Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-22 15:31 UTC

helicalAI / helical

A framework for state-of-the-art pre-trained bio foundation models on genomics and transcriptomics modalities.

PythonAGPL-3.0★ 229 stars⑂ 38 forkssince Apr 2024View on GitHub ↗

helicalAI/helical holds a health index of 81 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (78/100) and lowest on AI Readiness (57/100). It was last updated today. A single contributor accounts for most of its recent work.

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.

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)

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 69 is calibrated to 81 on the published index scale (record calibration 2026-08-02).

Ownership

HelicalOrganization

53 followers3 public repossince Jul 2023

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

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish
PyPI	helical	3.1.1	1,236	80	15 days ago

Metrics by category

Vitality

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

73Good · 21% of overall

Development activity

87Excellent

How it's scored

36/36	Push recency — last push 0 days ago
22.8/36	Commit cadence — 33/52 weeks with commits
18/18	Commit volume — 275 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	275
human_commit_share	0.96
days_since_last_push	0
active_weeks_last_year	33

Release discipline

52Moderate

How it's scored

27/27	Ships releases — 2 releases published
7.2/36	Release recency — latest release 606 days ago
12.6/27	Release cadence — a release every ~146.7 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	2
latest_release_tag	v0.0.1a16
releases_from_tags	no
days_since_latest_release	606
mean_days_between_releases	146.7

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?

60Moderate · 17% of overall

Popularity & adoption

55Moderate

How it's scored

38.2/60	Stars — 229 stars
13.1/25	Forks — 38 forks
3.9/15	Watchers — 6 watchers

Inputs used

forks	38
stars	229
watchers	6
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

70Good

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (AGPL-3.0)
18/18	CONTRIBUTING guide
0/13.5	Code of conduct
0/7.2	Issue template
0/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	5
has_contributing	yes
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	badge.fury.io, github.com, shields.io
has_pull_request_template	no

Ecosystem adoption (downloads)

52Moderate

How it's scored

41.2/80	Monthly downloads — 1,236 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	helical
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	1,236
unverified_packages_excluded	—

Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

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

66Good · 23% of overall

Maintainer resilience (bus factor)

36Weak

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
10.7/22.5	Commit distribution — top contributor authored 53% of commits
13.5/13.5	Contributor breadth — 17 contributors
3/10	OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3

Inputs used

bus_factor	1
contributors_sampled	17
top_contributor_share	0.526

Issue & PR responsiveness

87Excellent

How it's scored

36.9/42	Issue resolution — 88% of issues closed
25.7/30	PR acceptance — 330/385 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
13.5/15	OpenSSF Scorecard: Code-Review — Found 16/17 approved changesets -- score normalized to 9

Inputs used

merged_prs	330
open_issues	4
closed_issues	29
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	5
prs_decided_30d	5
issue_closed_ratio	0.879
closed_unmerged_prs	55
first_time_authors_30d	0
first_time_prs_merged_30d	0
first_time_prs_decided_30d	0

Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

53Moderate

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain
12.5/25	Owner reach — 53 followers of helicalAI
10.6/25	Track record — 3 public repos, account ~3 yr old

Inputs used

followers	53
owner_type	Organization
is_verified	no
owner_login	helicalAI
public_repos	3
account_age_days	1,136

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 15 days ago
20/20	Version history — 80 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	helical
ecosystems	pypi
any_deprecated	no
min_days_since_publish	15

Engineering Quality

Are baseline engineering and documentation practices in place?

78Good · 19% of overall

Engineering practices

64Moderate

How it's scored

24/24	CI workflows — 2 workflow(s)
24/24	Tests present
0/16	Linter config
0/9.6	Pre-commit hooks
0/6.4	.editorconfig
16/20	OpenSSF Scorecard: CI-Tests — 17 out of 21 merged PRs checked by a CI test -- score normalized to 8

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	no
has_precommit_config	no

Documentation

100Exceptional

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://www.helical-ai.com/
10/10	Repository description
10/10	Topics — 20 topics
10/10	Wiki

