Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-04 22:34 UTC

JuliusBrussee / caveman

🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking like caveman

JavaScript · PythonMIT★ 95,786 stars⑂ 5,500 forkssince Apr 2026View on GitHub ↗
KindCommand-line toolhow this is determined

JuliusBrussee/caveman holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Community & Adoption (92/100) and lowest on Sustainability & Governance (42/100). It was last updated today. 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

Julius BrusseePersonal account
2,397 followers50 public repossince Apr 2022

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Metrics by category

Vitality

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

84Excellent · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
9/36Commit cadence13/52 weeks with commits
18/18Commit volume262 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year262
human_commit_share0.96
days_since_last_push0
active_weeks_last_year13

Release discipline

100Exceptional
How it's scored
27/27Ships releases17 releases published
36/36Release recencylatest release 1 days ago
27/27Release cadencea release every ~12.6 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count17
latest_release_tagv1.10.0
releases_from_tagsno
days_since_latest_release1
mean_days_between_releases12.6
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?

92Excellent · 17% of overall
How it's scored
60/60Stars95,786 stars
25/25Forks5,500 forks
13.2/15Watchers234 watchers
Inputs used
forks5,500
stars95,786
watchers234
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateno

Sustainability & Governance

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

42Weak · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
5.8/22.5Commit distributiontop contributor authored 74% of commits
13.5/13.5Contributor breadth31 contributors
6/10OpenSSF Scorecard: Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled31
top_contributor_share0.743
How it's scored
14.7/42Issue resolution35% of issues closed
9.6/30PR acceptance52/163 decided PRs merged
0/13Newcomer PR acceptance0/16 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 1/30 approved changesets -- score normalized to 0
Inputs used
merged_prs52
open_issues206
closed_issues111
prs_merged_7d0
prs_decided_7d4
prs_merged_30d0
prs_decided_30d24
issue_closed_ratio0.35
closed_unmerged_prs111
first_time_authors_30d10
first_time_prs_merged_30d0
first_time_prs_decided_30d16
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
24.3/25Owner reach2,397 followers of JuliusBrussee
21/25Track record50 public repos, account ~4 yr old
Inputs used
followers2,397
owner_typeUser
is_verified
owner_loginJuliusBrussee
public_repos50
account_age_days1,566
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

72Good · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
6.4/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 1 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configno
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://caveman.so/
10/10Repository description
10/10Topics10 topics
10/10Wiki
Inputs used
topicsai, anthropic, caveman, claude, claude-code, llm, meme, prompt-engineering, skill, tokens
has_wikiyes
homepagehttps://caveman.so/
docs_sitehttps://caveman.so/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

52Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
0/2.5CI-Tests0 out of 1 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 1/30 approved changesets -- score normalized to 0
1.5/2.5Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
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
7.5/7.5Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
5/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
6.8/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.2
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.

55Moderate · 4% of overall
How it's scored
45/45Agent instructionsAGENTS.md, CLAUDE.md, GEMINI.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history89 of 96 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.927
agent_instruction_filesAGENTS.md, CLAUDE.md, GEMINI.md
agent_instruction_max_bytes25,044
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
10/10Demonstrated agent practice50 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency 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_share0.5
toolchain_manifests
dependency_bot_commit_share0
How it's scored
0/45Type-checkable codeJavaScript without a type-check config
54/55Manageable file sizes1/56 source files over 60KB
Inputs used
primary_languageJavaScript
largest_source_bytes78,350
source_files_sampled56
oversized_source_files1

Key facts

95,786GitHub stars
31contributors
262commits, last 12 months
0days since last push
17releases
1bus factor
206open issues
npm, PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • First-time contributor figures cover 12 of 13 authors (cap 12)
  • Could not fetch npm package 'caveman-installer' from its registry
  • No resolved dependencies carried a version and a supported ecosystem

More detail

Star and fork history 0 ★ / 5,500 ⇿
0Stars
5,500Forks
2Releases

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.

4,5004,7505,0005,2505,5005,500642026-072026-072026-08
Major 0Minor 1Patch 1
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 · 2026-08-04 22:34 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 1 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 1/30 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 0 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
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 1

Full resolved dependency set from the GitHub dependency graph: 0 direct and 1 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIanthropicindirect
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies carried a version and a supported ecosystem

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 statistics.