Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-19 13:28 UTC

idfkit / idfkit

⚡ A fast, modern EnergyPlus IDF/epJSON toolkit for Python

PythonMIT★ 11 stars⑂ 2 forkssince Feb 2026View on GitHub ↗

KindLibraryCommand-line toolhow this is determined

#building-energy-simulation #energy-modeling #energyplus #idf #python #epjson

idfkit/idfkit holds a health index of 75 out of 100, placing it in the Good band. It scores highest on Vitality (85/100) and lowest on Community & Adoption (46/100). It was last updated today. A single contributor accounts 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 65 is calibrated to 75 on the published index scale (record calibration 2026-08-02).

Ownership

idfkitOrganization

5 followers12 public repossince Feb 2026

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	idfkit	1.1.1	4,265	38	0 days ago	building-simulation energy-modeling energyplus epjson idf parser

Metrics by category

Vitality

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

85Excellent · 21% of overall

Development activity

81Excellent

How it's scored

36/36	Push recency — last push 0 days ago
16.6/36	Commit cadence — 24/52 weeks with commits
18/18	Commit volume — 234 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 30 commit(s) and 22 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	234
human_commit_share	0.99
days_since_last_push	0
active_weeks_last_year	24

Release discipline

90Excellent

How it's scored

27/27	Ships releases — 38 releases published
36/36	Release recency — latest release 0 days ago
27/27	Release cadence — a release every ~11.5 days
0/10	OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.

Inputs used

releases_count	38
latest_release_tag	v1.1.1
releases_from_tags	no
days_since_latest_release	0
mean_days_between_releases	11.5

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

46Weak · 17% of overall

Popularity & adoption

16Critical

How it's scored

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

Inputs used

forks	2
stars	11
watchers	0
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 (MIT)
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	4
has_contributing	yes
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	codecov.io, shields.io
has_pull_request_template	no

Ecosystem adoption (downloads)

60Moderate

How it's scored

48.4/80	Monthly downloads — 4,265 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	idfkit
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	4,265
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?

54Moderate · 23% of overall

Maintainer resilience (bus factor)

23At Risk

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
0.3/22.5	Commit distribution — top contributor authored 99% of commits
4.1/13.5	Contributor breadth — 3 contributors
10/10	OpenSSF Scorecard: Contributors — project has 3 contributing companies or organizations -- score normalized to 10

Inputs used

bus_factor	1
contributors_sampled	3
top_contributor_share	0.987

Issue & PR responsiveness

65Good

How it's scored

28.6/42	Issue resolution — 68% of issues closed
27.8/30	PR acceptance — 168/181 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15	OpenSSF Scorecard: Code-Review — Found 0/27 approved changesets -- score normalized to 0

Inputs used

merged_prs	168
open_issues	14
closed_issues	30
prs_merged_7d	11
prs_decided_7d	11
prs_merged_30d	14
prs_decided_30d	14
issue_closed_ratio	0.682
closed_unmerged_prs	13
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

45Weak

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain
5.6/25	Owner reach — 5 followers of idfkit
9.4/25	Track record — 12 public repos, account ~0 yr old

Inputs used

followers	5
owner_type	Organization
is_verified	no
owner_login	idfkit
public_repos	12
account_age_days	240

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 0 days ago
20/20	Version history — 38 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	idfkit
ecosystems	pypi
any_deprecated	no
min_days_since_publish	0

Engineering Quality

Are baseline engineering and documentation practices in place?

82Excellent · 19% of overall

Engineering practices

94Exceptional

How it's scored

24/24	CI workflows — 10 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.ruff]), tox.ini
9.6/9.6	Pre-commit hooks
0/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 28 out of 28 merged PRs checked by a CI test -- score normalized to 10

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	yes

Documentation

65Good

How it's scored

30/30	README
0/25	Documentation directory
15/15	Documentation / homepage site — https://py.idfkit.com
10/10	Repository description
10/10	Topics — 6 topics
0/10	Wiki

Inputs used

topics	building-energy-simulation, energy-modeling, energyplus, idf, python, epjson
has_wiki	no
homepage	https://py.idfkit.com
docs_site	https://py.idfkit.com
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?

