Public record
Software health reportschema 0.31.0 · metrics 2.5.0 · 2026-08-08 19:05 UTC

necaris / cuid.py

A fast, scalable unique ID generator for Python

PythonBSD-2-Clause★ 64 stars⑂ 8 forkssince Jul 2015View on GitHub ↗
KindLibraryhow this is determined

necaris/cuid.py holds a health index of 30 out of 100, placing it in the At Risk band. It scores highest on Sustainability & Governance (55/100) and lowest on Vitality (1/100). It was last updated 1175 days ago. A single contributor accounts for most of its recent work.

30
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.

30
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 36 is calibrated to 30 on the published index scale (record calibration 2026-08-02).

Ownership

Rami ChowdhuryPersonal account
102 followers100 public repossince Oct 2010

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 publish
PyPIcuid0.4-31251 days ago

Metrics by category

Vitality

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

1Critical · 21% of overall

Development activity

1Critical
How it's scored
0/36Push recency — last push 1,175 days ago
0/36Commit cadence — 0/52 weeks with commits
0/18Commit volume — 0 commits in the last year
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share1
days_since_last_push1,175
active_weeks_last_year0

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
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?

43Weak · 17% of overall

Popularity & adoption

36Weak
How it's scored
29.2/60Stars — 64 stars
7/25Forks — 8 forks
0/15Watchers — 1 watchers
Inputs used
forks8
stars64
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (BSD-2-Clause)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Sustainability & Governance

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

55Moderate · 23% of overall

Maintainer resilience (bus factor)

28At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
4.8/22.5Commit distribution — top contributor authored 79% of commits
4.1/13.5Contributor breadth — 3 contributors
10/10OpenSSF Scorecard: Contributors — project has 9 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.786

Issue & PR responsiveness

74Good
How it's scored
36.8/42Issue resolution — 88% of issues closed
26.2/30PR acceptance — 14/16 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
1.5/15OpenSSF Scorecard: Code-Review — Found 2/16 approved changesets -- score normalized to 1
Inputs used
merged_prs14
open_issues1
closed_issues7
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.875
closed_unmerged_prs2
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

62Moderate
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
14.5/25Owner reach — 102 followers of necaris
25/25Track record — 100 public repos, account ~15 yr old
Inputs used
followers102
owner_typeUser
is_verified—
owner_loginnecaris
public_repos100
account_age_days5,761
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

61Moderate
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
4/35Publish recency — latest publish 1,251 days ago
12/20Version history — 3 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagescuid
ecosystemspypi
any_deprecatedno
min_days_since_publish1,251

Engineering Quality

Are baseline engineering and documentation practices in place?

49Weak · 19% of overall

Engineering practices

48Weak
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 7 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepage—
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

33At Risk · 16% of overall

Security posture

33At Risk
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
0/2.5CI-Tests — 0 out of 7 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
0.8/7.5Code-Review — Found 2/16 approved changesets -- score normalized to 1
2.5/2.5Contributors — project has 9 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
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 — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
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 — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate3.3
Excluded from scoring (no data or not applicable): packaging, 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.

24At Risk · 4% of overall

Agent context & guidance

12Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
12.4/40Legible commit history — 13 of 56 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
legible_history_share0.232
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

22At Risk
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 56
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_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/3 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes5,116
source_files_sampled3
oversized_source_files0

Key facts

64GitHub stars
3contributors
0commits, last 12 months
1,175days since last push
0releases
1bus factor
1open 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 ★ / 8 ⇿
0Stars
8Forks

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.

02468812017-072020-072023-06

Each point covers 6 days.

OpenSSF Scorecard 3.3 / 10
3.3aggregate

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 · 2026-08-08 19:05 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 7 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 2/16 approved changesets -- score normalized to 1
10Contributorsproject has 9 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update 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
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

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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 v2.5.0, schema v0.31.0 — full methodology · metrics wiki.

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