Öffentliches Register
Software-GesundheitsberichtSchema 0.25.0 · Metriken 1.13.0 · 2026-07-21 23:06 UTC

Aider-AI / aider

aider is AI pair programming in your terminal

PythonApache-2.0★ 47.589 Sterne⑂ 4.746 Forksseit Mai 2023Auf GitHub ansehen ↗

Aider-AI/aider erreicht einen Gesundheitsindex von 63 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Community & Adoption (88/100) ab, am schwächsten bei Security (10/100). Zuletzt vor 60 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.

63
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.

63
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

Aider AIOrganisation
794 Follower7 öffentliche Reposseit Juni 2024

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

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlicht
PyPIaider-chat0.86.2848.398174vor 159 Tagen

Metriken nach Kategorie

Vitalität

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

68Mittel · 22 % des Gesamtindex
Wie die Bewertung erfolgt
18/36Push-Aktualität — letzter Push vor 60 Tagen
18.7/36Commit-Rhythmus — 27/52 Wochen mit Commits
18/18Commit-Volumen — 182 Commits im letzten Jahr
0/10OpenSSF Scorecard: Maintained — keine Daten
Verwendete Eingangsdaten
commits_last_year182
human_commit_share1
days_since_last_push60
active_weeks_last_year27
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 93 Releases veröffentlicht
16.2/36Release-Aktualität — letztes Release vor 346 Tagen
27/27Release-Rhythmus — ein Release etwa alle 16,5 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count93
latest_release_tagv0.86.0
releases_from_tagsnein
days_since_latest_release346
mean_days_between_releases16,5

Community & Verbreitung

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

88Exzellent · 18 % des Gesamtindex
Wie die Bewertung erfolgt
60/60Stars — 47.589 Stars
25/25Forks — 4.746 Forks
13.4/15Watcher — 254 Watcher
Verwendete Eingangsdaten
forks4.746
stars47.589
watchers254
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonwindow_too_short
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (Apache-2.0)
18/18CONTRIBUTING-Leitfaden
0/13.5Verhaltenskodex
0/7.2Issue-Vorlage
0/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
has_issue_templatenein
has_code_of_conductnein
has_pull_request_templatenein
Wie die Bewertung erfolgt
79/80Downloads pro Monat — 848.398 Downloads/Monat über pypi
0/20Abhängige in der Registry — von diesem Ökosystem nicht ausgewiesen
Verwendete Eingangsdaten
packagesaider-chat
dependents
ecosystemspypi
total_downloads
monthly_downloads848.398
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Abhängige in der Registry. Die verbleibenden Gewichte wurden renormalisiert.

Nachhaltigkeit & Governance

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

58Mittel · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
0.7/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 97 % der Commits
13.5/13.5Breite der Beitragenden — 100 Beitragende
0/10OpenSSF Scorecard: Contributors — keine Daten
Verwendete Eingangsdaten
bus_factor1
contributors_sampled100
top_contributor_share0,97
Wie die Bewertung erfolgt
32.4/46.8Issue-Lösungsquote — 69 % der Issues geschlossen
16.1/38.3PR-Annahme — 288/683 entschiedene PRs gemergt
0/15OpenSSF Scorecard: Code-Review — keine Daten
Verwendete Eingangsdaten
merged_prs288
open_issues1.320
closed_issues2.981
issue_closed_ratio0,693
closed_unmerged_prs395
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
20.9/25Reichweite des Inhabers — 794 Follower von Aider-AI
10.8/25Kontohistorie — 7 öffentliche Repos, Kontoalter ca. 2 Jahre
Verwendete Eingangsdaten
followers794
owner_typeOrganization
is_verified
owner_loginAider-AI
public_repos7
account_age_days773

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 159 Tagen
20/20Versionshistorie — 174 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagesaider-chat
ecosystemspypi
any_deprecatednein
min_days_since_publish159

