Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-13 16:24 UTC

jmcollin78 / vtherm_api

The API of the Versatile Thermostat integration for Home Assistant

PythonMIT★ 0 stars⑂ 3 forkssince Apr 2026View on GitHub ↗

jmcollin78/vtherm_api holds a health index of 47 out of 100, placing it in the Weak band. It scores highest on Vitality (70/100) and lowest on Security (1/100). It was last updated today. A single contributor accounts for most of its recent work.

47
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.

47
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 48 is calibrated to 47 on the published index scale (record calibration 2026-08-02).

Ownership

Jean-Marc CollinPersonal account
170 followers23 public repossince May 2012Clouderial

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIvtherm_api0.6.134,502100 days agohome-assistantthermostathvacversatile-thermostat

Metrics by category

Vitality

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

70Good · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
4.2/36Commit cadence — 6/52 weeks with commits
14.1/18Commit volume — 36 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year36
human_commit_share1
days_since_last_push0
active_weeks_last_year6
How it's scored
27/27Ships releases — 2 releases published
36/36Release recency — latest release 20 days ago
12.6/27Release cadence — a release every ~153 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count2
latest_release_tag0.5.0
releases_from_tagsno
days_since_latest_release20
mean_days_between_releases153

Community & Adoption

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

37Weak · 17% of overall
How it's scored
0/60Stars — 0 stars
2.5/25Forks — 3 forks
0/15Watchers — 0 watchers
Inputs used
forks3
stars0
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
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
How it's scored
60.5/80Monthly downloads — 34,502 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesvtherm_api
dependents—
ecosystemspypi
total_downloads—
monthly_downloads34,502
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?

55Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
9/22.5Commit distribution — top contributor authored 60% of commits
4.1/13.5Contributor breadth — 3 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.6
How it's scored
0/42Issue resolution — 0% of issues closed
30/30PR acceptance — 5/5 decided PRs merged
13/13Newcomer PR acceptance — 1/1 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs5
open_issues3
closed_issues0
prs_merged_7d2
prs_decided_7d2
prs_merged_30d2
prs_decided_30d2
issue_closed_ratio0
closed_unmerged_prs0
first_time_authors_30d1
first_time_prs_merged_30d1
first_time_prs_decided_30d1
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
16.1/25Owner reach — 170 followers of jmcollin78
22.1/25Track record — 23 public repos, account ~14 yr old
Inputs used
followers170
owner_typeUser
is_verified—
owner_loginjmcollin78
public_repos23
account_age_days5,272
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 10 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesvtherm_api
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

66Good · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
16/16Linter config — .pylintrc, pyproject.toml ([tool.black])
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://github.com/jmcollin78/vtherm_api
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepage—
docs_sitehttps://github.com/jmcollin78/vtherm_api
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

1Critical · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestspyproject.toml, requirements-dev.txt
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

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.

52Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
11.5/40Legible commit history — 8 of 37 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.216
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — .pylintrc, pyproject.toml ([tool.black])
11/11Static type checking — pyrightconfig.json
10/10Reproducible environment — devcontainer
10/10Demonstrated agent practice — 2 of the last 37 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontaineryes
has_linter_configyes
typecheck_configspyrightconfig.json
agent_commit_share0.054
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
27/45Type-checkable code — Python with type-check config (pyrightconfig.json)
55/55Manageable file sizes — 0/17 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes24,456
source_files_sampled17
oversized_source_files0

Key facts

0GitHub stars
3contributors
36commits, last 12 months
0days since last push
2releases
1bus factor
3open issues
PyPIpackage ecosystems

Data collection warnings

  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • deps.dev does not index pypi:vtherm_api@0.6.1; advisories assessed against the repository dependency graph instead
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Star and fork history 0 ★ / 3 ⇿
0Stars
3Forks
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.

12233312026-042026-072026-10
Major 0Minor 2Patch 0
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

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.

The message is kept through sign-in.

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.