.40indirekt
PyPIbotocore-stubs1.43.14indirekt
PyPIbracex2.6indirekt
PyPIcertifi2026.6.17indirekt
PyPIcffi2.0.0indirekt
PyPIcharset-normalizer3.4.7indirekt
PyPIcharset-normalizer3.4.8indirekt
PyPIclick8.4.1indirekt
PyPIclick8.4.2indirekt
PyPIcolorama0.4.6indirekt
PyPIcoverage7.14.3indirekt
PyPIcoverage7.15.0indirekt
PyPIcryptography49.0.0indirekt
PyPIdeepagents0.6.11indirekt
PyPIdistro1.9.0indirekt
PyPIdocstring-parser0.18.0indirekt
PyPIexceptiongroup1.3.1indirekt
PyPIexecnet2.1.2indirekt
PyPIfakeredis2.36.2indirekt
PyPIfiletype1.2.0indirekt
PyPIgoogle-auth2.55.0indirekt
PyPIgoogle-genai2.9.0indirekt
PyPIgreenlet3.5.3indirekt
PyPIh110.16.0indirekt
PyPIhttpcore1.0.9indirekt
PyPIhttpx0.28.1indirekt
PyPIidna3.18indirekt
PyPIijson3.5.1indirekt
PyPIiniconfig2.3.0indirekt
PyPIjiter0.15.0indirekt
PyPIjiter0.16.0indirekt
PyPIjmespath1.1.0indirekt
PyPIjsonpatch1.33indirekt
PyPIjsonpointer3.1.1indirekt
PyPIlangchain1.3.11indirekt
PyPIlangchain-agentcore-codeinterpreter0.0.5indirekt
PyPIlangchain-anthropic1.4.7indirekt
PyPIlangchain-anthropic1.4.8indirekt
PyPIlangchain-aws1.6.1indirekt
PyPIlangchain-aws1.6.2indirekt
PyPIlangchain-classic1.0.8indirekt
PyPIlangchain-core1.4.8indirekt
PyPIlangchain-google-genai4.2.5indirekt
PyPIlangchain-protocol0.0.18indirekt
PyPIlangchain-tests1.1.9indirekt
PyPIlangchain-text-splitters1.1.2indirekt
PyPIlanggraph1.2.6indirekt
PyPIlanggraph1.2.7indirekt
PyPIlanggraph-checkpoint4.1.1indirekt
PyPIlanggraph-checkpoint-aws1.2.0indirekt
PyPIlanggraph-checkpoint-conformance0.0.2indirekt
PyPIlanggraph-prebuilt1.1.0indirekt
PyPIlanggraph-sdk0.4.2indirekt
PyPIlangsmith0.9.0indirekt
PyPIlangsmith0.9.6indirekt
PyPIlangsmith0.9.7indirekt
PyPIlibrt0.11.0indirekt
PyPIlibrt0.12.0indirekt
PyPImarkdown-it-py4.2.0indirekt
PyPImdurl0.1.2indirekt
PyPImypy2.1.0indirekt
PyPImypy-boto3-cloudformation1.43.23indirekt
PyPImypy-boto3-cloudformation1.43.38indirekt
PyPImypy-boto3-dynamodb1.43.0indirekt
PyPImypy-boto3-ec21.43.35indirekt
PyPImypy-boto3-ec21.43.39indirekt
PyPImypy-boto3-lambda1.43.35indirekt
PyPImypy-boto3-lambda1.43.37indirekt
PyPImypy-boto3-rds1.43.30indirekt
PyPImypy-boto3-s31.43.31indirekt
PyPImypy-boto3-sqs1.43.0indirekt
PyPImypy-extensions1.1.0indirekt
PyPInumpy2.0.2indirekt
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PyPInumpy2.4.6indirekt
PyPInumpy2.5.0indirekt
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PyPIormsgpack1.12.2indirekt
PyPIpackaging26.2indirekt
PyPIpathspec1.1.1indirekt
PyPIplaywright1.61.0indirekt
PyPIpluggy1.6.0indirekt
PyPIprotobuf7.35.1indirekt
PyPIpy-cpuinfo9.0.0indirekt
PyPIpyasn10.6.3indirekt
PyPIpyasn1-modules0.4.2indirekt
PyPIpycparser3.0indirekt
PyPIpydantic2.13.4indirekt
PyPIpydantic2.14.0a1indirekt
PyPIpydantic-core2.46.4indirekt
PyPIpydantic-core2.47.0indirekt
PyPIpyee13.0.1indirekt
PyPIpygments2.20.0indirekt
PyPIpytest9.1.1indirekt
PyPIpytest-asyncio1.4.0indirekt
PyPIpytest-benchmark5.2.3indirekt
PyPIpytest-codspeed5.0.3indirekt
PyPIpytest-cov7.1.0indirekt
PyPIpytest-mock3.15.1indirekt
PyPIpytest-recording0.13.4indirekt
PyPIpytest-socket0.8.0indirekt
PyPIpytest-watcher0.6.3indirekt
PyPIpytest-xdist3.8.0indirekt
PyPIpython-dateutil2.9.0.post0indirekt
PyPIpyyaml6.0.3indirekt
PyPIredis8.0.1indirekt
PyPIrequests2.34.2indirekt
PyPIrequests-toolbelt1.0.0indirekt
PyPIrich15.0.0indirekt
PyPIruff0.15.18indirekt
PyPIruff0.15.20indirekt
PyPIs3transfer0.19.0indirekt
PyPIsix1.17.0indirekt
PyPIsmithy-aws-core0.7.0indirekt
PyPIsmithy-aws-event-stream0.3.0indirekt
PyPIsmithy-core0.6.0indirekt
PyPIsmithy-http0.4.2indirekt
PyPIsmithy-json0.2.3indirekt
PyPIsniffio1.3.1indirekt
PyPIsortedcontainers2.4.0indirekt
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PyPIsyrupy5.3.2indirekt