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

85Exzellent · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 10 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration — .flake8
9.6/9.6Pre-Commit-Hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — keine Daten
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_configja
has_precommit_configja
Wie die Bewertung erfolgt
30/30README
0/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://aider.chat/
10/10Repository-Beschreibung
10/10Topics — 13 Topics
10/10Wiki
Verwendete Eingangsdaten
topicschatgpt, cli, command-line, gpt-4, openai, gpt-3, gpt-35-turbo, claude-3, gpt-4o, anthropic, gemini, llama, sonnet
has_wikija
homepagehttps://aider.chat/
has_readmeja
has_docs_dirnein
has_descriptionja

Sicherheit

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

10Kritisch · 16 % des Gesamtindex
Wie die Bewertung erfolgt
0/30Sicherheitsrichtlinie (SECURITY.md)
0/25Dependabot-Konfiguration
0/25Lockfiles für Abhängigkeiten — veröffentlichte Bibliothek — Lockfiles sind Sache der Anwendung, hier nicht erwartet
0/20CodeQL-Workflow
Verwendete Eingangsdaten
sourcefile_signals
lockfiles
manifestspyproject.toml, requirements.txt, requirements/requirements-browser.txt, requirements/requirements-dev.txt, requirements/requirements-help.txt, requirements/requirements-playwright.txt
has_codeql_workflownein
has_security_policynein
has_dependabot_confignein
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lockfiles für Abhängigkeiten. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
2.6/35Direkte Abhängigkeiten ohne bekannte Advisories — 13 betroffen: aiohttp 3.13.3 (critical 9.1), gitpython 3.1.46 (critical 9.8), litellm 1.81.10 (critical 9.8), +10 weitere
25/25Indirekte Abhängigkeiten ohne bekannte Advisories — keine indirekte Abhängigkeit trägt ein bekanntes Advisory
18.5/40Keine offenen Advisories — 7 Paket(e) mit Advisory seit über 90 Tagen unbehandelt; ältestes vor 160 Tagen veröffentlicht
Verwendete Eingangsdaten
sourceosv
advisories131
affected_packages13
assessed_packages107
unassessed_packages0
affected_by_severitycritical 4, high 3, moderate 4, low 1, unknown 1
direct_affected_packages13
Abgeglichen wurde die Laufzeit-Abhängigkeitshülle von pypi:aider-chat@0.86.2 — das, was die Installation des veröffentlichten Pakets nach sich zieht — mit 107 Paketen. Erreichbarkeit wird nicht analysiert.

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.

61Mittel · 0 % des Gesamtindex
Wie die Bewertung erfolgt
45/45Agentenanweisungen — aider/website/docs/llms/gemini.md
0/15Maschinenlesbare Doku (llms.txt)
34.1/40Lesbare Commit-Historie — 64 von 100 menschlichen Commits benennen ihre Absicht (strukturierter Betreff oder erläuternder Text)
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share0,64
agent_instruction_filesaider/website/docs/llms/gemini.md
agent_instruction_max_bytes700
Wie die Bewertung erfolgt
0/18Bootstrap mit einem Befehl
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration — .flake8
0/11Statische Typprüfung
10/10Reproduzierbare Umgebung — Dockerfile
10/10Belegte Agentenpraxis — 34 der letzten 100 Commits von Agenten verfasst oder ihnen zugeschrieben
0/8Automatisierte Wartung — keine automatisierten Abhängigkeits-Updates beobachtet
0/10OpenSSF Scorecard: Pinned-Dependencies — keine Daten
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfiles
has_dockerfileja
typed_languagenein
bootstrap_files
has_devcontainernein
has_linter_configja
typecheck_configs
agent_commit_share0,34
toolchain_manifests
dependency_bot_commit_share0
Wie die Bewertung erfolgt
0/45Typprüfbarer Code — Python ohne Typprüfungs-Konfiguration
53.4/55Handhabbare Dateigrößen — 5/175 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes193.531
source_files_sampled175
oversized_source_files5
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

47.589GitHub-Sterne
100Mitwirkende
182Commits, letzte 12 Monate
60Tage seit letztem Push
93Releases
1Bus-Faktor
1.320offene Issues
PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • Advisory severity resolved for 120 of 131 advisories (lookup cap); the remainder are reported as unknown severity
  • OpenSSF Scorecard did not return a usable result (2026/07/21 23:05:57 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

Weitere Details

Stern- und Fork-Verlauf 47.589 ★ / 4.746 ⇿
47.589Sterne
4.746Forks

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.

