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Software-GesundheitsberichtSchema 0.17.0 · Metriken 1.13.0 · 2026-07-21 05:03 UTC

JetXu-LLM / llama-github

Llama-github is an open-source Python library that empowers LLM Chatbots, AI Agents, and Auto-dev Solutions to conduct Agentic RAG from actively selected GitHub public projects. It Augments through LLMs and Generates context for any coding question, in order to streamline the development of sophisticated AI-driven applications.

PythonApache-2.0★ 291 Sterne⑂ 23 Forksseit Mai 2024Auf GitHub ansehen ↗

JetXu-LLM/llama-github erreicht einen Gesundheitsindex von 61 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Engineering Quality (72/100) ab, am schwächsten bei AI Readiness (26/100). Zuletzt vor 1 Tag aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.

61
gesamt / 100
Mittel

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.

61
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

Jet XuPersönliches Konto
36 Follower10 öffentliche Reposseit Dez. 2014

Dieses Repository gehört einem persönlichen Konto. Ein Projekt mit nur einem Eigentümer trägt ein höheres Kontinuitätsrisiko als ein organisationsgetragenes.

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlicht
PyPIllama-github0.4.5-30vor 1 Tag

Metriken nach Kategorie

Vitalität

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

70Gut · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 1 Tagen
4.2/36Commit-Rhythmus — 6/52 Wochen mit Commits
10/18Commit-Volumen — 12 Commits im letzten Jahr
5/10OpenSSF Scorecard: Maintained — 7 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
Verwendete Eingangsdaten
commits_last_year12
human_commit_share
days_since_last_push1
active_weeks_last_year6
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 30 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 1 Tagen
19.8/27Release-Rhythmus — ein Release etwa alle 46,7 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count30
latest_release_tagv0.4.5
releases_from_tagsnein
days_since_latest_release1
mean_days_between_releases46,7
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: Signed-Releases. Die verbleibenden Gewichte wurden renormalisiert.

Community & Verbreitung

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

71Gut · 18 % des Gesamtindex
Wie die Bewertung erfolgt
39.9/60Stars — 291 Stars
11.2/25Forks — 23 Forks
6.7/15Watcher — 17 Watcher
Verwendete Eingangsdaten
forks23
stars291
watchers17
growth_stateorganic
growth_factor_pct100
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (Apache-2.0)
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?

45Gefährdet · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
0.4/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 98 % der Commits
2.7/13.5Breite der Beitragenden — 2 Beitragende
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Verwendete Eingangsdaten
bus_factor1
contributors_sampled2
top_contributor_share0,983
Wie die Bewertung erfolgt
10.8/46.8Issue-Lösungsquote — 23 % der Issues geschlossen
25.5/38.3PR-Annahme — 4/6 entschiedene PRs gemergt
0/15OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0
Verwendete Eingangsdaten
merged_prs4
open_issues10
closed_issues3
issue_closed_ratio0,231
closed_unmerged_prs2
Wie die Bewertung erfolgt
10/30Organisatorische Trägerschaft — persönliches (Nutzer-)Konto
0/20Verifizierte Domain — für Nutzerkonten nicht anwendbar
11.3/25Reichweite des Inhabers — 36 Follower von JetXu-LLM
19.6/25Kontohistorie — 10 öffentliche Repos, Kontoalter ca. 11 Jahre
Verwendete Eingangsdaten
followers36
owner_typeUser
is_verified
owner_loginJetXu-LLM
public_repos10
account_age_days4.219
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Verifizierte Domain. Die verbleibenden Gewichte wurden renormalisiert.

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 1 Tagen
20/20Versionshistorie — 30 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagesllama-github
ecosystemspypi
any_deprecatednein
min_days_since_publish1

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

72Gut · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 3 Workflow(s)
24/24Tests vorhanden
0/16Linter-Konfiguration
0/9.6Pre-Commit-Hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — keine Daten
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_confignein
has_precommit_confignein
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: CI-Tests. Die verbleibenden Gewichte wurden renormalisiert.