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PyPItypes-requests2.33.0.20260518indirekt
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PyPItyping-extensions4.16.0indirekt
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PyPIxxhash3.8.0indirekt
PyPIxxhash3.8.1indirekt
PyPIzstandard0.25.0indirekt
JSON-Rohbericht maschinenlesbar
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                ],
                "max_points": 13.5
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              {
                "key": "openssf_scorecard_contributors",
                "name": "OpenSSF Scorecard: Contributors",
                "detail": "project has 6 contributing companies or organizations",
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
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            ]
          },
          {
            "key": "responsiveness",
            "band": "good",
            "name": "Issue & PR responsiveness",
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            "notes": [],
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              "merged_prs": 649,
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              "closed_issues": 307,
              "issue_closed_ratio": 0.83,
              "closed_unmerged_prs": 94
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                "key": "issue_resolution",
                "name": "Issue resolution",
                "detail": "83% of issues closed",
                "points": 38.8,
                "status": "partial",
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                  {
                    "code": "issues_closed_share",
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                      "share": 83
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                "max_points": 46.75
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              {
                "key": "pr_acceptance",
                "name": "PR acceptance",
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                "max_points": 38.25
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              {
                "key": "openssf_scorecard_code_review",
                "name": "OpenSSF Scorecard: Code-Review",
                "detail": "Found 5/26 approved changesets -- score normalized to 1",
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            "key": "stewardship",
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            "notes": [],
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                "key": "ownership_backing",
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                "max_points": 30
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                "key": "verified_domain",
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                "status": "missed",
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                "key": "owner_reach",
                "name": "Owner reach",
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                "status": "met",
                "details": [
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                    "code": "owner_followers",
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                      "count": 20950,
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                "max_points": 25
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              {
                "key": "track_record",
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        ],
        "description": "Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?"
