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Software-GesundheitsberichtSchema 0.11.0 · Metriken 1.13.0 · 2026-07-16 23:56 UTC

openai / tiktoken

tiktoken is a fast BPE tokeniser for use with OpenAI's models.

Python · RustMIT★ 18.758 Sterne⑂ 1.548 Forksseit Dez. 2022Auf GitHub ansehen ↗

openai/tiktoken erreicht einen Gesundheitsindex von 59 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Community & Adoption (76/100) ab, am schwächsten bei AI Readiness (37/100). Zuletzt vor 53 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.

59
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.

59
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

OpenAIOrganisation
126.529 Follower264 öffentliche Reposseit Okt. 2015

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

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlichtTags
crates.iotiktokenverweist auf ein anderes Repo — nicht bewertet3.5.14.26915vor 39 Tagenbpegptopenaitiktokentokenizeralgorithmstext-processing
PyPItiktoken0.13.0-19vor 62 Tagen

Metriken nach Kategorie

Vitalität

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

60Mittel · 22 % des Gesamtindex
Wie die Bewertung erfolgt
18/36Push-Aktualität — letzter Push vor 53 Tagen
6.2/36Commit-Rhythmus — 9/52 Wochen mit Commits
10.6/18Commit-Volumen — 14 Commits im letzten Jahr
4/10OpenSSF Scorecard: Maintained — 2 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 4
Verwendete Eingangsdaten
commits_last_year14
human_commit_share
days_since_last_push53
active_weeks_last_year9
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 14 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 62 Tagen
19.8/27Release-Rhythmus — ein Release etwa alle 108,5 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count14
latest_release_tag0.13.0
releases_from_tagsnein
days_since_latest_release62
mean_days_between_releases108,5
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: Signed-Releases. Die verbleibenden Gewichte wurden renormalisiert.

Community & Verbreitung

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

76Gut · 18 % des Gesamtindex
Wie die Bewertung erfolgt
60/60Stars — 18.758 Stars
25/25Forks — 1.548 Forks
12.8/15Watcher — 201 Watcher
Verwendete Eingangsdaten
forks1.548
stars18.758
watchers201
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (MIT)
0/18CONTRIBUTING-Leitfaden
0/13.5Verhaltenskodex
0/7.2Issue-Vorlage
0/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingnein
has_issue_templatenein
has_code_of_conductnein
has_pull_request_templatenein

Nachhaltigkeit & Governance

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

63Mittel · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
7.6/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 66 % der Commits
13.5/13.5Breite der Beitragenden — 22 Beitragende
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Verwendete Eingangsdaten
bus_factor1
contributors_sampled22
top_contributor_share0,662
Wie die Bewertung erfolgt
38.3/46.8Issue-Lösungsquote — 82 % der Issues geschlossen
11/38.3PR-Annahme — 36/125 entschiedene PRs gemergt
4.5/15OpenSSF Scorecard: Code-Review — Found 10/30 approved changesets -- score normalized to 3
Verwendete Eingangsdaten
merged_prs36
open_issues60
closed_issues274
issue_closed_ratio0,82
closed_unmerged_prs89
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
25/25Reichweite des Inhabers — 126.529 Follower von openai
25/25Kontohistorie — 264 öffentliche Repos, Kontoalter ca. 10 Jahre
Verwendete Eingangsdaten
followers126.529
owner_typeOrganization
is_verified
owner_loginopenai
public_repos264
account_age_days3.939

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 62 Tagen
20/20Versionshistorie — 19 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagestiktoken
ecosystemspypi
any_deprecatednein
min_days_since_publish62

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

52Mittel · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 1 Workflow(s)
24/24Tests vorhanden
0/16Linter-Konfiguration
0/9.6Pre-Commit-Hooks
0/6.4.editorconfig
6/20OpenSSF Scorecard: CI-Tests — 7 out of 18 merged PRs checked by a CI test -- score normalized to 3
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
0/10Topics
10/10Wiki
Verwendete Eingangsdaten
topics
has_wikija
homepage
has_readmeja
has_docs_dirnein
has_descriptionja

Sicherheit

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

44Gefährdet · 16 % des Gesamtindex

Sicherheitslage

44Gefährdet
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — keine Daten
0.8/2.5CI-Tests — 7 out of 18 merged PRs checked by a CI test -- score normalized to 3
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
2.2/7.5Code-Review — Found 10/30 approved changesets -- score normalized to 3
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
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
3/7.5Maintained — 2 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 4
0/5Packaging — keine Daten
3/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 6
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — keine Daten
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate4,4
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection, packaging, 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.

