Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-14 13:38 UTC

linkml / prefixmaps

Semantic prefix map registry

PythonApache-2.0★ 14 stars⑂ 5 forkssince Aug 2022View on GitHub ↗

KindCommand-line toolLibraryhow this is determined

#bioregistry #linkml #obofoundry #prefixmaps

linkml/prefixmaps holds a health index of 69 out of 100, placing it in the Good band. It scores highest on Engineering Quality (81/100) and lowest on AI Readiness (44/100). It was last updated 73 days ago. 3 contributors account for most of its recent work.

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.

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

Ownership

Linked data Modeling LanguageOrganization

241 followers68 public repossince Feb 2021

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	Tags
PyPI	prefixmaps	0.2.6	-	15	696 days ago	semantic-web bioinformatics

Metrics by category

Vitality

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

47Weak · 21% of overall

Development activity

32At Risk

How it's scored

18/36	Push recency — last push 73 days ago
3.5/36	Commit cadence — 5/52 weeks with commits
8.1/18	Commit volume — 7 commits in the last year
2/10	OpenSSF Scorecard: Maintained — 3 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 2

Inputs used

commits_last_year	7
human_commit_share	1
days_since_last_push	73
active_weeks_last_year	5

Release discipline

70Good

How it's scored

27/27	Ships releases — 15 releases published
16.2/36	Release recency — latest release 318 days ago
19.8/27	Release cadence — a release every ~83.3 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	15
latest_release_tag	v0.2.7
releases_from_tags	no
days_since_latest_release	318
mean_days_between_releases	83.3

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?

55Moderate · 17% of overall

Popularity & adoption

28At Risk

How it's scored

18.1/60	Stars — 14 stars
5/25	Forks — 5 forks
5.3/15	Watchers — 10 watchers

Inputs used

forks	5
stars	14
watchers	10
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

85Excellent

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (Apache-2.0)
18/18	CONTRIBUTING guide
13.5/13.5	Code of conduct
0/7.2	Issue template
0/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	0
has_contributing	yes
has_issue_template	no
has_code_of_conduct	yes
readme_badge_services	—
has_pull_request_template	no

Sustainability & Governance

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

76Good · 23% of overall

Maintainer resilience (bus factor)

76Good

How it's scored

36/54	Bus factor — 3 contributor(s) cover half of all commits
16.7/22.5	Commit distribution — top contributor authored 26% of commits
13.5/13.5	Contributor breadth — 11 contributors
10/10	OpenSSF Scorecard: Contributors — project has 61 contributing companies or organizations

Inputs used

bus_factor	3
contributors_sampled	11
top_contributor_share	0.256

Issue & PR responsiveness

78Good

How it's scored

27/42	Issue resolution — 64% of issues closed
28.9/30	PR acceptance — 52/54 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
12/15	OpenSSF Scorecard: Code-Review — Found 8/9 approved changesets -- score normalized to 8

Inputs used

merged_prs	52
open_issues	10
closed_issues	18
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	0
prs_decided_30d	0
issue_closed_ratio	0.643
closed_unmerged_prs	2
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

71Good

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain
17.1/25	Owner reach — 241 followers of linkml
24.1/25	Track record — 68 public repos, account ~5 yr old

Inputs used

followers	241
owner_type	Organization
is_verified	no
owner_login	linkml
public_repos	68
account_age_days	2,032

Package maintenance

79Good

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
14/35	Publish recency — latest publish 696 days ago
20/20	Version history — 15 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	prefixmaps
ecosystems	pypi
any_deprecated	no
min_days_since_publish	696

Engineering Quality

Are baseline engineering and documentation practices in place?

81Excellent · 19% of overall

Engineering practices

68Good

How it's scored

24/24	CI workflows — 4 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.black], [tool.isort]), tox.ini
0/9.6	Pre-commit hooks
0/6.4	.editorconfig
4/20	OpenSSF Scorecard: CI-Tests — 2 out of 9 merged PRs checked by a CI test -- score normalized to 2

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	no

Documentation

100Exceptional

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://linkml.io/prefixmaps/
10/10	Repository description
10/10	Topics — 4 topics
10/10	Wiki

Inputs used

topics	bioregistry, linkml, obofoundry, prefixmaps
has_wiki	yes
homepage	https://linkml.io/prefixmaps/
docs_site	https://linkml.io/prefixmaps/
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?

49Weak · 16% of overall

Security posture

36Weak

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — no data
0.5/2.5	CI-Tests — 2 out of 9 merged PRs checked by a CI test -- score normalized to 2
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6/7.5	Code-Review — Found 8/9 approved changesets -- score normalized to 8
2.5/2.5	Contributors — project has 61 contributing companies or organizations
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5	Dependency-Update-Tool — no update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
1.5/7.5	Maintained — 3 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 2
0/5	Packaging — no data
0/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
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
0/7.5	Vulnerabilities — 25 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	15
scorecard_version	v5.5.0
checks_inconclusive	3
scorecard_aggregate	3.6

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

Dependency advisories

100Exceptional

How it's scored

35/35	Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	0
affected_packages	0
assessed_packages	9
unassessed_packages	0
affected_by_severity	none
direct_affected_packages	0

Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:prefixmaps@0.2.6 runtime dependency closure — what installing the published package pulls in — 9 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.