Es wird nur die jüngste Historie angezeigt — dieses Repository überschreitet das Erfassungsfenster, sodass die früheste Historie nicht erfasst wird.

010.00020.00030.00040.00050.00047.5894.746512026-022026-042026-07
Alle Abhängigkeiten 210

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 210 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPIaiohappyeyeballs2.6.1indirekt
PyPIaiohttp3.13.3indirekt
PyPIaiosignal1.4.0indirekt
PyPIaiosqlite0.22.1indirekt
PyPIaltair6.0.0indirekt
PyPIannotated-doc0.0.4indirekt
PyPIannotated-types0.7.0indirekt
PyPIanyio4.12.1indirekt
PyPIasgiref3.11.1indirekt
PyPIattrs25.4.0indirekt
PyPIaudioop-ltsindirekt
PyPIbackoff2.2.1indirekt
PyPIbanks2.4.1indirekt
PyPIbeautifulsoup44.14.3indirekt
PyPIblinker1.9.0indirekt
PyPIbuild1.4.0indirekt
PyPIcachetools7.0.5indirekt
PyPIcertifi2026.2.25indirekt
PyPIcffi2.0.0indirekt
PyPIcfgv3.5.0indirekt
PyPIcharset-normalizer3.4.6indirekt
PyPIclick8.3.1indirekt
PyPIcodespell2.4.2indirekt
PyPIcogapp3.6.0indirekt
PyPIcolorama0.4.6indirekt
PyPIconfigargparse1.7.5indirekt
PyPIcontourpy1.3.3indirekt
PyPIcoverage7.13.4indirekt
PyPIcryptography46.0.5indirekt
PyPIcycler0.12.1indirekt
PyPIdataclasses-json0.6.7indirekt
PyPIdeprecated1.3.1indirekt
PyPIdiff-match-patch20241021indirekt
PyPIdirtyjson1.0.8indirekt
PyPIdiskcache5.6.3indirekt
PyPIdistlib0.4.0indirekt
PyPIdistro1.9.0indirekt
PyPIfastapi0.135.1indirekt
PyPIfastuuid0.14.0indirekt
PyPIfilelock3.25.2indirekt
PyPIfiletype1.2.0indirekt
PyPIflake87.3.0indirekt
PyPIfonttools4.62.1indirekt
PyPIfrozenlist1.8.0indirekt
PyPIfsspec2026.2.0indirekt
PyPIgitdb4.0.12indirekt
PyPIgitpython3.1.46indirekt
PyPIgoogle-api-core2.30.0indirekt
PyPIgoogle-auth2.49.1indirekt
PyPIgoogle-cloud-bigquery3.40.1indirekt
PyPIgoogle-cloud-core2.5.0indirekt
PyPIgoogle-crc32c1.8.0indirekt
PyPIgoogle-resumable-media2.8.0indirekt
PyPIgoogleapis-common-protos1.73.0indirekt
PyPIgreenlet3.3.2indirekt
PyPIgrep-ast0.9.0indirekt
PyPIgriffe2.0.0indirekt
PyPIgriffecli2.0.0indirekt
PyPIgriffelib2.0.0indirekt
PyPIgrpcio1.78.0indirekt
PyPIgrpcio-status1.78.0indirekt
PyPIh110.16.0indirekt
PyPIhf-xet1.4.2indirekt
PyPIhttpcore1.0.9indirekt
PyPIhttpx0.28.1indirekt
PyPIhuggingface-hub1.7.1indirekt
PyPIidentify2.6.18indirekt
PyPIidna3.11indirekt
PyPIimgcat0.6.0indirekt
PyPIimportlib-metadata7.2.1indirekt
PyPIimportlib-resources6.5.2indirekt
PyPIiniconfig2.3.0indirekt
PyPIjinja23.1.6indirekt
PyPIjiter0.13.0indirekt
PyPIjoblib1.5.3indirekt
PyPIjson50.13.0indirekt
PyPIjsonschema4.26.0indirekt
PyPIjsonschema-specifications2025.9.1indirekt
PyPIkiwisolver1.5.0indirekt
PyPIlitellm1.82.3indirekt
PyPIllama-index-core0.14.18indirekt
PyPIllama-index-embeddings-huggingface0.7.0indirekt
PyPIllama-index-instrumentation0.5.0indirekt
PyPIllama-index-workflows2.16.1indirekt
PyPIlox1.0.0indirekt
PyPImarkdown-it-py4.0.0indirekt
PyPImarkupsafe3.0.3indirekt
PyPImarshmallow3.26.2indirekt
PyPImatplotlib3.10.8indirekt
PyPImccabe0.7.0indirekt
PyPImdurl0.1.2indirekt
PyPImixpanel5.0.0indirekt
PyPImpmath1.3.0indirekt
PyPImslex1.3.0indirekt
PyPImultidict6.7.1indirekt
PyPImypy-extensions1.1.0indirekt
PyPInarwhals2.18.0indirekt
PyPInest-asyncio1.6.0indirekt
PyPInetworkx3.4.2indirekt
PyPInltk3.9.3indirekt
PyPInodeenv1.10.0indirekt
PyPInumpyindirekt
PyPInumpy2.4.3indirekt
PyPIopenai2.28.0indirekt
PyPIorjson3.11.7indirekt
PyPIoslex0.1.3indirekt
PyPIpackaging26.0indirekt
PyPIpandas2.3.3indirekt
PyPIpathspec1.0.4indirekt
PyPIpexpect4.9.0indirekt
PyPIpillow12.1.1indirekt
PyPIpip26.0.1indirekt
PyPIpip-tools7.5.3indirekt
PyPIplatformdirs4.9.4indirekt
PyPIplaywright1.58.0indirekt
PyPIpluggy1.6.0indirekt
PyPIposthog7.9.12indirekt
PyPIpre-commit4.5.1indirekt
PyPIprompt-toolkit3.0.52indirekt
PyPIpropcache0.4.1indirekt
PyPIproto-plus1.27.1indirekt
PyPIprotobuf6.33.5indirekt
PyPIpsutil7.2.2indirekt
PyPIptyprocess0.7.0indirekt
PyPIpyarrow23.0.1indirekt
PyPIpyasn10.6.2indirekt
PyPIpyasn1-modules0.4.2indirekt
PyPIpycodestyle2.14.0indirekt
PyPIpycparser3.0indirekt
PyPIpydantic2.12.5indirekt
PyPIpydantic-core2.41.5indirekt
PyPIpydeck0.9.1indirekt
PyPIpydub0.25.1indirekt
PyPIpyee13.0.1indirekt
PyPIpyflakes3.4.0indirekt
PyPIpygments2.19.2indirekt
PyPIpypandoc1.17indirekt