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        "key": "engineering",
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        "name": "Engineering Quality",
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        "weight": 0.2,
        "metrics": [
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            "notes": [],
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                "key": "ci_workflows",
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                "detail": "11 workflow(s)",
                "points": 24,
                "status": "met",
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                "max_points": 24
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              {
                "key": "tests_present",
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                "points": 24,
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              {
                "key": "linter_config",
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                "details": [],
                "max_points": 6.4
              },
              {
                "key": "openssf_scorecard_ci_tests",
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                "detail": "30 out of 30 merged PRs checked by a CI test -- score normalized to 10",
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          },
          {
            "key": "documentation",
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            "notes": [],
            "value": 50,
            "inputs": {
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              "homepage": null,
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                "key": "documentation_directory",
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                "status": "missed",
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              {
                "key": "documentation_homepage_site",
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                "status": "missed",
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              {
                "key": "repository_description",
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                "points": 10,
                "status": "met",
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                "max_points": 10
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              {
                "key": "topics",
                "name": "Topics",
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                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "topics_count",
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                "max_points": 10
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              {
                "key": "wiki",
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                "detail": null,
                "points": 0,
                "status": "missed",
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                "max_points": 10
              }
            ]
          }
        ],
        "description": "Are baseline engineering and documentation practices in place?"
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      {
        "key": "security",
        "band": "moderate",
        "name": "Security",
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        "weight": 0.16,
        "metrics": [
          {
            "key": "security_posture",
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            "note": "Excluded from scoring (no data or not applicable): Branch-Protection. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
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              },
              {
                "code": "weights_renormalized",
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            "value": 61,
            "inputs": {
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            "components": [
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                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "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",
                "details": [
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                    "params": {}
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                ],
                "max_points": 7.5
              },
              {
                "key": "ci_tests",
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                "detail": "30 out of 30 merged PRs checked by a CI test -- score normalized to 10",
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                "max_points": 2.5
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                "key": "cii_best_practices",
                "name": "CII-Best-Practices",
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                "points": 0,
                "status": "missed",
                "details": [],
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              {
                "key": "code_review",
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                "detail": "Found 5/26 approved changesets -- score normalized to 1",
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                "max_points": 2.5
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              {
                "key": "dangerous_workflow",
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                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
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              {
                "key": "dependency_update_tool",
                "name": "Dependency-Update-Tool",
                "detail": "update tool detected",
                "points": 7.5,
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                "details": [],
                "max_points": 7.5
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              {
                "key": "fuzzing",
                "name": "Fuzzing",
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                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
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                "key": "license",
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                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
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                "key": "maintained",
                "name": "Maintained",
                "detail": "30 commit(s) and 11 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
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              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
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                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
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              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool is not run on all commits -- score normalized to 3",
                "points": 1.5,
                "status": "partial",
                "details": [],
                "max_points": 5
              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file detected",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "Project has not signed or included provenance with any releases.",
                "points": 0,
                "status": "missed",
                "details": [],
                "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",
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            "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,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
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              "review_only_matches": 0,
              "assessed_self_published_locations": 5
            },
            "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": {}
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                "max_points": 100
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          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "good",
        "name": "AI Readiness",
        "value": 80,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "excellent",
            "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": 100,
            "inputs": {
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              "legible_history_share": null,
              "agent_instruction_files": [
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              "agent_instruction_max_bytes": 7965
            },
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                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "AGENTS.md, CLAUDE.md",
                "points": 45,
                "status": "met",
                "details": [
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                    "code": "file_list",
                    "params": {
                      "files": "AGENTS.md, CLAUDE.md"
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                  }
                ],
                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": "llms.txt present",
                "points": 15,
                "status": "met",
                "details": [
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                    "code": "llms_txt_present",
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                "max_points": 15
              },
              {
                "key": "legible_commit_history",
                "name": "Legible commit history",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
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                    "code": "no_data",
                    "params": {}
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                ],
                "max_points": 40
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            ]
          },
          {
            "key": "ai_verify_loop",
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                "code": "excluded_no_data",
                "params": {
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                "code": "weights_renormalized",
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                "key": "automated_maintenance",
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                "details": [
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                "max_points": 8
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              {
                "key": "openssf_scorecard_pinned_dependencies",
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                "points": 0,
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                "max_points": 40
              },
              {
                "key": "mcp_server",
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                "points": 20,
                "status": "met",
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              },
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                "key": "runnable_examples",
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        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
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    "metrics_version": "1.13.0"
  },
  "warnings": [],
  "report_type": "repository",
  "generated_at": "2026-07-18T13:40:17.837536Z",
  "schema_version": "0.12.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/l/langchain-ai/langchain-aws.svg",
  "full_name": "langchain-ai/langchain-aws",
  "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.

Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken.