Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-13 03:38 UTC

seruva19 / ayase

Modular media quality metrics toolkit.

PythonMIT★ 2 stars⑂ 0 forkssince Mar 2026View on GitHub ↗
KindCommand-line toolLibraryTerminal interfacehow this is determined

seruva19/ayase holds a health index of 9 out of 100, placing it in the Critical band. It scores highest on Engineering Quality (85/100) and lowest on Security (1/100). It was last updated 5 days ago. A single contributor accounts for most of its recent work.

9
overall / 100
Critical

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

9
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 46 is calibrated to 44 on the published index scale (record calibration 2026-08-02). High-Risk Jurisdiction Policy applies a 20% multiplier to weighted overall health and gives it an At Risk ceiling of 34.

Ownership

seruva19Personal account
31 followers11 public repossince Mar 2017

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIayase0.1.76818745 days agoaicomputer-visiondatasetimagemetricsmlquality-assessmentvideovqa

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

45Weak · 21% of overall

Development activity

75Good
How it's scored
36/36Push recency — last push 5 days ago
13.8/36Commit cadence — 20/52 weeks with commits
18/18Commit volume — 228 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year228
human_commit_share1
days_since_last_push5
active_weeks_last_year20

Release discipline

1Critical
How it's scored
0/27Ships releases — no releases published
0/36Release recency — no releases
0/27Release cadence — no releases
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count0

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

37Weak · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 2 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars2
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

70Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Ecosystem adoption (downloads)

48Weak
How it's scored
38.8/80Monthly downloads — 818 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesayase
dependents—
ecosystemspypi
total_downloads—
monthly_downloads818
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

48Weak · 23% of overall

Maintainer resilience (bus factor)

12Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0/22.5Commit distribution — top contributor authored 100% of commits
1.4/13.5Contributor breadth — 1 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1

Ownership & stewardship

51Moderate
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
10.8/25Owner reach — 31 followers of seruva19
19.9/25Track record — 11 public repos, account ~9 yr old
Inputs used
followers31
owner_typeUser
is_verified—
owner_loginseruva19
public_repos11
account_age_days3,452
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 5 days ago
20/20Version history — 74 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesayase
ecosystemspypi
any_deprecatedno
min_days_since_publish5

Engineering Quality

Are baseline engineering and documentation practices in place?

85Excellent · 19% of overall

Engineering practices

92Excellent
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff], [tool.black])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

75Good
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

1Critical · 16% of overall

Security posture

1Critical
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestspyproject.toml
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
high_risk_jurisdiction_cap34
high_risk_jurisdiction_multiplier20
security_posture_after_multiplier1
security_posture_before_jurisdiction1
High-Risk Jurisdiction Policy applies a 20% multiplier and gives Security posture an At risk ceiling of 34.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

75Good · 4% of overall

Agent context & guidance

78Good
How it's scored
45/45Agent instructions — AGENTS.md
0/15Machine-readable docs (llms.txt)
33.1/40Legible commit history — 62 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.62
agent_instruction_filesAGENTS.md
agent_instruction_max_bytes27,045

Verify loop (build / test / typecheck)

60Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff], [tool.black])
11/11Static type checking — src/ayase/py.typed
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configssrc/ayase/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (src/ayase/py.typed)
54.7/55Manageable file sizes — 4/870 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes101,418
source_files_sampled870
oversized_source_files4

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples, sample
Inputs used
example_dirsexamples, sample
has_mcp_signalno
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

2GitHub stars
1contributors
228commits, last 12 months
5days since last push
0releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit; 2026/09/13 03:37:53 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