Inputs used

topics	artificial-intelligence, bioinformatics, biology, deep-learning, dna-sequences, foundation-models, gene-expression, pre-trained-model, pre-training, rna-seq, rnaseq, transformer, vcf, scgpt, uce, geneformer, evo2, transcriptformer, helixmrna, rna
has_wiki	yes
homepage	https://www.helical-ai.com/
docs_site	https://www.helical-ai.com/
has_readme	yes
has_docs_dir	yes
has_description	yes

Security

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

70Good · 16% of overall

Security posture

70Good

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — no data
2/2.5	CI-Tests — 17 out of 21 merged PRs checked by a CI test -- score normalized to 8
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6.8/7.5	Code-Review — Found 16/17 approved changesets -- score normalized to 9
0.8/2.5	Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5	Dependency-Update-Tool — update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5	Packaging — packaging workflow detected
2.5/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
5/5	SAST — SAST tool is run on all commits
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
6/7.5	Vulnerabilities — 2 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	16
scorecard_version	v5.5.0
checks_inconclusive	2
scorecard_aggregate	7

Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.

Dependency advisories

69Good

How it's scored

10.4/35	Direct dependencies free of known advisories — 3 affected: hydra-core 1.3.2 (high 7.8), torch 2.10.0 (high 7.8), datasets 3.6.0 (unknown)
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
33.5/40	No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 509 days ago

Inputs used

source	osv
advisories	4
affected_packages	3
assessed_packages	100
unassessed_packages	0
affected_by_severity	high 2, unknown 1
direct_affected_packages	3

Matched the pypi:helical@3.1.1 runtime dependency closure — what installing the published package pulls in — 100 packages. 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.

57Moderate · 4% of overall

Agent context & guidance

40Weak

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15	Machine-readable docs (llms.txt)
40/40	Legible commit history — 75 of 96 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.781
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

55Moderate

How it's scored

0/18	One-command bootstrap
22/22	Automated tests
0/11	Lint / format config
0/11	Static type checking
10/10	Reproducible environment — Dockerfile
10/10	Demonstrated agent practice — 8 of the last 100 commits agent-authored or agent-credited
8/8	Automated maintenance — 4 of the last 100 commits are automated dependency updates
5/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5

Inputs used

has_nix	no
has_tests	yes
lockfiles	—
has_dockerfile	yes
typed_language	no
bootstrap_files	—
has_devcontainer	no
has_linter_config	no
typecheck_configs	—
agent_commit_share	0.08
toolchain_manifests	—
dependency_bot_commit_share	0.04

Code legibility for models

55Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
54.7/55	Manageable file sizes — 1/210 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	88,570
source_files_sampled	210
oversized_source_files	1

Machine-readable interfaces

100Exceptional

How it's scored

0/40	API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20	MCP server — not applicable to this kind of software
40/40	Runnable examples — examples, notebooks

Inputs used

example_dirs	examples, notebooks
has_mcp_signal	no
api_schema_files	—
interfaces_expected_of	—

Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

229GitHub stars

17contributors

275commits, last 12 months

0days since last push

2releases

1bus factor

4open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 38 ⇿

0Stars

38Forks

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.

Major 0Minor 0Patch 0

Each point covers 2 days.

OpenSSF Scorecard 7.0 / 10

7.0aggregate

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 · 2026-08-22 15:31 UTC

10	Binary-Artifacts	no binaries found in the repo
n/a	Branch-Protection	internal 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
8	CI-Tests	17 out of 21 merged PRs checked by a CI test -- score normalized to 8
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
9	Code-Review	Found 16/17 approved changesets -- score normalized to 9
3	Contributors	project has 1 contributing companies or organizations -- score normalized to 3
10	Dangerous-Workflow	no dangerous workflow patterns detected
10	Dependency-Update-Tool	update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
10	Packaging	packaging workflow detected
5	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 5
10	SAST	SAST tool is run on all commits
0	Security-Policy	security policy file not detected
n/a	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
8	Vulnerabilities	2 existing vulnerabilities detected