Dokumentation

90Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://pypi.org/project/llama-github/
10/10Repository-Beschreibung
10/10Topics — 12 Topics
0/10Wiki
Verwendete Eingangsdaten
topicsai-agent, ai-code-generator, chatbot, code-generation, github, github-api, github-search, llm, python-library, retrieval-augmented-generation, jinaai, langchain
has_wikinein
homepagehttps://pypi.org/project/llama-github/
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

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

48Gefährdet · 16 % des Gesamtindex

Sicherheitslage

48Gefährdet
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
0/2.5CI-Tests — keine Daten
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/30 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
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
3.8/7.5Maintained — 7 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
5/5Packaging — packaging workflow detected
1.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 3
0/5SAST — no SAST tool detected
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — keine Daten
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate4,8
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): ci_tests, 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.

26Kritisch · 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
3/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 3
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 — Python ohne Typprüfungs-Konfiguration
53.5/55Handhabbare Dateigrößen — 1/36 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes96.307
source_files_sampled36
oversized_source_files1
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
0/20MCP-Server
40/40Lauffähige Beispiele — examples
Verwendete Eingangsdaten
example_dirsexamples
has_mcp_signalnein
api_schema_files

Eckdaten

291GitHub-Sterne
2Mitwirkende
12Commits, letzte 12 Monate
1Tage seit letztem Push
30Releases
1Bus-Faktor
10offene Issues
PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • deps.dev does not index pypi:llama-github@0.4.5; advisories assessed against the repository dependency graph instead
  • No resolved dependencies carried a version and a supported ecosystem

Weitere Details

Stern- und Fork-Verlauf 291 ★ / 0 ⇿
291Sterne

Wann jeder Stern und Fork hinzugefügt wurde, von GitHub erfasst und nach Tagen gruppiert. Das kumulierte Wachstum steht direkt über den täglichen Zugängen, aus denen es besteht, sodass beide gegeneinander lesbar sind: stetiger organischer Zuwachs sieht ganz anders aus als ein abrupter, kurzlebiger Ausschlag. Wo dieser Unterschied messbar ist, wird er als Wachstumsauthentizität ausgewiesen.

050100150200250300291332024-062025-062026-06

Jeder Punkt umfasst 2 Tage.

OpenSSF Scorecard 4.8 / 10
4.8Gesamtwert

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 · 2026-07-21 05:02 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
k. A.CI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
5Maintained7 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
10Packagingpackaging workflow detected
3Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 3
0SASTno SAST tool detected
0Security-Policysecurity policy file not detected
k. A.Signed-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direkte Abhängigkeiten 16
RegistryPaketVersionsvorgabeManifest
PyPIPyGithub>=2.4,<3pyproject.toml
PyPIPyJWT>=2.13,<3pyproject.toml
PyPIaiohttp>=3.14.1,<4pyproject.toml
PyPIipython>=8.10,<9pyproject.toml
PyPIlangchain-core>=1.3.3,<2pyproject.toml
PyPIlangchain-mistralai>=1.0,<2pyproject.toml
PyPIlangchain-openai>=1.1.14,<2pyproject.toml
PyPIlangchain-text-splitters>=1.1.2,<2pyproject.toml
PyPInest-asyncio>=1.6,<2pyproject.toml
PyPInumpy>=1.26.4,<3pyproject.toml
PyPIpydantic>=2.10,<3pyproject.toml
PyPIpython-dateutil>=2.9,<3pyproject.toml
PyPIrequests>=2.33,<3pyproject.toml
PyPItokenizers>=0.22.1,<1pyproject.toml
PyPItransformers>=5.5,<6pyproject.toml
PyPIurllib3>=2.7,<3pyproject.toml
Alle Abhängigkeiten 22

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 16 direkte und 6 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPIaiohttpdirekt
PyPIipythondirekt
PyPIlangchain-coredirekt
PyPIlangchain-mistralaidirekt
PyPIlangchain-openaidirekt
PyPIlangchain-text-splittersdirekt
PyPInest-asynciodirekt
PyPInumpydirekt
PyPIpydanticdirekt
PyPIpygithubdirekt
PyPIpyjwtdirekt
PyPIpython-dateutildirekt
PyPIrequestsdirekt
PyPItokenizersdirekt
PyPItransformersdirekt
PyPIurllib3direkt
PyPIbuildindirekt
PyPIpip-auditindirekt
PyPIpytestindirekt
PyPIpytest-asyncioindirekt
PyPIsetuptoolsindirekt
PyPItwineindirekt
Abhängigkeits-Advisories nicht bewertet

