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Software-GesundheitsberichtSchema 0.9.0 · Metriken 1.13.0 · 2026-07-13 20:33 UTC

ohdearquant / lattice

Run, quantize, and fine-tune LLMs on Apple Silicon. Pure Rust, no Python, no CUDA, no ONNX

RustApache-2.0★ 31 Sterne⑂ 4 Forksseit Mai 2026Auf GitHub ansehen ↗

ohdearquant/lattice erreicht einen Gesundheitsindex von 56 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Engineering Quality (75/100) ab, am schwächsten bei Security (39/100). Zuletzt heute aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.

56
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.

56
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

OceanLiPersönliches Konto
103 Follower12 öffentliche Reposseit Jan. 2023

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

Metriken nach Kategorie

Vitalität

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

71Gut · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 0 Tagen
4.8/36Commit-Rhythmus — 7/52 Wochen mit Commits
18/18Commit-Volumen — 516 Commits im letzten Jahr
0/10OpenSSF Scorecard: Maintained — project was created within the last 90 days. Please review its contents carefully
Verwendete Eingangsdaten
commits_last_year516
human_commit_share
days_since_last_push0
active_weeks_last_year7
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 14 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 0 Tagen
27/27Release-Rhythmus — ein Release etwa alle 5,4 Tage
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Verwendete Eingangsdaten
releases_count14
latest_release_tagv0.6.1
releases_from_tagsnein
days_since_latest_release0
mean_days_between_releases5,4

Community & Verbreitung

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

51Mittel · 18 % des Gesamtindex
Wie die Bewertung erfolgt
24/60Stars — 31 Stars
4/25Forks — 4 Forks
0/15Watcher — 0 Watcher
Verwendete Eingangsdaten
forks4
stars31
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
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
6.3/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
has_issue_templatenein
has_code_of_conductnein
has_pull_request_templateja

Nachhaltigkeit & Governance

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

43Gefährdet · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
0.6/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 97 % 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_share0,974
Wie die Bewertung erfolgt
25.1/46.8Issue-Lösungsquote — 54 % der Issues geschlossen
35.3/38.3PR-Annahme — 456/494 entschiedene PRs gemergt
12/15OpenSSF Scorecard: Code-Review — Found 26/30 approved changesets -- score normalized to 8
Verwendete Eingangsdaten
merged_prs456
open_issues199
closed_issues231
issue_closed_ratio0,537
closed_unmerged_prs38
Wie die Bewertung erfolgt
10/30Organisatorische Trägerschaft — persönliches (Nutzer-)Konto
0/20Verifizierte Domain — für Nutzerkonten nicht anwendbar
14.5/25Reichweite des Inhabers — 103 Follower von ohdearquant
15.1/25Kontohistorie — 12 öffentliche Repos, Kontoalter ca. 3 Jahre
Verwendete Eingangsdaten
followers103
owner_typeUser
is_verified
owner_loginohdearquant
public_repos12
account_age_days1.274
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Verifizierte Domain. Die verbleibenden Gewichte wurden renormalisiert.

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

75Gut · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 8 Workflow(s)
24/24Tests vorhanden
0/16Linter-Konfiguration
0/9.6Pre-Commit-Hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_confignein
has_precommit_confignein

Dokumentation

85Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
0/15Dokumentations-/Homepage-Site
10/10Repository-Beschreibung
10/10Topics — 11 Topics
10/10Wiki
Verwendete Eingangsdaten
topicsapple-silicon, embeddings, fine-tuning, graphdb, inference, llm, local-llm, machine-learning, quantization, retrieval, rust
has_wikija
homepage
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

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

39Gefährdet · 16 % des Gesamtindex

Sicherheitslage

39Gefährdet
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
3/7.5Branch-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 26/30 approved changesets -- score normalized to 8
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
0/7.5Maintained — project was created within the last 90 days. Please review its contents carefully
0/5Packaging — keine Daten
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
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 — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate3,9
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): packaging. 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.

