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Software-GesundheitsberichtSchema 0.9.0 · Metriken 1.13.0 · 2026-07-13 00:53 UTC

Significant-Gravitas / AutoGPT

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

Python · TypeScriptEigene Lizenz★ 185.497 Sterne⑂ 46.106 Forksseit März 2023Auf GitHub ansehen ↗
#agentic-ai#agents#ai#artificial-intelligence#autonomous-agents#claude#gpt#llama-api#llm#openai#python

Significant-Gravitas/AutoGPT erreicht einen Gesundheitsindex von 86 von 100 und liegt damit im Bereich Exzellent. Am stärksten schneidet es bei Vitality (100/100) ab, am schwächsten bei Security (58/100). Zuletzt vor 1 Tag aktualisiert. 5 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

AutoGPTOrganisation
4.455 Follower28 öffentliche Reposseit Apr. 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?

100Exzellent · 22 % des Gesamtindex

Entwicklungsaktivität

100Exzellent
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 1 Tagen
36/36Commit-Rhythmus — 52/52 Wochen mit Commits
18/18Commit-Volumen — 1.841 Commits im letzten Jahr
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 7 issue activity found in the last 90 days -- score normalized to 10
Verwendete Eingangsdaten
commits_last_year1.841
human_commit_share—
days_since_last_push1
active_weeks_last_year52

Release-Disziplin

100Exzellent
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 100 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 4 Tagen
27/27Release-Rhythmus — ein Release etwa alle 8,6 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count100
latest_release_tagautogpt-platform-beta-v0.6.66
releases_from_tagsnein
days_since_latest_release4
mean_days_between_releases8,6
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: Signed-Releases. Die verbleibenden Gewichte wurden renormalisiert.

Community & Verbreitung

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

93Exzellent · 18 % des Gesamtindex

Popularität & Verbreitung

100Exzellent
Wie die Bewertung erfolgt
60/60Stars — 185.497 Stars
25/25Forks — 46.106 Forks
15/15Watcher — 1.547 Watcher
Verwendete Eingangsdaten
forks46.106
stars185.497
watchers1.547
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community-Gesundheit

86Exzellent
Wie die Bewertung erfolgt
22.5/22.5README
16.9/22.5Lizenz — Lizenzdatei vorhanden, keine anerkannte Lizenz
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?

80Gut · 24 % des Gesamtindex

Maintainer-Resilienz (Bus-Faktor)

89Exzellent
Wie die Bewertung erfolgt
45.9/54Bus-Faktor — 5 Beitragende decken die Hälfte aller Commits ab
19.4/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 14 % der Commits
13.5/13.5Breite der Beitragenden — 100 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 18 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor5
contributors_sampled100
top_contributor_share0,137

Reaktionsfähigkeit bei Issues & PRs

77Gut
Wie die Bewertung erfolgt
43.3/46.8Issue-Lösungsquote — 93 % der Issues geschlossen
21.7/38.3PR-Annahme — 4.608/8.126 entschiedene PRs gemergt
12/15OpenSSF Scorecard: Code-Review — Found 25/30 approved changesets -- score normalized to 8
Verwendete Eingangsdaten
merged_prs4.608
open_issues285
closed_issues3.606
issue_closed_ratio0,927
closed_unmerged_prs3.518

Eigentümerschaft & Trägerschaft

72Gut
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
25/25Reichweite des Inhabers — 4.455 Follower von Significant-Gravitas
17.1/25Kontohistorie — 28 öffentliche Repos, Kontoalter ca. 3 Jahre
Verwendete Eingangsdaten
followers4.455
owner_typeOrganization
is_verified—
owner_loginSignificant-Gravitas
public_repos28
account_age_days1.185

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

96Exzellent · 20 % des Gesamtindex

Engineering-Praktiken

94Exzellent
Wie die Bewertung erfolgt
24/24CI-Workflows — 33 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration — .eslintrc.json, .flake8
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

100Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://agpt.co
10/10Repository-Beschreibung
10/10Topics — 11 Topics
10/10Wiki
Verwendete Eingangsdaten
topicsagentic-ai, agents, ai, artificial-intelligence, autonomous-agents, claude, gpt, llama-api, llm, openai, python
has_wikija
homepagehttps://agpt.co
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

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

58Mittel · 16 % des Gesamtindex

Sicherheitslage

58Mittel
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
6/7.5Branch-Protection — branch protection is not maximal on development and all release branches
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
6/7.5Code-Review — Found 25/30 approved changesets -- score normalized to 8
2.5/2.5Contributors — project has 18 contributing companies or organizations
0/10Dangerous-Workflow — dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5Lizenz — license file detected
7.5/7.5Maintained — 30 commit(s) and 7 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
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — keine Daten
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 233 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5,8
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): 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.

