Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-10 12:30 UTC

EBI-Metagenomics / mgnify-pipelines-toolkit

This Python package contains a collection of scripts and tools for including in MGnify pipelines

PythonApache-2.0★ 1 star⑂ 2 forkssince Nov 2023View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

EBI-Metagenomics/mgnify-pipelines-toolkit holds a health index of 77 out of 100, placing it in the Good band. It scores highest on Vitality (90/100) and lowest on Community & Adoption (24/100). It was last updated 27 days ago. 2 contributors account for most of its recent work.

77
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.

77
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 66 is calibrated to 77 on the published index scale (record calibration 2026-08-02).

Ownership

MGnifyOrganization
175 followers236 public repossince Oct 2017

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPImgnify_pipelines_toolkit1.5.41,0157259 days agobioinformaticspipelinesmetagenomics

Metrics by category

Vitality

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

90Excellent · 21% of overall

Development activity

83Excellent
How it's scored
28.8/36Push recency — last push 27 days ago
26.3/36Commit cadence — 38/52 weeks with commits
18/18Commit volume — 296 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year296
human_commit_share1
days_since_last_push27
active_weeks_last_year38

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 72 releases published
36/36Release recency — latest release 59 days ago
27/27Release cadence — a release every ~13 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count72
latest_release_tagv1.5.4
releases_from_tagsno
days_since_latest_release59
mean_days_between_releases13
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?

24At Risk · 17% of overall

Popularity & adoption

2Critical
How it's scored
0/60Stars — 1 stars
0/25Forks — 2 forks
1.7/15Watchers — 3 watchers
Inputs used
forks2
stars1
watchers3
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Sustainability & Governance

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

81Excellent · 23% of overall

Maintainer resilience (bus factor)

63Moderate
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
13.9/22.5Commit distribution — top contributor authored 38% of commits
13.5/13.5Contributor breadth — 11 contributors
10/10OpenSSF Scorecard: Contributors — project has 4 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled11
top_contributor_share0.384

Issue & PR responsiveness

99Exceptional
How it's scored
0/42Issue resolution — no issues or no data
29.4/30PR acceptance — 158/161 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs158
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d1
prs_decided_30d1
issue_closed_ratio—
closed_unmerged_prs3
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

71Good
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
16.1/25Owner reach — 175 followers of EBI-Metagenomics
25/25Track record — 236 public repos, account ~8 yr old
Inputs used
followers175
owner_typeOrganization
is_verifiedno
owner_loginEBI-Metagenomics
public_repos236
account_age_days3,249

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 59 days ago
20/20Version history — 72 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesmgnify_pipelines_toolkit
ecosystemspypi
any_deprecatedno
min_days_since_publish59

Engineering Quality

Are baseline engineering and documentation practices in place?

76Good · 19% of overall

Engineering practices

90Excellent
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
16/20OpenSSF Scorecard: CI-Tests — 6 out of 7 merged PRs checked by a CI test -- score normalized to 8
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

55Moderate
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://www.ebi.ac.uk/metagenomics
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics—
has_wikino
homepagehttps://www.ebi.ac.uk/metagenomics
docs_sitehttps://www.ebi.ac.uk/metagenomics
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

50Moderate · 16% of overall

Security posture

46Weak
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2/2.5CI-Tests — 6 out of 7 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
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 4 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 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
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
0/7.5Vulnerabilities — 21 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4.6
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

Dependency advisories

64Moderate
How it's scored
8/35Direct dependencies free of known advisories — 3 affected: click 8.1.8 (high 7.2), datamodel-code-generator 0.54.1 (high 8.8), biopython 1.85.0 (moderate 4.9)
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
30.7/40No advisories left outstanding — 2 advisory-carrying package(s) unaddressed past 90 days; oldest published 266 days ago
Inputs used
sourceosv
advisories25
affected_packages3
assessed_packages39
unassessed_packages0
affected_by_severityhigh 2, moderate 1
direct_affected_packages3
Matched the pypi:mgnify_pipelines_toolkit@1.5.4 runtime dependency closure — what installing the published package pulls in — 39 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.

43Weak · 4% of overall

Agent context & guidance

13Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
13.3/40Legible commit history — 25 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.25
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

61Moderate
How it's scored
18/18One-command bootstrap — Taskfile.yml
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — Dockerfile, lockfile
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
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_filesTaskfile.yml
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/87 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes48,176
source_files_sampled87
oversized_source_files0

Key facts

1GitHub stars
11contributors
296commits, last 12 months
27days since last push
72releases
2bus factor
0open 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 ★ / 2 ⇿
0Stars
2Forks
12Releases

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.