37Gefährdet · 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
11/11Statische Typprüfung — tiktoken/py.typed
0/10Reproduzierbare Umgebung
0/10Belegte Agentenpraxis — keine Daten
0/8Automatisierte Wartung — keine Daten
6/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 6
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfiles
has_dockerfilenein
typed_languagenein
bootstrap_files
has_devcontainernein
has_linter_confignein
typecheck_configstiktoken/py.typed
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
27/45Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (tiktoken/py.typed)
55/55Handhabbare Dateigrößen — 0/20 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes26.068
source_files_sampled20
oversized_source_files0

Eckdaten

18.758GitHub-Sterne
22Mitwirkende
14Commits, letzte 12 Monate
53Tage seit letztem Push
14Releases
1Bus-Faktor
60offene Issues
crates.io, PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • crates package 'tiktoken' points at a different repository (https://github.com/goliajp/rust-tiktoken); excluded from ecosystem scoring

Weitere Details

OpenSSF Scorecard 4.4 / 10
4.4Gesamtwert

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 · 2026-07-16 23:56 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
3CI-Tests7 out of 18 merged PRs checked by a CI test -- score normalized to 3
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 10/30 approved changesets -- score normalized to 3
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
4Maintained2 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 4
k. A.Packagingpackaging workflow not detected
6Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 6
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
k. A.Signed-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direkte Abhängigkeiten 7
RegistryPaketVersionsvorgabeManifest
crates.iopyo30.28.3Cargo.toml
crates.iofancy-regex0.17.0Cargo.toml
crates.ioregex1.10.3Cargo.toml
crates.iorustc-hash2Cargo.toml
crates.iobstr1.5.0Cargo.toml
PyPIregexpyproject.toml
PyPIrequestspyproject.toml
Alle Abhängigkeiten 8

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 5 direkte und 3 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
crates.iobstrdirekt
crates.iofancy-regexdirekt
crates.iopyo3direkt
crates.ioregexdirekt
crates.iorustc-hashdirekt
PyPIblobfileindirekt
PyPIsetuptoolsindirekt
PyPIsetuptools-rustindirekt
JSON-Rohbericht maschinenlesbar
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                "points": 24,
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                "details": [],
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              },
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                "key": "openssf_scorecard_ci_tests",
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            ]
          },
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          }
        ],
        "description": "Are baseline engineering and documentation practices in place?"
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      {
        "key": "security",
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        "weight": 0.16,
        "metrics": [
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                "key": "binary_artifacts",
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                "details": [],
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              },
              {
                "key": "branch_protection",
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                "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,
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                "key": "code_review",
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                "details": [],
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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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                "details": [],
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              {
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                "details": [
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                "max_points": 5
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                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 6",
                "points": 3,
                "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",
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                "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": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
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                "points": 7.5,
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            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
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            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
                "params": {}
              }
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              "policy_countries": [
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                "Iran",
                "North Korea"
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              "assessed_self_published_locations": 5
            },
            "components": [
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                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
                "detail": "no confirmed policy-scope location match",
                "points": 100,
                "status": "met",
                "details": [
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                    "code": "jurisdiction_no_match",
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                  }
                ],
                "max_points": 100
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            ]
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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": "at_risk",
        "name": "AI Readiness",
        "value": 37,
        "weight": 0,
        "metrics": [
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            "key": "ai_agent_context",
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            "name": "Agent context & guidance",
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            "notes": [
              {
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                "params": {
                  "components": [
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              },
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                "code": "weights_renormalized",
                "params": {}
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            "inputs": {
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              "agent_instruction_max_bytes": null
            },
            "components": [
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                "key": "agent_instructions",
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                "detail": "no CLAUDE.md / AGENTS.md / editor rules",
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                "status": "missed",
                "details": [
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                "key": "machine_readable_docs_llms_txt",
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                    "params": {}
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                "max_points": 40
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            ]
          },
          {
            "key": "ai_verify_loop",
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            "notes": [
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                "code": "excluded_no_data",
                "params": {
                  "components": [
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              "toolchain_manifests": [],
              "dependency_bot_commit_share": null
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            "components": [
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                "key": "one_command_bootstrap",
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              {
                "key": "automated_tests",
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              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
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                "status": "excluded",
                "details": [
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                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
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                "details": [
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                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
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            ]
          },
          {
            "key": "ai_code_legibility",
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            "name": "Code legibility for models",
            "note": null,
            "notes": [],
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            },
            "components": [
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                "name": "Type-checkable code",
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                "details": [
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                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "0/20 source files over 60KB",
                "points": 55,
                "status": "met",
                "details": [
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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."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [
    "crates package 'tiktoken' points at a different repository (https://github.com/goliajp/rust-tiktoken); excluded from ecosystem scoring"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-16T23:56:39.252184Z",
  "schema_version": "0.11.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/o/openai/tiktoken.svg",
  "full_name": "openai/tiktoken",
  "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 v0.11.0 — vollständige Methodik · Metriken-Wiki.

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