More detail

Direct dependencies 81
RegistryPackageVersion constraintManifest
PyPItyper>=0.12.0,<1.0pyproject.toml
PyPIrich>=13.7.0,<15.0pyproject.toml
PyPIpydantic>=2.5.0,<3.0pyproject.toml
PyPIpydantic-settings>=2.1.0,<3.0pyproject.toml
PyPIopencv-python>=4.9.0,<5.0pyproject.toml
PyPIpillow>=10.2.0,<13.0pyproject.toml
PyPInumpy>=1.24.0,<3.0pyproject.toml
PyPItqdm>=4.66.0,<5.0pyproject.toml
PyPIpyarrow>=15.0.0,<23.0pyproject.toml
PyPIpandas>=2.1.0,<3.0pyproject.toml
PyPIimageio>=2.33.0,<3.0pyproject.toml
PyPIimageio-ffmpeg>=0.4.9,<1.0pyproject.toml
PyPItextual>=0.52.0pyproject.toml
PyPItorch>=2.1.0,<2.11pyproject.toml
PyPItorchvision>=0.16.0,<0.26pyproject.toml
PyPItorchaudio>=2.1.0,<2.11pyproject.toml
PyPItransformers>=4.45.0,<5.0pyproject.toml
PyPIqwen-vl-utils>=0.0.8pyproject.toml
PyPIhuggingface-hub>=0.20.0,<2.0pyproject.toml
PyPIsafetensors>=0.4.0pyproject.toml
PyPItimm>=0.9.12pyproject.toml
PyPIeinops>=0.8.1pyproject.toml
PyPIeinops-exts>=0.0.4,<0.1pyproject.toml
PyPIgeomloss>=0.2.6,<1.0pyproject.toml
PyPIpeft>=0.2.0,<1.0pyproject.toml
PyPIftfy>=6.0pyproject.toml
PyPIregex>=2024.0.0pyproject.toml
PyPIiopath>=0.1.10,<0.2pyproject.toml
PyPIpytorchvideo>=0.1.5,<0.2pyproject.toml
PyPIlpips>=0.1.4pyproject.toml
PyPIopen-clip-torch>=2.24.0pyproject.toml
PyPIpyiqa>=0.1.13,<1.0pyproject.toml
PyPIscipy>=1.11.0pyproject.toml
PyPIscikit-image>=0.19.0pyproject.toml
PyPIscikit-video>=1.1.11pyproject.toml
PyPIdecord>=0.6.0pyproject.toml
PyPIvebench==1.0.0pyproject.toml
PyPIv-stream>=0.1.2pyproject.toml
PyPIprdc>=0.2pyproject.toml
PyPIscikit-learn>=1.3.0pyproject.toml
PyPIjoblib>=1.3.0pyproject.toml
PyPInumba>=0.58.0pyproject.toml
PyPImatplotlib>=3.7.0pyproject.toml
PyPIcolour-science>=0.4.0pyproject.toml
PyPIPyWavelets>=1.3.0pyproject.toml
PyPIpyrtools>=1.0.9pyproject.toml
PyPIcvvdp>=0.5.6,<0.6pyproject.toml
PyPIPyYAML>=6.0pyproject.toml
PyPIrequests>=2.31.0pyproject.toml
PyPIscenedetect>=0.6.5,<1.0pyproject.toml
PyPIomegaconf>=2.3.0pyproject.toml
PyPInltk>=3.8.0pyproject.toml
PyPIaccelerate>=0.25.0pyproject.toml
PyPIdiffusers>=0.25.0pyproject.toml
PyPIpaddlepaddle>=3.0pyproject.toml
PyPIpaddleocr>=3.0pyproject.toml
PyPIpython-Levenshtein>=0.21.0pyproject.toml
PyPIfaster-whisper>=1.2.0,<2.0pyproject.toml
PyPImsclap>=1.3.4,<2.0pyproject.toml
PyPIaudiobox_aesthetics>=0.0.4,<0.1.0pyproject.toml
PyPImediapipe>=0.10.0,<1.0pyproject.toml
PyPIrtmlib>=0.0.13pyproject.toml
PyPIinsightface>=0.7.0pyproject.toml
PyPIonnxruntime>=1.14.0pyproject.toml
PyPIultralytics>=8.0.0,<9.0pyproject.toml
PyPIinvisible-watermark>=0.2.0pyproject.toml
PyPIlibrosa>=0.10.1,<0.11pyproject.toml
PyPImuq>=0.1.0pyproject.toml
PyPImoviepy>=1.0.3,<2.0pyproject.toml
PyPIpyloudnorm>=0.1.1,<1.0pyproject.toml
PyPIpython_speech_features>=0.6,<1.0pyproject.toml
PyPIsoundfile>=0.12.0pyproject.toml
PyPIsilero-vad>=6.0.0,<7.0pyproject.toml
PyPItorchmetrics>=1.0.0pyproject.toml
PyPItransnetv2-pytorch>=1.0.0pyproject.toml
PyPIumap-learn>=0.5.0pyproject.toml
PyPIwget>=3.2,<4.0pyproject.toml
PyPIsetuptools>=69,<70pyproject.toml
PyPItomli>=2.0.1,<3.0pyproject.toml
PyPItomli-w>=1.0.0,<2.0pyproject.toml
PyPItyping_extensions>=4.0.0pyproject.toml
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

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Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.