PyPIpyparsing3.3.2indirekt
PyPIpyperclip1.11.0indirekt
PyPIpyproject-hooks1.2.0indirekt
PyPIpytest9.0.2indirekt
PyPIpytest-cov7.0.0indirekt
PyPIpytest-env1.6.0indirekt
PyPIpython-dateutil2.9.0.post0indirekt
PyPIpython-discovery1.1.3indirekt
PyPIpython-dotenv1.2.2indirekt
PyPIpytz2026.1.post1indirekt
PyPIpyyaml6.0.3indirekt
PyPIreferencing0.37.0indirekt
PyPIregex2026.2.28indirekt
PyPIrequests2.32.5indirekt
PyPIrich14.3.3indirekt
PyPIrpds-py0.30.0indirekt
PyPIsafetensors0.7.0indirekt
PyPIscikit-learn1.8.0indirekt
PyPIscipyindirekt
PyPIscipy1.17.1indirekt
PyPIsemver3.0.4indirekt
PyPIsentence-transformers5.3.0indirekt
PyPIsetuptools82.0.1indirekt
PyPIshellingham1.5.4indirekt
PyPIshtab1.8.0indirekt
PyPIsix1.17.0indirekt
PyPIsmmap5.0.3indirekt
PyPIsniffio1.3.1indirekt
PyPIsocksio1.0.0indirekt
PyPIsounddevice0.5.5indirekt
PyPIsoundfile0.13.1indirekt
PyPIsoupsieve2.8.3indirekt
PyPIsqlalchemy2.0.48indirekt
PyPIstarlette0.52.1indirekt
PyPIstreamlit1.55.0indirekt
PyPIsympy1.14.0indirekt
PyPItenacity9.1.4indirekt
PyPIthreadpoolctl3.6.0indirekt
PyPItiktoken0.12.0indirekt
PyPItinytag2.2.1indirekt
PyPItokenizers0.22.2indirekt
PyPItoml0.10.2indirekt
PyPItorch2.10.0indirekt
PyPItornado6.5.5indirekt
PyPItqdm4.67.3indirekt
PyPItransformers5.3.0indirekt
PyPItree-sitter0.23.2indirekt
PyPItree-sitter0.25.2indirekt
PyPItree-sitter-c-sharp0.23.1indirekt
PyPItree-sitter-embedded-template0.25.0indirekt
PyPItree-sitter-language-pack0.13.0indirekt
PyPItree-sitter-yaml0.7.2indirekt
PyPItyper0.24.1indirekt
PyPItyping-extensions4.15.0indirekt
PyPItyping-inspect0.9.0indirekt
PyPItyping-inspection0.4.2indirekt
PyPItzdata2025.3indirekt
PyPIurllib32.6.3indirekt
PyPIuv0.10.11indirekt
PyPIvirtualenv21.2.0indirekt
PyPIwatchfiles1.1.1indirekt
PyPIwcwidth0.6.0indirekt
PyPIwheel0.46.3indirekt
PyPIwrapt2.1.2indirekt
PyPIyarl1.23.0indirekt
PyPIzipp3.23.0indirekt
RubyGemsgithub-pagesindirekt
RubyGemshtml-prooferindirekt
RubyGemsjekyllindirekt
RubyGemsjekyll-redirect-fromindirekt
RubyGemsjekyll-sitemapindirekt
RubyGemsjust-the-docs0.8.2indirekt
RubyGemswebrickindirekt
Abhängigkeits-Advisories 13

