Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-19 15:23 UTC

banesullivan / scooby

Great Dane turned Python environment detective

PythonMIT★ 61 stars⑂ 14 forkssince Jun 2019View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

banesullivan/scooby holds a health index of 67 out of 100, placing it in the Good band. It scores highest on Engineering Quality (74/100) and lowest on Community & Adoption (45/100). It was last updated 9 days ago. A single contributor accounts for most of its recent work.

67
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.

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

Ownership

Bane SullivanPersonal account
618 followers51 public repossince Sep 2016

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
PyPIscooby0.11.2-42118 days agoenvironmentreportingversioning

Metrics by category

Vitality

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

60Moderate · 21% of overall
How it's scored
28.8/36Push recencylast push 9 days ago
7.6/36Commit cadence11/52 weeks with commits
12.2/18Commit volume22 commits in the last year
2/10OpenSSF Scorecard: Maintained3 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 2
Inputs used
commits_last_year22
human_commit_share0.95
days_since_last_push9
active_weeks_last_year11
How it's scored
27/27Ships releases7 releases published
27/36Release recencylatest release 120 days ago
12.6/27Release cadencea release every ~227.9 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count7
latest_release_tagv0.11.1
releases_from_tagsno
days_since_latest_release120
mean_days_between_releases227.9
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?

45Weak · 17% of overall
How it's scored
28.8/60Stars61 stars
9.3/25Forks14 forks
2.7/15Watchers4 watchers
Inputs used
forks14
stars61
watchers4
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateno

Sustainability & Governance

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

70Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
8.5/22.5Commit distributiontop contributor authored 62% of commits
13.5/13.5Contributor breadth12 contributors
10/10OpenSSF Scorecard: Contributorsproject has 14 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled12
top_contributor_share0.624
How it's scored
40.4/42Issue resolution96% of issues closed
25.3/30PR acceptance87/103 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
6/15OpenSSF Scorecard: Code-ReviewFound 11/25 approved changesets -- score normalized to 4
Inputs used
merged_prs87
open_issues2
closed_issues51
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.962
closed_unmerged_prs16
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
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
20.1/25Owner reach618 followers of banesullivan
24.5/25Track record51 public repos, account ~9 yr old
Inputs used
followers618
owner_typeUser
is_verified
owner_loginbanesullivan
public_repos51
account_age_days3,632
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 118 days ago
20/20Version history42 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesscooby
ecosystemspypi
any_deprecatedno
min_days_since_publish118

Engineering Quality

Are baseline engineering and documentation practices in place?

74Good · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
16/20OpenSSF Scorecard: CI-Tests20 out of 24 merged PRs checked by a CI test -- score normalized to 8
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics5 topics
0/10Wiki
Inputs used
topicspython, bug-reporting, system-information, python-versions, reproducibility
has_wikino
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

53Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
2.2/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2/2.5CI-Tests20 out of 24 merged PRs checked by a CI test -- score normalized to 8
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3/7.5Code-ReviewFound 11/25 approved changesets -- score normalized to 4
2.5/2.5Contributorsproject has 14 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
1.5/7.5Maintained3 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 2
5/5Packagingpackaging workflow detected
0.5/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
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
7.5/7.5Token-PermissionsGitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.3
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

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.

55Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
30.9/40Legible commit history55 of 95 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.579
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
11/11Lint / format config
11/11Static type checkingscooby/py.typed
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
0/8Automated maintenanceno automated dependency updates observed
1/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configsscooby/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
How it's scored
27/45Type-checkable codePython with type-check config (scooby/py.typed)
55/55Manageable file sizes0/6 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes24,647
source_files_sampled6
oversized_source_files0

Key facts

61GitHub stars
12contributors
22commits, last 12 months
9days since last push
7releases
1bus factor
2open issues
PyPIpackage ecosystems

Data collection warnings

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

More detail

Star and fork history 0 ★ / 14 ⇿
0Stars
14Forks
6Releases

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.

03581013151412020-022022-092025-04
Major 0Minor 4Patch 2

Each point covers 5 days.

OpenSSF Scorecard 5.3 / 10
5.3aggregate

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 · 2026-08-19 15:22 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
8CI-Tests20 out of 24 merged PRs checked by a CI test -- score normalized to 8
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
4Code-ReviewFound 11/25 approved changesets -- score normalized to 4
10Contributorsproject has 14 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
2Maintained3 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 2
10Packagingpackaging workflow detected
1Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 0

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

RegistryPackageVersionRelation
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies to assess

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 v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.