Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-19 02:23 UTC

sustainable-computing-io / kepler-model-server

Model Server for Kepler

PythonApache-2.0★ 29 stars⑂ 26 forkssince May 2022View on GitHub ↗
KindCommand-line toolNetwork servicehow this is determined

sustainable-computing-io/kepler-model-server holds a health index of 32 out of 100, placing it in the At Risk band. It scores highest on Engineering Quality (72/100) and lowest on Vitality (26/100). It was last updated 183 days ago. A single contributor accounts for most of its recent work.

32
overall / 100
At Risk

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.

32
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 53 is calibrated to 54 on the published index scale (record calibration 2026-08-02).

Ownership

243 followers37 public repossince Sep 2021

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIs3points to another repo — not scored3.0.01,65494132 days agoamazonawss3uploaddownload

Metrics by category

Vitality

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

26At Risk · 21% of overall
How it's scored
3.6/36Push recencylast push 183 days ago
0/36Commit cadence0/52 weeks with commits
0/18Commit volume0 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share0.89
days_since_last_push183
active_weeks_last_year0
How it's scored
27/27Ships releases5 releases published
7.2/36Release recencylatest release 694 days ago
19.8/27Release cadencea release every ~97.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count5
latest_release_tagv0.7.12
releases_from_tagsno
days_since_latest_release694
mean_days_between_releases97.8
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

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

56Moderate · 17% of overall
How it's scored
23.5/60Stars29 stars
11.7/25Forks26 forks
2.7/15Watchers4 watchers
Inputs used
forks26
stars29
watchers4
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateyes

Sustainability & Governance

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

59Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
9.9/22.5Commit distributiontop contributor authored 56% of commits
13.5/13.5Contributor breadth14 contributors
10/10OpenSSF Scorecard: Contributorsproject has 11 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled14
top_contributor_share0.561
How it's scored
28.5/42Issue resolution68% of issues closed
18/30PR acceptance274/457 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
13.5/15OpenSSF Scorecard: Code-ReviewFound 12/13 approved changesets -- score normalized to 9
Inputs used
merged_prs274
open_issues44
closed_issues93
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.679
closed_unmerged_prs183
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
17.2/25Owner reach243 followers of sustainable-computing-io
21.4/25Track record37 public repos, account ~4 yr old
Inputs used
followers243
owner_typeOrganization
is_verifiedno
owner_loginsustainable-computing-io
public_repos37
account_age_days1,816

Engineering Quality

Are baseline engineering and documentation practices in place?

72Good · 19% of overall
How it's scored
24/24CI workflows13 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 15 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics9 topics
10/10Wiki
Inputs used
topicsmachine-learning, model-server, stream-processing, online-machine-learning, sustainability, tensorflow, tensorflow2, prometheus, tensorflow-io
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?

52Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
0/2.5CI-Tests0 out of 15 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6.8/7.5Code-ReviewFound 12/13 approved changesets -- score normalized to 9
2.5/2.5Contributorsproject has 11 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate5.2
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.
How it's scored
10.8/35Direct dependencies free of known advisories3 affected: protobuf 5.28.2 (high 7.5), werkzeug 3.0.4 (high 7.5), flask 3.0.3 (moderate 4.3)
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
27/40No advisories left outstanding3 advisory-carrying package(s) unaddressed past 90 days; oldest published 693 days ago
Inputs used
sourceosv
advisories16
affected_packages3
assessed_packages20
unassessed_packages2
affected_by_severityhigh 2, moderate 1
direct_affected_packages3
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories. Remaining weights renormalized. Matched 20 resolved dependencies against OSV. 2 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. Reachability is not analyzed.

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.

54Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history87 of 89 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.978
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environmentDockerfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance11 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.11
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/102 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes47,980
source_files_sampled102
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
0/20MCP server
40/40Runnable examplesexamples
Inputs used
example_dirsexamples
has_mcp_signalno
api_schema_files
interfaces_expected_ofnetwork-service

Key facts

29GitHub stars
14contributors
0commits, last 12 months
183days since last push
5releases
1bus factor
44open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Could not fetch pypi package 'kepler_model' from its registry
  • pypi package 's3' points at a different repository (https://bitbucket.org/prometheus/s3/); excluded from ecosystem scoring

More detail

Star and fork history 0 ★ / 26 ⇿
0Stars
26Forks
3Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

05101520252522022-052023-062024-08
Major 0Minor 0Patch 0

Each point covers 3 days.

OpenSSF Scorecard 5.2 / 10
5.2aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-09-19 02:23 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-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
0CI-Tests0 out of 15 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
9Code-ReviewFound 12/13 approved changesets -- score normalized to 9
10Contributorsproject has 11 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging 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
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 22
RegistryPackageVersion constraintManifest
PyPIflask==3.0.3pyproject.toml
PyPIjoblib==1.4.2pyproject.toml
PyPInumpy==2.1.2pyproject.toml
PyPIpandas==2.2.3pyproject.toml
PyPIprometheus-api-client==0.5.5pyproject.toml
PyPIprometheus-client==0.21.0pyproject.toml
PyPIprotobuf==5.28.2pyproject.toml
PyPIpsutil==6.1.0pyproject.toml
PyPIpy-cpuinfo==9.0.0pyproject.toml
PyPIpyudev==0.24.3pyproject.toml
PyPIpyyaml_env_tag==0.1pyproject.toml
PyPIscikit-learn==1.5.2pyproject.toml
PyPIscipy==1.14.1pyproject.toml
PyPIseaborn==0.13.2pyproject.toml
PyPIWerkzeug==3.0.4pyproject.toml
PyPIxgboost==2.1.2pyproject.toml
PyPIboto3==1.35.43pyproject.toml
PyPIpymarkdownlnt==0.9.22pyproject.toml
PyPIyamllint==1.35.1pyproject.toml
PyPIrequests-file==2.1.0pyproject.toml
PyPIboto3model_training/s3/pyproject.toml
PyPIibm-cos-sdkmodel_training/s3/pyproject.toml
All dependencies 22

Full resolved dependency set from the GitHub dependency graph: 22 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIboto3direct
PyPIboto31.35.43direct
PyPIflask3.0.3direct
PyPIibm-cos-sdkdirect
PyPIjoblib1.4.2direct
PyPInumpy2.1.2direct
PyPIpandas2.2.3direct
PyPIprometheus-api-client0.5.5direct
PyPIprometheus-client0.21.0direct
PyPIprotobuf5.28.2direct
PyPIpsutil6.1.0direct
PyPIpy-cpuinfo9.0.0direct
PyPIpymarkdownlnt0.9.22direct
PyPIpyudev0.24.3direct
PyPIpyyaml-env-tag0.1direct
PyPIrequests-file2.1.0direct
PyPIscikit-learn1.5.2direct
PyPIscipy1.14.1direct
PyPIseaborn0.13.2direct
PyPIwerkzeug3.0.4direct
PyPIxgboost2.1.2direct
PyPIyamllint1.35.1direct
Dependency advisories 3

This repository publishes no package the index resolves, so its own dependency graph was assessed — 20 packages, which also include development and test pins that never ship: 3 carry known advisories, of which 3 are direct. 2 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
protobuf5.28.2directhigh46.33.5
werkzeug3.0.4directhigh103.1.6
flask3.0.3directmoderate23.1.3

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

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 statisticsPyPI.