48Weak · 16% of overall

Security posture

35Weak

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
2.2/7.5	Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5	CI-Tests — 28 out of 28 merged PRs checked by a CI test -- score normalized to 10
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5	Code-Review — Found 0/27 approved changesets -- score normalized to 0
2.5/2.5	Contributors — project has 3 contributing companies or organizations -- score normalized to 10
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
7.5/7.5	Maintained — 30 commit(s) and 22 issue activity found in the last 90 days -- score normalized to 10
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 — Project has not signed or included provenance with any releases.
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5	Vulnerabilities — 95 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	17
scorecard_version	v5.5.0
checks_inconclusive	1
scorecard_aggregate	3.5

Excluded from scoring (no data or not applicable): Packaging. 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
0/25	Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	181
affected_packages	16
assessed_packages	140
unassessed_packages	0
affected_by_severity	critical 2, high 6, moderate 7, low 1
direct_affected_packages	0

Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 140 resolved dependencies against OSV. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

83Excellent · 4% of overall

Agent context & guidance

85Excellent

How it's scored

45/45	Agent instructions — AGENTS.md, CLAUDE.md
0/15	Machine-readable docs (llms.txt)
40/40	Legible commit history — 93 of 99 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.939
agent_instruction_files	AGENTS.md, CLAUDE.md
agent_instruction_max_bytes	16,450

Verify loop (build / test / typecheck)

82Excellent

How it's scored

18/18	One-command bootstrap — Makefile
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.ruff]), tox.ini
11/11	Static type checking — src/idfkit/py.typed
10/10	Reproducible environment — devcontainer, lockfile
10/10	Demonstrated agent practice — 44 of the last 100 commits agent-authored or agent-credited
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	uv.lock
has_dockerfile	no
typed_language	no
bootstrap_files	Makefile
has_devcontainer	yes
has_linter_config	yes
typecheck_configs	src/idfkit/py.typed
agent_commit_share	0.44
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

81Excellent

How it's scored

27/45	Type-checkable code — Python with type-check config (src/idfkit/py.typed)
54.3/55	Manageable file sizes — 3/239 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	93,978
source_files_sampled	239
oversized_source_files	3

Key facts

11GitHub stars

3contributors

234commits, last 12 months

0days since last push

38releases

1bus factor

14open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
deps.dev does not index pypi:idfkit@1.1.1; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 2 ⇿

0Stars

2Forks

24Releases

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 11Patch 12

OpenSSF Scorecard 3.5 / 10

3.5aggregate

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 · 2026-10-19 13:28 UTC

10	Binary-Artifacts	no binaries found in the repo
3	Branch-Protection	branch protection is not maximal on development and all release branches
10	CI-Tests	28 out of 28 merged PRs checked by a CI test -- score normalized to 10
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
0	Code-Review	Found 0/27 approved changesets -- score normalized to 0
10	Contributors	project has 3 contributing companies or organizations -- score normalized to 10
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
10	Maintained	30 commit(s) and 22 issue activity found in the last 90 days -- score normalized to 10
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
0	Signed-Releases	Project has not signed or included provenance with any releases.
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
0	Vulnerabilities	95 existing vulnerabilities detected

