Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 11:15 UTC

Bluetooth-Devices / usb-devices

Tools for mapping, describing, and resetting USB devices.

PythonMIT★ 9 stars⑂ 1 forksince Nov 2022View on GitHub ↗
KindLibraryhow this is determined

Bluetooth-Devices/usb-devices holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Engineering Quality (87/100) and lowest on Community & Adoption (54/100). It was last updated 2 days ago. A single contributor accounts for most of its recent work.

78
overall / 100
Good

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.

78
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 67 is calibrated to 78 on the published index scale (record calibration 2026-08-02).

Ownership

Bluetooth DevicesOrganization
236 followers48 public repossince Jul 2022

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIusb-devices0.5.1534,08011112 days ago

Metrics by category

Vitality

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

60Moderate · 21% of overall

Development activity

56Moderate
How it's scored
36/36Push recency — last push 2 days ago
2.8/36Commit cadence — 4/52 weeks with commits
13.8/18Commit volume — 33 commits in the last year
3/10OpenSSF Scorecard: Maintained — 4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3
Inputs used
commits_last_year33
human_commit_share0.526
days_since_last_push2
active_weeks_last_year4

Release discipline

67Good
How it's scored
27/27Ships releases — 13 releases published
27/36Release recency — latest release 112 days ago
12.6/27Release cadence — a release every ~142 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count13
latest_release_tagv0.5.1
releases_from_tagsno
days_since_latest_release112
mean_days_between_releases142

Community & Adoption

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

54Moderate · 17% of overall

Popularity & adoption

15Critical
How it's scored
14.6/60Stars — 9 stars
0/25Forks — 1 forks
0/15Watchers — 2 watchers
Inputs used
forks1
stars9
watchers2
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_badges9
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

96Exceptional
How it's scored
76.4/80Monthly downloads — 534,080 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesusb-devices
dependents—
ecosystemspypi
total_downloads—
monthly_downloads534,080
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?

70Good · 23% of overall

Maintainer resilience (bus factor)

34At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
11.2/22.5Commit distribution — top contributor authored 50% of commits
4.1/13.5Contributor breadth — 3 contributors
10/10OpenSSF Scorecard: Contributors — project has 22 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.5

Issue & PR responsiveness

91Excellent
How it's scored
42/42Issue resolution — 100% of issues closed
25.4/30PR acceptance — 77/91 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
12/15OpenSSF Scorecard: Code-Review — Found 14/17 approved changesets -- score normalized to 8
Inputs used
merged_prs77
open_issues0
closed_issues7
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio1
closed_unmerged_prs14
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.

Ownership & stewardship

68Good
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
17.1/25Owner reach — 236 followers of Bluetooth-Devices
20.6/25Track record — 48 public repos, account ~4 yr old
Inputs used
followers236
owner_typeOrganization
is_verifiedno
owner_loginBluetooth-Devices
public_repos48
account_age_days1,521

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 112 days ago
20/20Version history — 11 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesusb-devices
ecosystemspypi
any_deprecatedno
min_days_since_publish112

Engineering Quality

Are baseline engineering and documentation practices in place?

87Excellent · 19% of overall

Engineering practices

92Excellent
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
16/16Linter config — .flake8, pyproject.toml ([tool.isort])
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
12/20OpenSSF Scorecard: CI-Tests — 19 out of 28 merged PRs checked by a CI test -- score normalized to 6
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

80Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://usb-devices.readthedocs.io
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics—
has_wikino
homepage—
docs_sitehttps://usb-devices.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

62Moderate · 16% of overall

Security posture

52Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
1.5/2.5CI-Tests — 19 out of 28 merged PRs checked by a CI test -- score normalized to 6
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6/7.5Code-Review — Found 14/17 approved changesets -- score normalized to 8
2.5/2.5Contributors — project has 22 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
2.2/7.5Maintained — 4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3
5/5Packaging — packaging workflow detected
2/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
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
Inputs used
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate5.2

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages36
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 36 resolved dependencies against OSV. 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.

76Good · 4% of overall

Agent context & guidance

37Weak
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
37.3/40Legible commit history — 35 of 50 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.7
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

94Exceptional
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config — .flake8, pyproject.toml ([tool.isort])
11/11Static type checking — src/usb_devices/py.typed
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 7 of the last 95 commits agent-authored or agent-credited
8/8Automated maintenance — 26 of the last 95 commits are automated dependency updates
4/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
Inputs used
has_nixno
has_testsyes
lockfilespoetry.lock
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configssrc/usb_devices/py.typed
agent_commit_share0.074
toolchain_manifests—
dependency_bot_commit_share0.274

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (src/usb_devices/py.typed)
55/55Manageable file sizes — 0/7 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes9,467
source_files_sampled7
oversized_source_files0

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
Inputs used
example_dirsexamples
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

9GitHub stars
3contributors
33commits, last 12 months
2days since last push
13releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

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 · 2026-09-17 11:15 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
6CI-Tests19 out of 28 merged PRs checked by a CI test -- score normalized to 6
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
8Code-ReviewFound 14/17 approved changesets -- score normalized to 8
10Contributorsproject has 22 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
3Maintained4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3
10Packagingpackaging workflow detected
4Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
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
All dependencies 36

Full resolved dependency set from the GitHub dependency graph: 0 direct and 36 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIalabaster0.7.16indirect
PyPIbabel2.14.0indirect
PyPIcertifi2024.7.4indirect
PyPIcharset-normalizer3.3.2indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.14.1indirect
PyPIdocutils0.20.1indirect
PyPIexceptiongroup1.2.0indirect
PyPIidna3.15indirect
PyPIimagesize1.4.1indirect
PyPIiniconfig2.0.0indirect
PyPIjinja23.1.6indirect
PyPImarkdown-it-py3.0.0indirect
PyPImarkupsafe2.1.3indirect
PyPImdit-py-plugins0.6.1indirect
PyPImdurl0.1.2indirect
PyPImyst-parser4.0.1indirect
PyPIpackaging23.2indirect
PyPIpluggy1.5.0indirect
PyPIpygments2.20.0indirect
PyPIpytest9.1.1indirect
PyPIpytest-cov7.1.0indirect
PyPIpyyaml6.0.1indirect
PyPIrequests2.33.0indirect
PyPIsnowballstemmer2.2.0indirect
PyPIsphinx8.1.3indirect
PyPIsphinx-rtd-theme3.1.0indirect
PyPIsphinxcontrib-applehelp1.0.7indirect
PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jquery4.1indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp1.0.6indirect
PyPIsphinxcontrib-serializinghtml1.1.9indirect
PyPItomli2.0.1indirect
PyPIurllib32.7.0indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 36 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct.

No known advisories affect the assessed dependencies.

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.

Related records

Inspected repositories sharing catalogue tags or ecosystems with Bluetooth-Devices/usb-devices. Read them side by side →

100apache/arrowApache Arrow is the universal columnar format and multi-language toolbox for fast data interchange and in-memory analyticsExceptional100scikit-learn/scikit-learnscikit-learn: machine learning in PythonExceptional100deepset-ai/haystackOpen-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.Exceptional100aws/serverless-application-modelThe AWS Serverless Application Model (AWS SAM) transform is a AWS CloudFormation macro that transforms SAM templates into CloudFormation templates.Exceptional100envoyproxy/envoyCloud-native high-performance edge/middle/service proxyExceptional100uxlfoundation/oneDNNoneAPI Deep Neural Network Library (oneDNN)Exceptional

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.