44Weak · 4% of overall

Agent context & guidance

16Critical

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15	Machine-readable docs (llms.txt)
15.5/40	Legible commit history — 29 of 100 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.29
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

61Moderate

How it's scored

18/18	One-command bootstrap — Makefile, docs/Makefile
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.black], [tool.isort]), tox.ini
0/11	Static type checking
10/10	Reproducible environment — lockfile
0/10	Demonstrated agent practice — no agent-authored commits among the last 100
0/8	Automated maintenance — no automated dependency updates observed
0/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0

Inputs used

has_nix	no
has_tests	yes
lockfiles	poetry.lock
has_dockerfile	no
typed_language	no
bootstrap_files	Makefile, docs/Makefile
has_devcontainer	no
has_linter_config	yes
typecheck_configs	—
agent_commit_share	0
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

55Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
55/55	Manageable file sizes — 0/29 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	14,416
source_files_sampled	29
oversized_source_files	0

Key facts

14GitHub stars

11contributors

7commits, last 12 months

73days since last push

15releases

3bus factor

10open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
pypi download statistics for 'prefixmaps' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced

More detail

Star and fork history 0 ★ / 5 ⇿

0Stars

5Forks

14Releases

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 1Patch 13

Each point covers 4 days.

OpenSSF Scorecard 3.6 / 10

3.6aggregate

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 · 2026-09-14 13:38 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
2	CI-Tests	2 out of 9 merged PRs checked by a CI test -- score normalized to 2
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
8	Code-Review	Found 8/9 approved changesets -- score normalized to 8
10	Contributors	project has 61 contributing companies or organizations
10	Dangerous-Workflow	no dangerous workflow patterns detected
0	Dependency-Update-Tool	no update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
2	Maintained	3 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 2
n/a	Packaging	packaging workflow not detected
0	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 0
0	SAST	SAST tool is not run on all commits -- score normalized to 0
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
0	Vulnerabilities	25 existing vulnerabilities detected

Direct dependencies 2

Registry	Package	Version constraint	Manifest
PyPI	pyyaml	`>=5.3.1`	pyproject.toml
PyPI	curies	`>=0.5.3`	pyproject.toml

All dependencies 64

Full resolved dependency set from the GitHub dependency graph: 2 direct and 62 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	curies	`0.7.9`	direct
PyPI	pyyaml	`6.0.1`	direct
PyPI	alabaster	`0.7.13`	indirect
PyPI	annotated-types	`0.6.0`	indirect
PyPI	babel	`2.14.0`	indirect
PyPI	bioregistry	`0.11.10`	indirect
PyPI	cachetools	`5.3.3`	indirect
PyPI	certifi	`2024.2.2`	indirect
PyPI	chardet	`5.2.0`	indirect
PyPI	charset-normalizer	`3.3.2`	indirect
PyPI	click	`8.1.7`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	coverage	`7.4.4`	indirect
PyPI	distlib	`0.3.8`	indirect
PyPI	docutils	`0.20.1`	indirect
PyPI	exceptiongroup	`1.2.0`	indirect
PyPI	filelock	`3.13.4`	indirect
PyPI	idna	`3.7`	indirect
PyPI	imagesize	`1.4.1`	indirect
PyPI	importlib-metadata	`7.1.0`	indirect
PyPI	iniconfig	`2.0.0`	indirect
PyPI	isodate	`0.6.1`	indirect
PyPI	jinja2	`3.1.3`	indirect
PyPI	markdown-it-py	`3.0.0`	indirect
PyPI	markupsafe	`2.1.5`	indirect
PyPI	mdit-py-plugins	`0.4.0`	indirect
PyPI	mdurl	`0.1.2`	indirect
PyPI	more-click	`0.1.2`	indirect
PyPI	myst-parser	`2.0.0`	indirect
PyPI	packaging	`24.0`	indirect
PyPI	platformdirs	`4.2.0`	indirect
PyPI	pluggy	`1.4.0`	indirect
PyPI	pydantic	`2.7.0`	indirect
PyPI	pydantic-core	`2.18.1`	indirect
PyPI	pygments	`2.17.2`	indirect
PyPI	pyparsing	`3.1.2`	indirect
PyPI	pyproject-api	`1.6.1`	indirect
PyPI	pystow	`0.5.4`	indirect
PyPI	pytest	`8.1.1`	indirect
PyPI	pytrie	`0.4.0`	indirect
PyPI	pytz	`2024.1`	indirect
PyPI	rdflib	`6.3.2`	indirect
PyPI	requests	`2.31.0`	indirect
PyPI	six	`1.16.0`	indirect
PyPI	snowballstemmer	`2.2.0`	indirect
PyPI	sortedcontainers	`2.4.0`	indirect
PyPI	sphinx	`7.1.2`	indirect
PyPI	sphinx-autodoc-typehints	`2.0.1`	indirect
PyPI	sphinx-click	`5.1.0`	indirect
PyPI	sphinx-rtd-theme	`2.0.0`	indirect
PyPI	sphinxcontrib-applehelp	`1.0.4`	indirect
PyPI	sphinxcontrib-devhelp	`1.0.2`	indirect
PyPI	sphinxcontrib-htmlhelp	`2.0.1`	indirect
PyPI	sphinxcontrib-jquery	`4.1`	indirect
PyPI	sphinxcontrib-jsmath	`1.0.1`	indirect
PyPI	sphinxcontrib-qthelp	`1.0.3`	indirect
PyPI	sphinxcontrib-serializinghtml	`1.1.5`	indirect
PyPI	tomli	`2.0.1`	indirect
PyPI	tox	`4.14.2`	indirect
PyPI	tqdm	`4.66.2`	indirect
PyPI	typing-extensions	`4.11.0`	indirect
PyPI	urllib3	`2.2.1`	indirect
PyPI	virtualenv	`20.25.1`	indirect
PyPI	zipp	`3.18.1`	indirect

Dependency advisories 0

Installing pypi:prefixmaps@0.2.6 pulls in 9 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

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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