All dependencies 140

Full resolved dependency set from the GitHub dependency graph: 0 direct and 140 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	aiobotocore	`3.1.2`	indirect
PyPI	aiohappyeyeballs	`2.6.1`	indirect
PyPI	aiohttp	`3.13.3`	indirect
PyPI	aioitertools	`0.13.0`	indirect
PyPI	aiosignal	`1.4.0`	indirect
PyPI	alabaster	`1.0.0`	indirect
PyPI	async-timeout	`5.0.1`	indirect
PyPI	attrs	`25.4.0`	indirect
PyPI	babel	`2.18.0`	indirect
PyPI	backports-asyncio-runner	`1.2.0`	indirect
PyPI	beautifulsoup4	`4.14.3`	indirect
PyPI	bleach	`6.3.0`	indirect
PyPI	boto3	`1.42.42`	indirect
PyPI	botocore	`1.42.42`	indirect
PyPI	botocore-stubs	`1.42.41`	indirect
PyPI	cachetools	`7.0.0`	indirect
PyPI	certifi	`2026.1.4`	indirect
PyPI	cffi	`2.0.0`	indirect
PyPI	cfgv	`3.5.0`	indirect
PyPI	chardet	`5.2.0`	indirect
PyPI	charset-normalizer	`3.4.4`	indirect
PyPI	click	`8.3.1`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	contourpy	`1.3.2`	indirect
PyPI	contourpy	`1.3.3`	indirect
PyPI	coverage	`7.13.3`	indirect
PyPI	cycler	`0.12.1`	indirect
PyPI	decorator	`5.2.1`	indirect
PyPI	defusedxml	`0.7.1`	indirect
PyPI	deptry	`0.24.0`	indirect
PyPI	distlib	`0.4.0`	indirect
PyPI	docutils	`0.21.2`	indirect
PyPI	docutils	`0.22.4`	indirect
PyPI	energyplus-idd-idf-utilities	`0.88`	indirect
PyPI	eppy	`0.5.69`	indirect
PyPI	esoreader	`1.2.3`	indirect
PyPI	exceptiongroup	`1.3.1`	indirect
PyPI	fastjsonschema	`2.21.2`	indirect
PyPI	filelock	`3.20.3`	indirect
PyPI	fonttools	`4.61.1`	indirect
PyPI	frozenlist	`1.8.0`	indirect
PyPI	future	`1.0.0`	indirect
PyPI	identify	`2.6.16`	indirect
PyPI	idfkit	`1.1.1`	indirect
PyPI	idna	`3.11`	indirect
PyPI	imagesize	`1.4.1`	indirect
PyPI	iniconfig	`2.3.0`	indirect
PyPI	jinja2	`3.1.6`	indirect
PyPI	jmespath	`1.1.0`	indirect
PyPI	jsonschema	`4.26.0`	indirect
PyPI	jsonschema-specifications	`2025.9.1`	indirect
PyPI	jupyter-client	`8.8.0`	indirect
PyPI	jupyter-core	`5.9.1`	indirect
PyPI	jupyterlab-pygments	`0.3.0`	indirect
PyPI	kiwisolver	`1.4.9`	indirect
PyPI	lxml	`6.0.2`	indirect
PyPI	markupsafe	`3.0.3`	indirect
PyPI	matplotlib	`3.10.8`	indirect
PyPI	matplotlib-stubs	`0.3.11`	indirect
PyPI	mistune	`3.2.0`	indirect
PyPI	multidict	`6.7.1`	indirect
PyPI	munch	`4.0.0`	indirect
PyPI	narwhals	`2.16.0`	indirect
PyPI	nbclient	`0.10.4`	indirect
PyPI	nbconvert	`7.17.0`	indirect
PyPI	nbformat	`5.10.4`	indirect
PyPI	nbsphinx	`0.9.8`	indirect
PyPI	nodeenv	`1.10.0`	indirect
PyPI	numpy	`2.2.6`	indirect
PyPI	numpy	`2.4.2`	indirect
PyPI	opyplus	`2.0.7`	indirect
PyPI	packaging	`26.0`	indirect
PyPI	pandas	`2.3.3`	indirect
PyPI	pandas-stubs	`2.3.3.260113`	indirect
PyPI	pandas-stubs	`3.0.0.260204`	indirect
PyPI	pandocfilters	`1.5.1`	indirect
PyPI	pillow	`11.3.0`	indirect
PyPI	platformdirs	`4.5.1`	indirect
PyPI	plotly	`6.5.2`	indirect
PyPI	pluggy	`1.6.0`	indirect
PyPI	pre-commit	`4.5.1`	indirect
PyPI	propcache	`0.4.1`	indirect
PyPI	pycparser	`3.0`	indirect
PyPI	pydot	`4.0.1`	indirect
PyPI	pygments	`2.19.2`	indirect
PyPI	pyinstrument	`5.1.2`	indirect
PyPI	pyparsing	`3.3.2`	indirect
PyPI	pyproject-api	`1.10.0`	indirect
PyPI	pyright	`1.1.408`	indirect
PyPI	pytest	`9.0.2`	indirect
PyPI	pytest-asyncio	`1.3.0`	indirect
PyPI	pytest-cov	`7.0.0`	indirect
PyPI	python-dateutil	`2.9.0.post0`	indirect
PyPI	python-slugify	`5.0.2`	indirect
PyPI	pytz	`2025.2`	indirect
PyPI	pyyaml	`6.0.3`	indirect
PyPI	pyzmq	`27.1.0`	indirect
PyPI	referencing	`0.37.0`	indirect
PyPI	requests	`2.32.5`	indirect
PyPI	requirements-parser	`0.13.0`	indirect
PyPI	roman-numerals	`4.1.0`	indirect
PyPI	rpds-py	`0.30.0`	indirect
PyPI	ruff	`0.15.0`	indirect
PyPI	s3transfer	`0.16.0`	indirect
PyPI	six	`1.17.0`	indirect
PyPI	snowballstemmer	`3.0.1`	indirect
PyPI	soupsieve	`2.8.3`	indirect
PyPI	sphinx	`8.1.3`	indirect
PyPI	sphinx	`9.0.4`	indirect
PyPI	sphinx	`9.1.0`	indirect
PyPI	sphinxcontrib-applehelp	`2.0.0`	indirect
PyPI	sphinxcontrib-devhelp	`2.0.0`	indirect
PyPI	sphinxcontrib-htmlhelp	`2.1.0`	indirect
PyPI	sphinxcontrib-jsmath	`1.0.1`	indirect
PyPI	sphinxcontrib-qthelp	`2.0.0`	indirect
PyPI	sphinxcontrib-serializinghtml	`2.0.0`	indirect
PyPI	text-unidecode	`1.3`	indirect
PyPI	tinycss2	`1.4.0`	indirect
PyPI	tinynumpy	`1.2.1`	indirect
PyPI	tomli	`2.4.0`	indirect
PyPI	tornado	`6.5.4`	indirect
PyPI	tox	`4.34.1`	indirect
PyPI	tox-uv	`1.29.0`	indirect
PyPI	tqdm	`4.67.3`	indirect
PyPI	traitlets	`5.14.3`	indirect
PyPI	types-aiobotocore-s3	`3.1.2`	indirect
PyPI	types-awscrt	`0.31.1`	indirect
PyPI	types-boto3	`1.42.42`	indirect
PyPI	types-boto3-s3	`1.42.37`	indirect
PyPI	types-pytz	`2025.2.0.20251108`	indirect
PyPI	types-s3transfer	`0.16.0`	indirect
PyPI	typing-extensions	`4.15.0`	indirect
PyPI	tzdata	`2025.3`	indirect
PyPI	unidecode	`1.4.0`	indirect
PyPI	urllib3	`2.6.3`	indirect
PyPI	uv	`0.9.29`	indirect
PyPI	virtualenv	`20.36.1`	indirect
PyPI	webencodings	`0.5.1`	indirect
PyPI	wrapt	`2.1.1`	indirect
PyPI	yarl	`1.22.0`	indirect

