Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-18 11:13 UTC

AbdyyEee / PyLibMS

PyLibMS is a library built for Python 3.10 and above for the MSBT, MSBP and MSBF file formats.

PythonMIT★ 11 stars⑂ 1 forksince Nov 2023View on GitHub ↗

AbdyyEee/PyLibMS holds a health index of 35 out of 100, placing it in the Weak band. It scores highest on Sustainability & Governance (54/100) and lowest on AI Readiness (11/100). It was last updated today. A single contributor accounts for most of its recent work.

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.

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 40 is calibrated to 35 on the published index scale (record calibration 2026-08-02).

Ownership

AbdyyPersonal account

2 followers8 public repossince Apr 2021

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish	Tags
PyPI	PyLibMS	4.2.0	-	107	1 day ago	nintendo msbt message-text msbp message-project msbf message-flowchart flw3 modding libmessagestudio

Metrics by category

Vitality

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

42Weak · 21% of overall

Development activity

70Good

How it's scored

36/36	Push recency — last push 0 days ago
6.9/36	Commit cadence — 10/52 weeks with commits
17/18	Commit volume — 78 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	78
human_commit_share	1
days_since_last_push	0
active_weeks_last_year	10

Release discipline

1Critical

How it's scored

0/27	Ships releases — no releases published
0/36	Release recency — no releases
0/27	Release cadence — no releases
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count

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?

32At Risk · 17% of overall

Popularity & adoption

16Critical

How it's scored

16.2/60	Stars — 11 stars
0/25	Forks — 1 forks
0/15	Watchers — 2 watchers

Inputs used

forks	1
stars	11
watchers	2
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

50Moderate

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (MIT)
0/18	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	2
has_contributing	no
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	badge.fury.io, shields.io
has_pull_request_template	no

Sustainability & Governance

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

54Moderate · 23% of overall

Maintainer resilience (bus factor)

12Critical

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
0.1/22.5	Commit distribution — top contributor authored 100% of commits
2.7/13.5	Contributor breadth — 2 contributors
0/10	OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0

Inputs used

bus_factor	1
contributors_sampled	2
top_contributor_share	0.996

Issue & PR responsiveness

83Excellent

How it's scored

42/42	Issue resolution — 100% of issues closed
30/30	PR acceptance — 1/1 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15	OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0

Inputs used

merged_prs	1
open_issues	0
closed_issues	5
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	0
prs_decided_30d	0
issue_closed_ratio	1
closed_unmerged_prs	0
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

39Weak

How it's scored

10/30	Ownership backing — personal (user) account
0/20	Verified domain — not applicable to user accounts
3.4/25	Owner reach — 2 followers of AbdyyEee
17.8/25	Track record — 8 public repos, account ~5 yr old

Inputs used

followers	2
owner_type	User
is_verified	—
owner_login	AbdyyEee
public_repos	8
account_age_days	1,984

Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 1 days ago
20/20	Version history — 107 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	PyLibMS
ecosystems	pypi
any_deprecated	no
min_days_since_publish	1

Engineering Quality

Are baseline engineering and documentation practices in place?

27At Risk · 19% of overall

Engineering practices

1Critical

How it's scored

0/24	CI workflows
0/24	Tests present
0/16	Linter config
0/9.6	Pre-commit hooks
0/6.4	.editorconfig
0/20	OpenSSF Scorecard: CI-Tests — no data

Inputs used

has_ci	no
has_tests	no
has_editorconfig	no
has_linter_config	no
has_precommit_config	no

Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

65Good

How it's scored

30/30	README
0/25	Documentation directory
15/15	Documentation / homepage site — https://github.com/AbdyyEee/PylibMS/wiki
10/10	Repository description
0/10	Topics
10/10	Wiki

Inputs used

topics	—
has_wiki	yes
homepage	—
docs_site	https://github.com/AbdyyEee/PylibMS/wiki
has_readme	yes
has_docs_dir	no
has_description	yes

Security

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

50Moderate · 16% of overall

Security posture

37Weak

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — branch protection not enabled on development/release branches
0/2.5	CI-Tests — no data
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5	Code-Review — Found 0/30 approved changesets -- score normalized to 0
0/2.5	Contributors — project has 0 contributing companies or organizations -- score normalized to 0
0/10	Dangerous-Workflow — no data
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
7.5/7.5	Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5	Packaging — no data
0/5	Pinned-Dependencies — no data
0/5	SAST — no SAST tool detected
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — no data
7.5/7.5	Vulnerabilities — 0 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	12
scorecard_version	v5.5.0
checks_inconclusive	6
scorecard_aggregate	3.7

Excluded from scoring (no data or not applicable): CI-Tests, Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. 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	6
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:PyLibMS@4.2.0 runtime dependency closure — what installing the published package pulls in — 6 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.

11Critical · 4% of overall

Agent context & guidance

1Critical

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15	Machine-readable docs (llms.txt)
0/40	Legible commit history — 0 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
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

1Critical

How it's scored

0/18	One-command bootstrap
0/22	Automated tests
0/11	Lint / format config
0/11	Static type checking
0/10	Reproducible environment
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 — no data

Inputs used

has_nix	no
has_tests	no
lockfiles	—
has_dockerfile	no
typed_language	no
bootstrap_files	—
has_devcontainer	no
has_linter_config	no
typecheck_configs	—
agent_commit_share	0
toolchain_manifests	—
dependency_bot_commit_share	0

Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.

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 — 0/64 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	17,042
source_files_sampled	64
oversized_source_files	0

Key facts

11GitHub stars

2contributors

78commits, last 12 months

0days since last push

0releases

1bus factor

0open issues

PyPIpackage ecosystems

Data collection warnings

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

More detail

OpenSSF Scorecard 3.7 / 10

3.7aggregate

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 · 2026-09-18 11:13 UTC

10	Binary-Artifacts	no binaries found in the repo
0	Branch-Protection	branch protection not enabled on development/release branches
n/a	CI-Tests	no pull request found
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
0	Code-Review	Found 0/30 approved changesets -- score normalized to 0
0	Contributors	project has 0 contributing companies or organizations -- score normalized to 0
n/a	Dangerous-Workflow	no workflows found
0	Dependency-Update-Tool	no 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
n/a	Packaging	packaging workflow not detected
n/a	Pinned-Dependencies	no dependencies found
0	SAST	no SAST tool detected
0	Security-Policy	security policy file not detected
n/a	Signed-Releases	no releases found
n/a	Token-Permissions	No tokens found
10	Vulnerabilities	0 existing vulnerabilities detected

Direct dependencies 2

Registry	Package	Version constraint	Manifest
PyPI	PyYAML	`>=6.0.1`	pyproject.toml
PyPI	requests	`>=2.34.0`	pyproject.toml

All dependencies 3

Full resolved dependency set from the GitHub dependency graph: 2 direct and 1 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	pyyaml	`—`	direct
PyPI	requests	`—`	direct
PyPI	setuptools	`—`	indirect

Dependency advisories 0

Installing pypi:PyLibMS@4.2.0 pulls in 6 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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