Der Advisory-Abgleich konnte für diesen Bericht nicht ausgeführt werden: No resolved dependencies carried a version and a supported ecosystem

JSON-Rohbericht maschinenlesbar
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              "scorecard_version": "v5.5.0",
              "checks_inconclusive": 2,
              "scorecard_aggregate": 4.8
            },
            "components": [
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                "key": "binary_artifacts",
                "name": "Binary-Artifacts",
                "detail": "no binaries found in the repo",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
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              {
                "key": "branch_protection",
                "name": "Branch-Protection",
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                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
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                "key": "ci_tests",
                "name": "CI-Tests",
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                "points": 0,
                "status": "excluded",
                "details": [
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                    "code": "no_data",
                    "params": {}
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                "max_points": 2.5
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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
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                "key": "code_review",
                "name": "Code-Review",
                "detail": "Found 0/30 approved changesets -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "contributors",
                "name": "Contributors",
                "detail": "project has 0 contributing companies or organizations -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "dangerous_workflow",
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                "points": 10,
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                "key": "dependency_update_tool",
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                "details": [],
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                "key": "fuzzing",
                "name": "Fuzzing",
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                "points": 0,
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                "key": "license",
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                "status": "met",
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                "key": "maintained",
                "name": "Maintained",
                "detail": "7 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5",
                "points": 3.8,
                "status": "partial",
                "details": [],
                "max_points": 7.5
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              {
                "key": "packaging",
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                "detail": "packaging workflow detected",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
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                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 3",
                "points": 1.5,
                "status": "partial",
                "details": [],
                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
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                "points": 0,
                "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",
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                "points": 0,
                "status": "excluded",
                "details": [
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                    "code": "no_data",
                    "params": {}
                  }
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                "max_points": 7.5
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              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "GitHub workflow tokens follow principle of least privilege",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
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              {
                "key": "vulnerabilities",
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                "points": 7.5,
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                "details": [],
                "max_points": 7.5
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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": "critical",
        "name": "AI Readiness",
        "value": 26,
        "weight": 0,
        "metrics": [
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            "key": "ai_agent_context",
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            "name": "Agent context & guidance",
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                "params": {
                  "components": [
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              {
                "code": "weights_renormalized",
                "params": {}
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            "value": 1,
            "inputs": {
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              "legible_history_share": null,
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            "components": [
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                "status": "missed",
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                "key": "machine_readable_docs_llms_txt",
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                "points": 0,
                "status": "missed",
                "details": [],
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                "key": "legible_commit_history",
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                "points": 0,
                "status": "excluded",
                "details": [
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                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
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                "code": "excluded_no_data",
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                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
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                "details": [
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                    "params": {}
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 3",
                "points": 3,
                "status": "partial",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "moderate",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 54,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 96307,
              "source_files_sampled": 36,
              "oversized_source_files": 1
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python without a type-check config",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_typecheck_config_language",
                    "params": {
                      "language": "Python"
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                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "1/36 source files over 60KB",
                "points": 53.5,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 36,
                      "oversized": 1
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "at_risk",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "example_dirs": [
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              ],
              "has_mcp_signal": false,
              "api_schema_files": []
            },
            "components": [
              {
                "key": "api_schema_openapi_graphql_proto",
                "name": "API schema (OpenAPI/GraphQL/proto)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
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                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
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                "detail": "examples",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "examples"
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [
    "deps.dev does not index pypi:llama-github@0.4.5; advisories assessed against the repository dependency graph instead",
    "No resolved dependencies carried a version and a supported ecosystem"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-21T05:03:00.183311Z",
  "schema_version": "0.17.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/j/JetXu-LLM/llama-github.svg",
  "full_name": "JetXu-LLM/llama-github",
  "license_state": "standard",
  "license_spdx": "Apache-2.0"
}

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 v0.17.0 — vollständige Methodik · Metriken-Wiki.

Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte StatistikenPyPI.