75Gut · 0 % des Gesamtindex

AI-Agentenkontext & Leitlinien

75Gut
Wie die Bewertung erfolgt
45/45Agentenanweisungen — .claude/skills/vercel-react-best-practices/AGENTS.md, .github/copilot-instructions.md, AGENTS.md, CLAUDE.md, autogpt_platform/AGENTS.md, autogpt_platform/CLAUDE.md, autogpt_platform/backend/AGENTS.md, autogpt_platform/backend/CLAUDE.md, autogpt_platform/backend/backend/copilot/bot/AGENTS.md, autogpt_platform/backend/backend/copilot/bot/CLAUDE.md, autogpt_platform/backend/backend/copilot/graphiti/AGENTS.md, autogpt_platform/backend/backend/copilot/graphiti/CLAUDE.md, autogpt_platform/frontend/AGENTS.md, autogpt_platform/frontend/CLAUDE.md, autogpt_platform/frontend/src/tests/AGENTS.md, autogpt_platform/frontend/src/tests/CLAUDE.md, classic/CLAUDE.md, classic/direct_benchmark/CLAUDE.md, classic/forge/CLAUDE.md, classic/original_autogpt/CLAUDE.md, docs/AGENTS.md, docs/CLAUDE.md, docs/content/forge/components/agents.md, docs/platform/gemini.md
0/15Maschinenlesbare Doku (llms.txt)
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share—
agent_instruction_files.claude/skills/vercel-react-best-practices/AGENTS.md, .github/copilot-instructions.md, AGENTS.md, CLAUDE.md, autogpt_platform/AGENTS.md, autogpt_platform/CLAUDE.md, autogpt_platform/backend/AGENTS.md, autogpt_platform/backend/CLAUDE.md, autogpt_platform/backend/backend/copilot/bot/AGENTS.md, autogpt_platform/backend/backend/copilot/bot/CLAUDE.md, autogpt_platform/backend/backend/copilot/graphiti/AGENTS.md, autogpt_platform/backend/backend/copilot/graphiti/CLAUDE.md, autogpt_platform/frontend/AGENTS.md, autogpt_platform/frontend/CLAUDE.md, autogpt_platform/frontend/src/tests/AGENTS.md, autogpt_platform/frontend/src/tests/CLAUDE.md, classic/CLAUDE.md, classic/direct_benchmark/CLAUDE.md, classic/forge/CLAUDE.md, classic/original_autogpt/CLAUDE.md, docs/AGENTS.md, docs/CLAUDE.md, docs/content/forge/components/agents.md, docs/platform/gemini.md
agent_instruction_max_bytes60.535
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lesbare Commit-Historie. Die verbleibenden Gewichte wurden renormalisiert.

AI-Verify-Loop (Build / Test / Typprüfung)

86Exzellent
Wie die Bewertung erfolgt
18/18Bootstrap mit einem Befehl — autogpt_platform/Makefile
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration — .eslintrc.json, .flake8
11/11Statische Typprüfung — autogpt_platform/backend/pyrightconfig.json, autogpt_platform/frontend/tsconfig.json
10/10Reproduzierbare Umgebung — devcontainer, Dockerfile, 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
lockfilespnpm-lock.yaml, poetry.lock
has_dockerfileja
typed_languagenein
bootstrap_filesautogpt_platform/Makefile
has_devcontainerja
has_linter_configja
typecheck_configsautogpt_platform/backend/pyrightconfig.json, autogpt_platform/frontend/tsconfig.json
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.

AI-Code-Lesbarkeit für Modelle

81Gut
Wie die Bewertung erfolgt
27/45Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (autogpt_platform/backend/pyrightconfig.json, autogpt_platform/frontend/tsconfig.json)
54.3/55Handhabbare Dateigrößen — 42/3.223 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes253.703
source_files_sampled3.223
oversized_source_files42

Maschinenlesbare AI-Schnittstellen

40Gefährdet
Wie die Bewertung erfolgt
40/40API-Schema (OpenAPI/GraphQL/proto) — autogpt_platform/frontend/src/app/api/openapi.json
0/20MCP-Server
0/40Lauffähige Beispiele
Verwendete Eingangsdaten
example_dirs—
has_mcp_signalnein
api_schema_filesautogpt_platform/frontend/src/app/api/openapi.json

