Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-10 10:57 UTC

mlr-org / mlr3extralearners

Extra learners for use in mlr3.

RLGPL-3.0★ 116 stars⑂ 69 forkssince Aug 2020View on GitHub ↗

mlr-org/mlr3extralearners holds a health index of 86 out of 100, placing it in the Excellent band. It scores highest on Vitality (89/100) and lowest on AI Readiness (54/100). It was last updated 7 days ago. 2 contributors account for most of its recent work.

86
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.

86
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 72 is calibrated to 86 on the published index scale (record calibration 2026-08-02).

Ownership

mlr-orgOrganization · verified domain
236 followers94 public repossince Jun 2015

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?

89Excellent · 21% of overall
How it's scored
36/36Push recency — last push 7 days ago
22.8/36Commit cadence — 33/52 weeks with commits
18/18Commit volume — 178 commits in the last year
10/10OpenSSF Scorecard: Maintained — 28 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year178
human_commit_share0.95
days_since_last_push7
active_weeks_last_year33
How it's scored
27/27Ships releases — 66 releases published
36/36Release recency — latest release 57 days ago
19.8/27Release cadence — a release every ~68.2 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count66
latest_release_tagv1.6.0
releases_from_tagsno
days_since_latest_release57
mean_days_between_releases68.2
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?

67Good · 17% of overall
How it's scored
33.4/60Stars — 116 stars
15.3/25Forks — 69 forks
2.7/15Watchers — 4 watchers
Inputs used
forks69
stars116
watchers4
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (LGPL-3.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno

Sustainability & Governance

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

76Good · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
13.7/22.5Commit distribution — top contributor authored 39% of commits
13.5/13.5Contributor breadth — 39 contributors
10/10OpenSSF Scorecard: Contributors — project has 28 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled39
top_contributor_share0.389
How it's scored
38.9/42Issue resolution — 92% of issues closed
25.7/30PR acceptance — 311/363 decided PRs merged
10.4/13Newcomer PR acceptance — 4/5 first-time contributors' PRs merged in 30d
3/15OpenSSF Scorecard: Code-Review — Found 6/26 approved changesets -- score normalized to 2
Inputs used
merged_prs311
open_issues17
closed_issues209
prs_merged_7d0
prs_decided_7d0
prs_merged_30d4
prs_decided_30d5
issue_closed_ratio0.925
closed_unmerged_prs52
first_time_authors_30d5
first_time_prs_merged_30d4
first_time_prs_decided_30d5
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
17.1/25Owner reach — 236 followers of mlr-org
25/25Track record — 94 public repos, account ~11 yr old
Inputs used
followers236
owner_typeOrganization
is_verifiedyes
owner_loginmlr-org
public_repos94
account_age_days4,102

Engineering Quality

Are baseline engineering and documentation practices in place?

68Good · 19% of overall
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
6.4/6.4.editorconfig
16/20OpenSSF Scorecard: CI-Tests — 16 out of 18 merged PRs checked by a CI test -- score normalized to 8
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configno
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://mlr3extralearners.mlr-org.com/
10/10Repository description
10/10Topics — 4 topics
0/10Wiki
Inputs used
topicsmlr3, machine-learning, r, r-package
has_wikino
homepagehttps://mlr3extralearners.mlr-org.com/
docs_sitehttps://mlr3extralearners.mlr-org.com/
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

57Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2/2.5CI-Tests — 16 out of 18 merged PRs checked by a CI test -- score normalized to 8
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
1.5/7.5Code-Review — Found 6/26 approved changesets -- score normalized to 2
2.5/2.5Contributors — project has 28 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
7.5/7.5Maintained — 28 commit(s) and 2 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
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_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate5.7
Excluded from scoring (no data or not applicable): Branch-Protection, 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.

54Moderate · 4% of overall
How it's scored
45/45Agent instructions — AGENTS.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://mlr3extralearners.mlr-org.com/llms.txt)
40/40Legible commit history — 90 of 95 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://mlr3extralearners.mlr-org.com/llms.txt
legible_history_share0.947
agent_instruction_filesAGENTS.md
agent_instruction_max_bytes5,298
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 practice — 13 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 5 of the last 100 commits are automated dependency updates
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_share0.13
toolchain_manifests—
dependency_bot_commit_share0.05
How it's scored
0/45Type-checkable code — R without a type-check config
0/55Manageable file sizes — no source files detected
Inputs used
primary_languageR
largest_source_bytes—
source_files_sampled0
oversized_source_files0
Excluded from scoring (no data or not applicable): Manageable file sizes. Remaining weights renormalized.

Key facts

116GitHub stars
39contributors
178commits, last 12 months
7days since last push
66releases
2bus factor
17open issues
—package ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

More detail

Star and fork history 0 ★ / 69 ⇿
0Stars
69Forks
65Releases

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.

01325385063756762020-102023-082026-06
Major 1Minor 14Patch 50

Each point covers 6 days.

OpenSSF Scorecard 5.7 / 10
5.7aggregate

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 · 2026-09-10 10:57 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
8CI-Tests16 out of 18 merged PRs checked by a CI test -- score normalized to 8
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 6/26 approved changesets -- score normalized to 2
10Contributorsproject has 28 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained28 commit(s) and 2 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
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 not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

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.