Dependency advisories 16

This repository publishes no package the index resolves, so its own dependency graph was assessed — 140 packages, which also include development and test pins that never ship: 16 carry known advisories, of which 0 are direct.

Package	Version	Relation	Severity	Advisories	Fixed in
aiohttp	`3.13.3`	indirect	critical	48	`3.14.3`
pillow	`11.3.0`	indirect	critical	36	`12.3.0`
lxml	`6.0.2`	indirect	high	2	`6.1.0`
mistune	`3.2.0`	indirect	high	32	`3.3.0`
soupsieve	`2.8.3`	indirect	high	8	`2.9.0`
tornado	`6.5.4`	indirect	high	18	`6.5.9`
urllib3	`2.6.3`	indirect	high	10	`2.8.0`
virtualenv	`20.36.1`	indirect	high	8	`21.7.13`
bleach	`6.3.0`	indirect	moderate	3	`6.4.0`
idna	`3.11`	indirect	moderate	2	`3.15`
multidict	`6.7.1`	indirect	moderate	2	`6.9.1`
nbconvert	`7.17.0`	indirect	moderate	4	`7.17.1`
pytest	`9.0.2`	indirect	moderate	2	`9.0.3`
requests	`2.32.5`	indirect	moderate	2	`2.33.0`
uv	`0.9.29`	indirect	moderate	2	`0.11.15`
pygments	`2.19.2`	indirect	low	2	`2.20.0`

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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