Eckdaten

185.497GitHub-Sterne
100Mitwirkende
1.841Commits, letzte 12 Monate
1Tage seit letztem Push
100Releases
5Bus-Faktor
285offene Issues
PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • Could not fetch pypi package 'autogpt-classic' from its registry

Weitere Details

OpenSSF Scorecard 5.8 / 10
5.8Gesamtwert

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 · 2026-07-13 00:53 UTC

10Binary-Artifactsno binaries found in the repo
8Branch-Protectionbranch protection is not maximal on development and all release branches
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
8Code-ReviewFound 25/30 approved changesets -- score normalized to 8
10Contributorsproject has 18 contributing companies or organizations
0Dangerous-Workflowdangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
10Maintained30 commit(s) and 7 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
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
k. A.Signed-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities233 existing vulnerabilities detected
Direkte Abhängigkeiten 50
RegistryPaketVersionsvorgabeManifest
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PyPIanthropic^0.45.0classic/pyproject.toml
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PyPIlitellm>=1.17.9,<1.82.7classic/pyproject.toml
PyPIopenai^1.50.0classic/pyproject.toml
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PyPIuvicorn>=0.23.2,<1classic/pyproject.toml
PyPIpython-multipart^0.0.7classic/pyproject.toml
PyPIcharset-normalizer^3.1.0classic/pyproject.toml
PyPIdemjson3^3.0.0classic/pyproject.toml
PyPIjsonschema*classic/pyproject.toml
PyPIorjson^3.8.10classic/pyproject.toml
PyPIpydantic^2.7.2classic/pyproject.toml
PyPIpyyaml^6.0classic/pyproject.toml
PyPItoml^0.10.2classic/pyproject.toml
PyPIboto3^1.33.6classic/pyproject.toml
PyPIchromadb^1.4.0classic/pyproject.toml
PyPIgoogle-cloud-logging^3.8.0classic/pyproject.toml
PyPIgoogle-cloud-storage^2.13.0classic/pyproject.toml
PyPIsqlalchemy^2.0.19classic/pyproject.toml
PyPIclick^8.0classic/pyproject.toml
PyPIcolorama^0.4.6classic/pyproject.toml
PyPIprompt-toolkit^3.0.0classic/pyproject.toml
PyPIrich^13.0classic/pyproject.toml
PyPIpypdf^3.1.0classic/pyproject.toml
PyPIpython-docx*classic/pyproject.toml
PyPIpylatexenc*classic/pyproject.toml
PyPIPillow*classic/pyproject.toml
PyPIen-core-web-sm—classic/pyproject.toml
PyPIspacy^3.8.0classic/pyproject.toml
PyPIddgs^9.9classic/pyproject.toml
PyPIgoogle-api-python-client^2.116classic/pyproject.toml
PyPIplaywright^1.50.0classic/pyproject.toml
PyPIdistro^1.8.0classic/pyproject.toml
PyPIdocker*classic/pyproject.toml
PyPIgitpython^3.1.32classic/pyproject.toml
PyPIgTTS^2.3.1classic/pyproject.toml
PyPIjinja2^3.1.2classic/pyproject.toml
PyPInumpy>=2.0.0classic/pyproject.toml
PyPIplaysound~1.2.2classic/pyproject.toml
PyPIpython-dotenv^1.0.0classic/pyproject.toml
PyPIsentry-sdk^1.40.4classic/pyproject.toml
PyPItenacity^8.2.2classic/pyproject.toml
PyPIwatchdog^6.0.0classic/pyproject.toml
PyPIpytest^8.0classic/pyproject.toml
JSON-Rohbericht maschinenlesbar
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        ],
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                "key": "openssf_scorecard_contributors",
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            "key": "responsiveness",
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                "key": "issue_resolution",
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                "key": "pr_acceptance",
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                "key": "openssf_scorecard_code_review",
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            "key": "stewardship",
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              "followers": 4455,
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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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        "key": "engineering",
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            "key": "engineering_practices",
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                "key": "ci_workflows",
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                "key": "pre_commit_hooks",
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        ],
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                "key": "branch_protection",
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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",
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                "key": "packaging",
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                "key": "pinned_dependencies",
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                "key": "sast",
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                "key": "security_policy",
                "name": "Security-Policy",
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              {
                "key": "signed_releases",
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                "max_points": 7.5
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                "key": "token_permissions",
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                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "233 existing vulnerabilities detected",
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            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
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                "code": "jurisdiction_evidence_limits",
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            "value": 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?"
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        "key": "ai_readiness",
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            ],
            "value": 75,
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                "CLAUDE.md",
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                "classic/direct_benchmark/CLAUDE.md",
                "classic/forge/CLAUDE.md",
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}

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