111222212024-082024-122025-03
Major 1Minor 1Patch 8
OpenSSF Scorecard 4.6 / 10
4.6aggregate

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 12:29 UTC

10Binary-Artifactsno binaries found in the repo
1Branch-Protectionbranch protection is not maximal on development and all release branches
8CI-Tests6 out of 7 merged PRs checked by a CI test -- score normalized to 8
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 4 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 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow 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
0Vulnerabilities21 existing vulnerabilities detected
Direct dependencies 10
RegistryPackageVersion constraintManifest
PyPIbiopython==1.85pyproject.toml
PyPIpandas==2.2.3pyproject.toml
PyPIpandera==0.27.1pyproject.toml
PyPIpydantic<2.12.0pyproject.toml
PyPIpyfastx==2.2.0pyproject.toml
PyPIintervaltree==3.1.0pyproject.toml
PyPIclick~=8.1.8pyproject.toml
PyPIrequests~=2.32pyproject.toml
PyPIbcbio-gff==0.7.1pyproject.toml
PyPIdatamodel-code-generator==0.54.1pyproject.toml
All dependencies 65

Full resolved dependency set from the GitHub dependency graph: 10 direct and 55 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIbcbio-gff0.7.1direct
PyPIbiopython1.85direct
PyPIclick8.1.8direct
PyPIdatamodel-code-generator0.54.1direct
PyPIintervaltree3.1.0direct
PyPIpandas2.2.3direct
PyPIpandera0.27.1direct
PyPIpydantic2.11.10direct
PyPIpyfastx2.2.0direct
PyPIrequests2.32.5direct
PyPIannotated-types0.7.0indirect
PyPIargcomplete3.6.3indirect
PyPIattrs25.4.0indirect
PyPIblack26.5.1indirect
PyPIcertifi2025.11.12indirect
PyPIcfgv3.5.0indirect
PyPIcharset-normalizer3.4.4indirect
PyPIcolorama0.4.6indirect
PyPIdistlib0.4.0indirect
PyPIfilelock3.20.1indirect
PyPIgenson1.3.0indirect
PyPIidentify2.6.15indirect
PyPIidna3.11indirect
PyPIinflect7.5.0indirect
PyPIiniconfig2.3.0indirect
PyPIisal1.8.0indirect
PyPIisort8.0.1indirect
PyPIjinja23.1.6indirect
PyPIjsonschema4.25.1indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPImarkupsafe3.0.3indirect
PyPImgnify-pipelines-toolkit1.5.2indirect
PyPImore-itertools10.8.0indirect
PyPImypy-extensions1.1.0indirect
PyPInodeenv1.10.0indirect
PyPInumpy2.4.0indirect
PyPIpackaging25.0indirect
PyPIpathspec1.1.1indirect
PyPIplatformdirs4.5.1indirect
PyPIpluggy1.6.0indirect
PyPIpre-commit4.2.0indirect
PyPIpydantic-core2.33.2indirect
PyPIpytest8.3.5indirect
PyPIpytest-md0.2.0indirect
PyPIpytest-workflow2.1.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpytokens0.4.1indirect
PyPIpytz2025.2indirect
PyPIpyyaml6.0.3indirect
PyPIreferencing0.37.0indirect
PyPIrpds-py0.30.0indirect
PyPIruff0.8.4indirect
PyPIsix1.17.0indirect
PyPIsortedcontainers2.4.0indirect
PyPItomli2.4.0indirect
PyPItypeguard4.4.4indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspect0.9.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2025.3indirect
PyPIurllib32.6.2indirect
PyPIvirtualenv20.35.4indirect
PyPIxopen2.0.2indirect
PyPIzlib-ng1.0.0indirect
PyPIzstandard0.25.0indirect
Dependency advisories 3

Installing pypi:mgnify_pipelines_toolkit@1.5.4 pulls in 39 packages, direct and transitive: 3 carry known advisories, of which 3 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
click8.1.8directhigh18.3.3
datamodel-code-generator0.54.1directhigh220.64.0
biopython1.85.0directmoderate21.87

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

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Related records

Inspected repositories sharing catalogue tags or ecosystems with EBI-Metagenomics/mgnify-pipelines-toolkit. Read them side by side →

77BigDataBiology/SemiBinSemiBin: metagenomics binning with self-supervised deep learningGood77rhysnewell/aviaryA hybrid assembly and MAG recovery pipeline (and more!)Good75EBI-Metagenomics/genome_uploaderPython script to upload bins and MAGs to ENA (European Nucleotide Archive)Good63ngless-toolkit/nglessNGLess: NGS with less workModerate100apache/airflowApache Airflow - A platform to programmatically author, schedule, and monitor workflowsExceptional99kedro-org/kedroKedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.Exceptional

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.