Die Installation von pypi:aider-chat@0.86.2 zieht 107 Pakete nach sich, direkt und transitiv: 13 tragen bekannte Advisories, davon 13 direkte Abhängigkeiten.

PaketVersionBeziehungSchweregradAdvisoriesBehoben in
aiohttp3.13.3direktkritisch423.14.1
gitpython3.1.46direktkritisch123.1.52
litellm1.81.10direktkritisch171.84.0
pillow12.1.1direktkritisch3112.3.0
click8.3.1direkthoch18.3.3
soupsieve2.8.3direkthoch42.8.4
starlette0.52.1direkthoch101.3.1
diskcache5.6.3direktmittel2
idna3.11.0direktmittel23.15
python-dotenv1.2.1direktmittel21.2.2
requests2.32.5direktmittel22.33.0
pygments2.19.2direktniedrig22.20.0
urllib32.6.3direktunbekannt4

Ein Advisory bedeutet, dass die im Abhängigkeitsgraphen erfasste Version in den betroffenen Bereich eines Advisories fällt. Erreichbarkeit wird nicht analysiert, und der Graph enthält Entwicklungs- und Test-Pins — ein Fund kann das Werkzeug betreffen und nicht die ausgelieferte Software.

JSON-Rohbericht maschinenlesbar
{
  "data": {
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                    "params": {
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                      "packages": "aiohttp 3.13.3 (critical 9.1), gitpython 3.1.46 (critical 9.8), litellm 1.81.10 (critical 9.8)"
                    }
                  },
                  {
                    "code": "advisories_affected_more",
                    "params": {
                      "count": 10
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                  }
                ],
                "max_points": 35
              },
              {
                "key": "indirect_dependencies_free_of_known_advisories",
                "name": "Indirect dependencies free of known advisories",
                "detail": "no indirect dependency carries a known advisory",
                "points": 25,
                "status": "met",
                "details": [
                  {
                    "code": "no_indirect_advisories",
                    "params": {}
                  }
                ],
                "max_points": 25
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              {
                "key": "no_advisories_left_outstanding",
                "name": "No advisories left outstanding",
                "detail": "7 advisory-carrying package(s) unaddressed past 90 days; oldest published 160 days ago",
                "points": 18.5,
                "status": "partial",
                "details": [
                  {
                    "code": "advisories_stale",
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                ],
                "max_points": 40
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          },
          {
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            "band": "excellent",
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            "note": null,
            "notes": [],
            "value": 100,
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              "packages": [],
              "red_flag": false,
              "assessed_packages": 107,
              "malicious_packages": 0,
              "direct_malicious_packages": 0,
              "withdrawn_malicious_packages": 0,
              "installable_malicious_packages": 0
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            "components": [
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                "name": "No dependency reported as a malicious package",
                "detail": "no dependency is reported as a malicious package",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "no_malicious_dependencies",
                    "params": {}
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                "max_points": 100
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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",
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            "inputs": {
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              "red_flag": false,
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              "review_only_matches": 0,
              "assessed_self_published_locations": 13
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            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
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                "points": 100,
                "status": "met",
                "details": [
                  {
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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": "moderate",
        "name": "AI Readiness",
        "value": 61,
        "weight": 0,
        "metrics": [
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            "name": "Agent context & guidance",
            "note": null,
            "notes": [],
            "value": 79,
            "inputs": {
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                "name": "Agent instructions",
                "detail": "aider/website/docs/llms/gemini.md",
                "points": 45,
                "status": "met",
                "details": [
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                "max_points": 45
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              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
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              {
                "key": "legible_commit_history",
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                "detail": "64 of 100 human commits state their intent (structured subject or explanatory body)",
                "points": 34.1,
                "status": "partial",
                "details": [
                  {
                    "code": "legible_history",
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                      "sampled": 100
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                "max_points": 40
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          },
          {
            "key": "ai_verify_loop",
            "band": "moderate",
            "name": "Verify loop (build / test / typecheck)",
            "note": null,
            "notes": [],
            "value": 59,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [],
              "has_dockerfile": true,
              "typed_language": false,
              "bootstrap_files": [],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [],
              "agent_commit_share": 0.34,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 18
              },
              {
                "key": "automated_tests",
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                "detail": null,
                "points": 22,
                "status": "met",
                "details": [],
                "max_points": 22
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              {
                "key": "lint_format_config",
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                "detail": ".flake8",
                "points": 11,
                "status": "met",
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                "max_points": 11
              },
              {
                "key": "static_type_checking",
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                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": "Dockerfile",
                "points": 10,
                "status": "met",
                "details": [
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                    "code": "file_list",
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                      "files": "Dockerfile"
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                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "34 of the last 100 commits agent-authored or agent-credited",
                "points": 10,
                "status": "met",
                "details": [
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                    "code": "agent_authored_commits",
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                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "no automated dependency updates observed",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_dependency_automation",
                    "params": {}
                  }
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                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "OpenSSF Scorecard unavailable",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
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                ],
                "max_points": 10
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            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "moderate",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 53,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 193531,
              "source_files_sampled": 175,
              "oversized_source_files": 5
            },
            "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": "5/175 source files over 60KB",
                "points": 53.4,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 175,
                      "oversized": 5
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                "max_points": 55
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          },
          {
            "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"
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                ],
                "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": [
    "Advisory severity resolved for 120 of 131 advisories (lookup cap); the remainder are reported as unknown severity",
    "OpenSSF Scorecard did not return a usable result (2026/07/21 23:05:57 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-21T23:06:32.802197Z",
  "schema_version": "0.25.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/a/Aider-AI/aider.svg",
  "full_name": "Aider-AI/aider",
  "license_state": "standard",
  "license_spdx": "Apache-2.0"
}

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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 v0.25.0 — vollständige Methodik · Metriken-Wiki.

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