Public record
Software health reportschema 0.31.0 · metrics 2.5.0 · 2026-08-06 18:12 UTC

rapidsai / rmm

RAPIDS Memory Manager

C++ · PythonApache-2.0★ 708 stars⑂ 253 forkssince Dec 2018View on GitHub ↗

rapidsai/rmm holds a health index of 97 out of 100, placing it in the Exceptional band. It scores highest on Vitality (96/100) and lowest on Security (69/100). It was last updated today. 4 contributors account for most of its recent work.

97
overall / 100
Exceptional

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.

97
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 85 is calibrated to 97 on the published index scale (record calibration 2026-08-02).

Ownership

RAPIDSOrganization
2,457 followers135 public repossince Oct 2018

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIrmmpoints to another repo — not scored0.0.124412256 days ago

Metrics by category

Vitality

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

96Exceptional · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
34.6/36Commit cadence — 50/52 weeks with commits
18/18Commit volume — 361 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 15 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year361
human_commit_share0.99
days_since_last_push0
active_weeks_last_year50
How it's scored
27/27Ships releases — 46 releases published
36/36Release recency — latest release 1 days ago
19.8/27Release cadence — a release every ~53.7 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count46
latest_release_tagv26.08.00
releases_from_tagsno
days_since_latest_release1
mean_days_between_releases53.7
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?

82Excellent · 17% of overall
How it's scored
46.2/60Stars — 708 stars
20/25Forks — 253 forks
7.9/15Watchers — 27 watchers
Inputs used
forks253
stars708
watchers27
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services
has_pull_request_templateyes

Sustainability & Governance

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

83Excellent · 23% of overall
How it's scored
43.2/54Bus factor — 4 contributor(s) cover half of all commits
17.6/22.5Commit distribution — top contributor authored 22% of commits
13.5/13.5Contributor breadth — 98 contributors
10/10OpenSSF Scorecard: Contributors — project has 46 contributing companies or organizations
Inputs used
bus_factor4
contributors_sampled98
top_contributor_share0.216
How it's scored
36.6/42Issue resolution — 87% of issues closed
25.8/30PR acceptance — 1,630/1,893 decided PRs merged
13/13Newcomer PR acceptance — 5/5 first-time contributors' PRs merged in 30d
12/15OpenSSF Scorecard: Code-Review — Found 18/21 approved changesets -- score normalized to 8
Inputs used
merged_prs1,630
open_issues73
closed_issues492
prs_merged_7d3
prs_decided_7d4
prs_merged_30d18
prs_decided_30d23
issue_closed_ratio0.871
closed_unmerged_prs263
first_time_authors_30d4
first_time_prs_merged_30d5
first_time_prs_decided_30d5
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
24.4/25Owner reach — 2,457 followers of rapidsai
25/25Track record — 135 public repos, account ~7 yr old
Inputs used
followers2,457
owner_typeOrganization
is_verified
owner_loginrapidsai
public_repos135
account_age_days2,862

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall
How it's scored
24/24CI workflows — 6 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 23 out of 23 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://docs.rapids.ai/api/rmm/stable/
10/10Repository description
10/10Topics — 4 topics
10/10Wiki
Inputs used
topicsrapids, cuda, memory-management, memory-allocation
has_wikiyes
homepagehttps://docs.rapids.ai/api/rmm/stable/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

69Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
6/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 23 out of 23 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
6/7.5Code-Review — Found 18/21 approved changesets -- score normalized to 8
2.5/2.5Contributors — project has 46 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
7.5/7.5Maintained — 30 commit(s) and 15 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
6.8/7.5Token-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_aggregate6.9
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.

75Good · 4% of overall
How it's scored
45/45Agent instructions — AGENTS.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 82 of 99 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
legible_history_share0.828
agent_instruction_filesAGENTS.md
agent_instruction_max_bytes7,649
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config
11/11Static type checking — python/rmm/rmm/py.typed
10/10Reproducible environment — devcontainer, Dockerfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
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_dockerfileyes
typed_languageyes
bootstrap_filesdocs/Makefile
has_devcontaineryes
has_linter_configyes
typecheck_configspython/rmm/rmm/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
How it's scored
45/45Type-checkable code — C++ (statically typed)
55/55Manageable file sizes — 0/246 source files over 60KB
Inputs used
primary_languageC++
largest_source_bytes59,765
source_files_sampled246
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
0/20MCP server
40/40Runnable examples — examples, recipes
Inputs used
example_dirsexamples, recipes
has_mcp_signalno
api_schema_files

Key facts

708GitHub stars
98contributors
361commits, last 12 months
0days since last push
46releases
4bus factor
73open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi package 'rmm' points at a different repository (https://github.com/rapidsai/dask-cuda); excluded from ecosystem scoring
  • Could not fetch pypi package 'librmm' from its registry
  • No resolved dependencies carried a version and a supported ecosystem

More detail

Star and fork history 0 ★ / 253 ⇿
0Stars
253Forks
45Releases

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.

05010015020025025042018-122022-102026-07
Major 0Minor 37Patch 5

Each point covers 7 days.

OpenSSF Scorecard 6.9 / 10
6.9aggregate

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 · 2026-08-06 18:11 UTC

10Binary-Artifactsno binaries found in the repo
8Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests23 out of 23 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
8Code-ReviewFound 18/21 approved changesets -- score normalized to 8
10Contributorsproject has 46 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 15 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
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPIrapids-logger==0.2.*,>=0.0.0a0python/librmm/pyproject.toml
PyPIcuda-bindings>=13.0.1,<14.0python/rmm/pyproject.toml
PyPIlibrmm==26.10.*,>=0.0.0a0python/rmm/pyproject.toml
PyPInumpy>=2.0,<3.0python/rmm/pyproject.toml
All dependencies 9

Full resolved dependency set from the GitHub dependency graph: 4 direct and 5 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcuda-bindingsdirect
PyPIlibrmmdirect
PyPInumpydirect
PyPIrapids-loggerdirect
PyPIcuda-coreindirect
PyPInumbaindirect
PyPInumba-cudaindirect
PyPIrapids-build-backendindirect
PyPIscikit-build-coreindirect
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

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 statisticsPyPI.