Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-11 20:29 UTC

blue-oil / blueoil

Bring Deep Learning to small devices

Python · C++Apache-2.0★ 247 stars⑂ 87 forkssince Oct 2018archivedView on GitHub ↗
KindCommand-line toolNetwork servicehow this is determined

blue-oil/blueoil holds a health index of 19 out of 100, placing it in the Critical band. It scores highest on Sustainability & Governance (73/100) and lowest on Vitality (25/100). The repository is archived, so no further maintenance is expected.

19
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.

19
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 50 is calibrated to 50 on the published index scale (record calibration 2026-08-02).

Ownership

blue-oilOrganization
1 follower2 public repossince Sep 2018

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

Metrics by category

Vitality

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

25At Risk · 21% of overall
How it's scored
0/36Push recency — last push 1,968 days ago
0/36Commit cadence — 0/52 weeks with commits
0/18Commit volume — 0 commits in the last year
0/10OpenSSF Scorecard: Maintained — project is archived
Inputs used
commits_last_year0
human_commit_share1
days_since_last_push1,968
active_weeks_last_year0
How it's scored
27/27Ships releases — 33 releases published
0/36Release recency — latest release 2,104 days ago
27/27Release cadence — a release every ~29.9 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count33
latest_release_tagv0.30.0
releases_from_tagsno
days_since_latest_release2,104
mean_days_between_releases29.9
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?

57Moderate · 17% of overall
How it's scored
38.8/60Stars — 247 stars
16.1/25Forks — 87 forks
1.7/15Watchers — 3 watchers
Inputs used
forks87
stars247
watchers3
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges1
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescircleci.com
has_pull_request_templateyes

Sustainability & Governance

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

73Good · 23% of overall
How it's scored
45.9/54Bus factor — 5 contributor(s) cover half of all commits
19.1/22.5Commit distribution — top contributor authored 15% of commits
13.5/13.5Contributor breadth — 49 contributors
10/10OpenSSF Scorecard: Contributors — project has 10 contributing companies or organizations
Inputs used
bus_factor5
contributors_sampled49
top_contributor_share0.152
How it's scored
28.8/42Issue resolution — 68% of issues closed
25.1/30PR acceptance — 684/817 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs684
open_issues123
closed_issues267
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.685
closed_unmerged_prs133
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 backing — organization-owned
0/20Verified domain
2.2/25Owner reach — 1 followers of blue-oil
15.5/25Track record — 2 public repos, account ~7 yr old
Inputs used
followers1
owner_typeOrganization
is_verifiedno
owner_loginblue-oil
public_repos2
account_age_days2,912

Engineering Quality

Are baseline engineering and documentation practices in place?

60Moderate · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
16/16Linter config — setup.cfg ([flake8])
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 30 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://blueoil.org
10/10Repository description
10/10Topics — 5 topics
0/10Wiki
Inputs used
topicsdeep-learning, machine-learning, python, quantization, fpga
has_wikino
homepagehttps://blueoil.org
docs_sitehttps://blueoil.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

31At Risk · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
0/2.5CI-Tests — 0 out of 30 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 10 contributing companies or organizations
0/10Dangerous-Workflow — no data
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
0/7.5Maintained — project is archived
0/5Packaging — no data
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 — no data
0/7.5Token-Permissions — no data
0/7.5Vulnerabilities — 67 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated13
scorecard_versionv5.5.0
checks_inconclusive5
scorecard_aggregate3
Excluded from scoring (no data or not applicable): Branch-Protection, Dangerous-Workflow, Packaging, Signed-Releases, Token-Permissions. Remaining weights renormalized.
How it's scored
4.9/35Direct dependencies free of known advisories — 4 affected: pillow 7.2. (critical 9.8), pyyaml 5.3.1 (critical 9.8), click 7.1.2 (high 7.2), +1 more
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
22.2/40No advisories left outstanding — 4 advisory-carrying package(s) unaddressed past 90 days; oldest published 4,530 days ago
Inputs used
sourceosv
advisories122
affected_packages4
assessed_packages5
unassessed_packages6
affected_by_severitycritical 2, high 1, moderate 1
direct_affected_packages4
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories. Remaining weights renormalized. Matched 5 resolved dependencies against OSV. 6 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.

51Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 98 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.98
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — Makefile, blueoil/converter/templates/Makefile, docs/Makefile
22/22Automated tests
11/11Lint / format config — setup.cfg ([flake8])
0/11Static type checking
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 — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile, blueoil/converter/templates/Makefile, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
54.7/55Manageable file sizes — 2/392 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes104,611
source_files_sampled392
oversized_source_files2
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
0/20MCP server
40/40Runnable examples — example, examples
Inputs used
example_dirsexample, examples
has_mcp_signalno
api_schema_files—
interfaces_expected_ofnetwork-service

Key facts

247GitHub stars
49contributors
0commits, last 12 months
1,968days since last push
33releases
5bus factor
123open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Could not fetch pypi package 'blueoil' from its registry

More detail

Star and fork history 0 ★ / 87 ⇿
0Stars
87Forks
33Releases

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.

0204060801008692018-102022-052025-12
Major 0Minor 30Patch 3

Each point covers 7 days.

OpenSSF Scorecard 3.0 / 10
3.0aggregate

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 · 2026-09-11 20:26 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 30 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 10 contributing companies or organizations
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintainedproject is archived
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
n/aToken-PermissionsNo tokens found
0Vulnerabilities67 existing vulnerabilities detected
Direct dependencies 10
RegistryPackageVersion constraintManifest
PyPIjinja2—setup.cfg
PyPIclick==7.1.2setup.cfg
PyPImatplotlib==3.3.0setup.cfg
PyPInumpy==1.19.1setup.cfg
PyPIPillow==8.2.0setup.cfg
PyPIprompt_toolkit==3.0.3setup.cfg
PyPIPyYAML==5.4.1setup.cfg
PyPItensorflow-datasets==1.3.0setup.cfg
PyPIinquirer==2.7.0setup.cfg
PyPIcython==0.29.21setup.cfg
All dependencies 11

Full resolved dependency set from the GitHub dependency graph: 6 direct and 5 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIclick7.1.2direct
PyPInumpy—direct
PyPInumpy1.19.1direct
PyPIpillow—direct
PyPIpillow7.2.direct
PyPIpyyaml5.3.1direct
PyPIrecommonmark—indirect
PyPIsphinx2.4.4indirect
PyPIsphinx-autoapi—indirect
PyPIsphinx-markdown-tables—indirect
PyPIsphinx-rtd-theme—indirect
Dependency advisories 4

This repository publishes no package the index resolves, so its own dependency graph was assessed — 5 packages, which also include development and test pins that never ship: 4 carry known advisories, of which 4 are direct. 6 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
pillow7.2.directcritical11727.0.0-beta.2
pyyaml5.3.1directcritical25.4
click7.1.2directhigh18.3.3
numpy1.19.1directmoderate21.22

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 statistics.