Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-08 09:53 UTC

nim-lang / Nim

Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).

NimCustom license★ 18,257 stars⑂ 1,562 forkssince Aug 2010View on GitHub ↗

nim-lang/Nim holds a health index of 90 out of 100, placing it in the Excellent band. It scores highest on Vitality (92/100) and lowest on AI Readiness (37/100). It was last updated today. 2 contributors account for most of its recent work.

90
overall / 100
Excellent

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.

90
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 76 is calibrated to 90 on the published index scale (record calibration 2026-08-02).

Ownership

The Nim programming languageOrganization · verified domain
652 followers105 public repossince Feb 2011

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?

92Excellent · 21% of overall

Development activity

100Exceptional
How it's scored
36/36Push recency — last push 0 days ago
36/36Commit cadence — 52/52 weeks with commits
18/18Commit volume — 536 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year536
human_commit_share1
days_since_last_push0
active_weeks_last_year52
How it's scored
16.2/27Ships releases — 72 version tags (no GitHub releases)
36/36Release recency — latest release 30 days ago
19.8/27Release cadence — a release every ~78.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count72
latest_release_tagv2.2.12
releases_from_tagsyes
days_since_latest_release30
mean_days_between_releases78.4
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?

73Good · 17% of overall
How it's scored
60/60Stars — 18,257 stars
25/25Forks — 1,562 forks
13.6/15Watchers — 286 watchers
Inputs used
forks1,562
stars18,257
watchers286
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges16
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, opencollective.com, shields.io
has_pull_request_templateno

Sustainability & Governance

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

78Good · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
13/22.5Commit distribution — top contributor authored 42% of commits
13.5/13.5Contributor breadth — 100 contributors
10/10OpenSSF Scorecard: Contributors — project has 26 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled100
top_contributor_share0.424
How it's scored
34.7/42Issue resolution — 83% of issues closed
23.5/30PR acceptance — 10,848/13,864 decided PRs merged
13/13Newcomer PR acceptance — 4/4 first-time contributors' PRs merged in 30d
7.5/15OpenSSF Scorecard: Code-Review — Found 17/30 approved changesets -- score normalized to 5
Inputs used
merged_prs10,848
open_issues2,102
closed_issues10,061
prs_merged_7d40
prs_decided_7d46
prs_merged_30d53
prs_decided_30d60
issue_closed_ratio0.827
closed_unmerged_prs3,016
first_time_authors_30d4
first_time_prs_merged_30d4
first_time_prs_decided_30d4
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
20.2/25Owner reach — 652 followers of nim-lang
25/25Track record — 105 public repos, account ~15 yr old
Inputs used
followers652
owner_typeOrganization
is_verifiedyes
owner_loginnim-lang
public_repos105
account_age_days5,722

Engineering Quality

Are baseline engineering and documentation practices in place?

81Excellent · 19% of overall
How it's scored
24/24CI workflows — 7 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://nim-lang.org
10/10Repository description
10/10Topics — 8 topics
10/10Wiki
Inputs used
topicslanguage, compiler, metaprogramming, macros, efficient, procedural, nim, hacktoberfest
has_wikiyes
homepagehttps://nim-lang.org
docs_sitehttps://nim-lang.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

61Moderate · 16% of overall
How it's scored
6/7.5Binary-Artifacts — binaries present in source code
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
3.8/7.5Code-Review — Found 17/30 approved changesets -- score normalized to 5
2.5/2.5Contributors — project has 26 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
2.2/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
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
5/5Security-Policy — security policy file 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_aggregate6.1
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.

37Weak · 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 — 99 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.99
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
2/10Demonstrated agent practice — 1 of the last 100 commits agent-authored or agent-credited
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
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_share0.01
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Nim without a type-check config
55/55Manageable file sizes — 0/25 source files over 60KB
Inputs used
primary_languageNim
largest_source_bytes42,733
source_files_sampled25
oversized_source_files0

Key facts

18,257GitHub stars
100contributors
536commits, last 12 months
0days since last push
72releases
2bus factor
2,102open issues
—package ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • First-time contributor figures cover 12 of 20 authors (cap 12)

More detail

Star and fork history 0 ★ / 1,562 ⇿
0Stars
1,562Forks
53Releases

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.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

4006008001,0001,2001,4001,6001,562142018-092022-102026-10
Major 2Minor 5Patch 46

Each point covers 8 days.

OpenSSF Scorecard 6.1 / 10
6.1aggregate

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 · 2026-10-08 09:52 UTC

8Binary-Artifactsbinaries present in source code
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
5Code-ReviewFound 17/30 approved changesets -- score normalized to 5
10Contributorsproject has 26 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
10Maintained30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
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
10Security-Policysecurity policy file 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

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.