68Mittel · 0 % des Gesamtindex
Wie die Bewertung erfolgt
45/45Agentenanweisungen — AGENTS.md, CLAUDE.md
0/15Maschinenlesbare Doku (llms.txt)
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes16.983
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lesbare Commit-Historie. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
18/18Bootstrap mit einem Befehl — Makefile
22/22Automatisierte Tests
0/11Lint-/Format-Konfiguration
11/11Statische Typprüfung — Rust (statisch typisiert)
0/10Reproduzierbare Umgebung
0/10Belegte Agentenpraxis — keine Daten
0/8Automatisierte Wartung — keine Daten
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfiles
has_dockerfilenein
typed_languageja
bootstrap_filesMakefile
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
45/45Typprüfbarer Code — Rust (statisch typisiert)
50.8/55Handhabbare Dateigrößen — 35/462 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languageRust
largest_source_bytes1.670.750
source_files_sampled462
oversized_source_files35
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

31GitHub-Sterne
2Mitwirkende
516Commits, letzte 12 Monate
0Tage seit letztem Push
14Releases
1Bus-Faktor
199offene Issues
crates.io, PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • Could not fetch pypi package 'lattice-dev' from its registry

Weitere Details

OpenSSF Scorecard 3.9 / 10
3.9Gesamtwert

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 20:33 UTC

10Binary-Artifactsno binaries found in the repo
4Branch-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 26/30 approved changesets -- score normalized to 8
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
0Maintainedproject was created within the last 90 days. Please review its contents carefully
k. A.Packagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direkte Abhängigkeiten 7
RegistryPaketVersionsvorgabeManifest
PyPIpyarrow>=17.0pyproject.toml
PyPIdatasets>=3.0pyproject.toml
PyPInumpy>=1.26pyproject.toml
PyPImlx>=0.22pyproject.toml
PyPImlx-lm>=0.21pyproject.toml
PyPItransformers>=4.46pyproject.toml
PyPImatplotlib>=3.9pyproject.toml
JSON-Rohbericht maschinenlesbar
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            "score": 10,
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            "documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#license"
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          {
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          },
          {
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                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "packaging",
                "name": "Packaging",
                "detail": "packaging workflow not detected",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 5
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              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
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              {
                "key": "sast",
                "name": "SAST",
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                "status": "missed",
                "details": [],
                "max_points": 5
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              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file not detected",
                "points": 0,
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              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
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                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
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              {
                "key": "token_permissions",
                "name": "Token-Permissions",
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                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "0 existing vulnerabilities detected",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "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",
                "params": {}
              }
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            "value": 100,
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              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
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              "review_only_matches": 0,
              "assessed_self_published_locations": 2
            },
            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
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                "points": 100,
                "status": "met",
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                ],
                "max_points": 100
              }
            ]
          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
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        "name": "AI Readiness",
        "value": 68,
        "weight": 0,
        "metrics": [
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            "band": "good",
            "name": "Agent context & guidance",
            "note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
            "notes": [
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                "params": {
                  "components": [
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              "legible_history_share": null,
              "agent_instruction_files": [
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                "CLAUDE.md"
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              "agent_instruction_max_bytes": 16983
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                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "AGENTS.md, CLAUDE.md",
                "points": 45,
                "status": "met",
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                    "code": "file_list",
                    "params": {
                      "files": "AGENTS.md, CLAUDE.md"
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                "max_points": 45
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                "key": "machine_readable_docs_llms_txt",
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                "points": 0,
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                "details": [],
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                "points": 0,
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                    "code": "no_data",
                    "params": {}
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                "max_points": 40
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            ]
          },
          {
            "key": "ai_verify_loop",
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            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
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              "lockfiles": [],
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              "dependency_bot_commit_share": null
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                "max_points": 18
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              {
                "key": "automated_tests",
                "name": "Automated tests",
                "detail": null,
                "points": 22,
                "status": "met",
                "details": [],
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              },
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                "key": "lint_format_config",
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                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 11
              },
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                "points": 11,
                "status": "met",
                "details": [
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                    "code": "statically_typed_language",
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                ],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
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                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
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                    "code": "no_data",
                    "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 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
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            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "excellent",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 96,
            "inputs": {
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              "largest_source_bytes": 1670750,
              "source_files_sampled": 462,
              "oversized_source_files": 35
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            "components": [
              {
                "key": "type_checkable_code",
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                "detail": "Rust (statically typed)",
                "points": 45,
                "status": "met",
                "details": [
                  {
                    "code": "statically_typed_language",
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                ],
                "max_points": 45
              },
              {
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                "name": "Manageable file sizes",
                "detail": "35/462 source files over 60KB",
                "points": 50.8,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
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                      "sampled": 462,
                      "oversized": 35
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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": {
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              ],
              "has_mcp_signal": false,
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                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
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                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
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              },
              {
                "key": "runnable_examples",
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                "points": 40,
                "status": "met",
                "details": [
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                    "code": "file_list",
                    "params": {
                      "files": "examples"
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              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [
    "Could not fetch pypi package 'lattice-dev' from its registry"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-13T20:33:30.394943Z",
  "schema_version": "0.9.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/o/ohdearquant/lattice.svg",
  "full_name": "ohdearquant/lattice",
  "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 v0.9.0 — vollständige Methodik · Metriken-Wiki.

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