Direct dependencies 21

Registry	Package	Version constraint	Manifest
PyPI	requests	`>=2.32.3`	pyproject.toml
PyPI	pandas	`==2.2.2`	pyproject.toml
PyPI	anndata	`>=0.11`	pyproject.toml
PyPI	numpy	`>=2.1.3,<2.3`	pyproject.toml
PyPI	scikit-learn	`>=1.5.0`	pyproject.toml
PyPI	scipy	`==1.13.1`	pyproject.toml
PyPI	torch	`==2.10.0`	pyproject.toml
PyPI	accelerate	`==1.14.0`	pyproject.toml
PyPI	transformers	`>=5.3.0`	pyproject.toml
PyPI	scikit-misc	`>=0.5.2`	pyproject.toml
PyPI	einops	`==0.8.1`	pyproject.toml
PyPI	omegaconf	`==2.3.0`	pyproject.toml
PyPI	hydra-core	`==1.3.2`	pyproject.toml
PyPI	pybiomart	`—`	pyproject.toml
PyPI	datasets	`==3.6.0`	pyproject.toml
PyPI	sentencepiece	`>=0.2.0`	pyproject.toml
PyPI	bitsandbytes	`>=0.48.2`	pyproject.toml
PyPI	scanpy	`>=1.11`	pyproject.toml
PyPI	requests-cache	`>=1.2`	pyproject.toml
PyPI	torchmetrics	`>=1.0`	pyproject.toml
PyPI	catalogue	`>=2.0`	pyproject.toml

All dependencies 36

Full resolved dependency set from the GitHub dependency graph: 20 direct and 16 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	accelerate	`1.14.0`	direct
PyPI	anndata	`—`	direct
PyPI	bitsandbytes	`—`	direct
PyPI	catalogue	`—`	direct
PyPI	datasets	`3.6.0`	direct
PyPI	einops	`0.8.1`	direct
PyPI	hydra-core	`1.3.2`	direct
PyPI	numpy	`—`	direct
PyPI	omegaconf	`2.3.0`	direct
PyPI	pandas	`2.2.2`	direct
PyPI	requests	`—`	direct
PyPI	requests-cache	`—`	direct
PyPI	scanpy	`—`	direct
PyPI	scikit-learn	`—`	direct
PyPI	scikit-misc	`—`	direct
PyPI	scipy	`1.13.1`	direct
PyPI	sentencepiece	`—`	direct
PyPI	torch	`2.10.0`	direct
PyPI	torchmetrics	`—`	direct
PyPI	transformers	`—`	direct
PyPI	biopython	`1.85`	indirect
PyPI	black	`26.3.1`	indirect
PyPI	causal-conv1d	`1.6.2.post1`	indirect
PyPI	causal-conv1d	`1.6.2.post1+cu13torch2.10cxx11abitrue`	indirect
PyPI	flash-attn	`2.8.3+cu13torch2.10cxx11abitrue`	indirect
PyPI	mamba-ssm	`2.3.2.post1`	indirect
PyPI	mamba-ssm	`2.3.2.post1+cu13torch2.10cxx11abitrue`	indirect
PyPI	mkdocs	`1.6.1`	indirect
PyPI	mkdocs-jupyter	`0.25.1`	indirect
PyPI	mkdocs-material	`9.5.44`	indirect
PyPI	mkdocstrings	`—`	indirect
PyPI	nbmake	`1.5.4`	indirect
PyPI	pytest	`9.0.3`	indirect
PyPI	pytest-cov	`7.1.0`	indirect
PyPI	pytest-mock	`3.15.1`	indirect
PyPI	transformer-engine	`1.13.0`	indirect

Dependency advisories 3

Installing pypi:helical@3.1.1 pulls in 100 packages, direct and transitive: 3 carry known advisories, of which 3 are direct dependencies.

Package	Version	Relation	Severity	Advisories	Fixed in
hydra-core	`1.3.2`	direct	high	1	`1.3.4`
torch	`2.10.0`	direct	high	2	`2.13.0`
datasets	`3.6.0`	direct	unknown	1	`5.0.1`

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.

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 — PyPI.

Software health index

Score profile

Ownership

Package ecosystems

Metrics by category

Key facts

Data collection warnings

More detail

Feedback

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