Public record
Software health reportschema 0.27.0 · metrics 2.10.0 · 2026-07-25 08:37 UTC

sisinflab / elliot

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

PythonApache-2.0★ 298 stars⑂ 58 forkssince Oct 2020View on GitHub ↗

sisinflab/elliot holds a health index of 42 out of 100, placing it in the Weak band. It scores highest on Community & Adoption (72/100) and lowest on AI Readiness (20/100). It was last updated 4 days ago. 2 contributors account for most of its recent work.

42
overall / 100
Weak

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.

42
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 50 is calibrated to 50 on the published index scale (record calibration 2026-08-02).

Ownership

44 followers145 public repossince Dec 2014

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?

49Weak · 21% of overall
How it's scored
36/36Push recencylast push 4 days ago
1.4/36Commit cadence2/52 weeks with commits
4.3/18Commit volume2 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year2
human_commit_share1
days_since_last_push4
active_weeks_last_year2
How it's scored
27/27Ships releases5 releases published
0/36Release recencylatest release 1,843 days ago
27/27Release cadencea release every ~31.2 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count5
latest_release_tagv0.3.1
releases_from_tagsno
days_since_latest_release1,843
mean_days_between_releases31.2
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?

72Good · 17% of overall
How it's scored
40.1/60Stars298 stars
14.6/25Forks58 forks
5.6/15Watchers11 watchers
Inputs used
forks58
stars298
watchers11
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 (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

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

66Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
12.8/22.5Commit distributiontop contributor authored 43% of commits
13.5/13.5Contributor breadth10 contributors
10/10OpenSSF Scorecard: Contributorsproject has 6 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled10
top_contributor_share0.433
How it's scored
16.8/42Issue resolution40% of issues closed
26.2/30PR acceptance7/8 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-ReviewFound 4/17 approved changesets -- score normalized to 2
Inputs used
merged_prs7
open_issues15
closed_issues10
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.4
closed_unmerged_prs1
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
11.9/25Owner reach44 followers of sisinflab
25/25Track record145 public repos, account ~11 yr old
Inputs used
followers44
owner_typeOrganization
is_verified
owner_loginsisinflab
public_repos145
account_age_days4,224
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

31At Risk · 19% of overall
How it's scored
0/24CI workflows
0/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 4 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsno
has_editorconfigno
has_linter_configno
has_precommit_configno
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics19 topics
0/10Wiki
Inputs used
topicsrecommender-system, machine-learning, collaborative-filtering, content-based-recommendation, bprmf, matrix-factorization, vae, svdpp, funksvd, slim, neural-collaborative-filtering, k-nn, k-nearest-neighbours, nfm, knowledge-graph, recommendations, tensorflow2, keras, deepfm
has_wikino
homepage
docs_site
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

38Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
0/2.5CI-Tests0 out of 4 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
1.5/7.5Code-ReviewFound 4/17 approved changesets -- score normalized to 2
2.5/2.5Contributorsproject has 6 contributing companies or organizations
0/10Dangerous-Workflowno data
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesno data
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
0/7.5Token-Permissionsno data
0/7.5Vulnerabilities432 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated12
scorecard_versionv5.5.0
checks_inconclusive6
scorecard_aggregate2.2
Excluded from scoring (no data or not applicable): Branch-Protection, Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories776
affected_packages5
assessed_packages9
unassessed_packages5
affected_by_severitycritical 1, high 2, unknown 2
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 9 resolved dependencies against OSV. 5 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. Reachability is not analyzed.

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.

20At Risk · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
2.7/40Legible commit history5 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.05
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapdocs/Makefile
0/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsno
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/364 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes23,723
source_files_sampled364
oversized_source_files0

Key facts

298GitHub stars
10contributors
2commits, last 12 months
4days since last push
5releases
2bus factor
15open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Could not fetch pypi package 'elliot' from its registry
  • Advisory severity resolved for 120 of 776 advisories (lookup cap); the remainder are reported as unknown severity

More detail

Star and fork history 0 ★ / 58 ⇿
0Stars
58Forks
5Releases

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.

01020304050605762021-032023-112026-07
Major 0Minor 3Patch 2

Each point covers 5 days.

OpenSSF Scorecard 2.2 / 10
2.2aggregate

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 · 2026-07-25 08:36 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
0CI-Tests0 out of 4 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 4/17 approved changesets -- score normalized to 2
10Contributorsproject has 6 contributing companies or organizations
n/aDangerous-Workflowno workflows found
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
n/aPinned-Dependenciesno dependencies found
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
0Vulnerabilities432 existing vulnerabilities detected
All dependencies 14

Full resolved dependency set from the GitHub dependency graph: 0 direct and 14 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIhyperopt0.2.5indirect
PyPInumpy1.18.0indirect
PyPIpandas1.1.5indirect
PyPIpillowindirect
PyPIpyyaml5.4.1indirect
PyPIrinohtypeindirect
PyPIscikit-learn0.24.1indirect
PyPIscipy1.4.1indirect
PyPIsixindirect
PyPIsphinx3.5.1indirect
PyPIsphinx-copybuttonindirect
PyPIsphinx-rtd-themeindirect
PyPItensorflow2.3.2indirect
PyPItqdm4.58.0indirect
Dependency advisories 5

This repository publishes no package the index resolves, so its own dependency graph was assessed — 9 packages, which also include development and test pins that never ship: 5 carry known advisories, of which 0 are direct. 5 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
tensorflow2.3.2indirectcritical7632.11.1
numpy1.18.0indirecthigh61.22
scikit-learn0.24.1indirecthigh31.5.0
scipy1.4.1indirectunknown21.10.0
tqdm4.58.0indirectunknown2

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

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 v0.27.0 — full methodology · metrics wiki.

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