Public record
Software health reportschema 0.13.0 · metrics 2.10.0 · 2026-07-18 16:16 UTC

HenestrosaDev / audiotext

A desktop application that transcribes audio from files, microphone input or YouTube videos with the option to translate the content and create subtitles.

PythonCustom license★ 351 stars⑂ 31 forkssince Jan 2023View on GitHub ↗

HenestrosaDev/audiotext holds a health index of 38 out of 100, placing it in the Weak band. It scores highest on Engineering Quality (64/100) and lowest on AI Readiness (16/100). It was last updated 641 days ago. A single contributor accounts for most of its recent work.

38
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.

38
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 42 is calibrated to 38 on the published index scale (record calibration 2026-08-02).

Ownership

HenestrosaDevPersonal account
67 followers14 public repossince Jan 2020

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

Metrics by category

Vitality

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

25At Risk · 21% of overall
How it's scored
0/36Push recencylast push 641 days ago
0/36Commit cadence0/52 weeks with commits
0/18Commit volume0 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share
days_since_last_push641
active_weeks_last_year0
How it's scored
27/27Ships releases14 releases published
7.2/36Release recencylatest release 717 days ago
19.8/27Release cadencea release every ~53.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count14
latest_release_tagv2.3.0
releases_from_tagsno
days_since_latest_release717
mean_days_between_releases53.8
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?

61Moderate · 17% of overall
How it's scored
41.3/60Stars351 stars
12.3/25Forks31 forks
5.8/15Watchers12 watchers
Inputs used
forks31
stars351
watchers12
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5Licenselicense file present, not a recognized license
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingyes
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?

43Weak · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
0.1/22.5Commit distributiontop contributor authored 100% of commits
4.1/13.5Contributor breadth3 contributors
0/10OpenSSF Scorecard: Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.996
How it's scored
29.3/42Issue resolution70% of issues closed
28.5/30PR acceptance37/39 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
1.5/15OpenSSF Scorecard: Code-ReviewFound 1/9 approved changesets -- score normalized to 1
Inputs used
merged_prs37
open_issues10
closed_issues23
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.697
closed_unmerged_prs2
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
13.2/25Owner reach67 followers of HenestrosaDev
20.6/25Track record14 public repos, account ~6 yr old
Inputs used
followers67
owner_typeUser
is_verified
owner_loginHenestrosaDev
public_repos14
account_age_days2,360
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

64Moderate · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
0/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 9 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsno
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics11 topics
10/10Wiki
Inputs used
topicscustomtkinter, python, speech-recognition, audio-to-text, video-to-text, transcriber, speech-to-text, speech-to-text-api, subtitles-generator, whisperx, ffmpeg
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

24At Risk · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
0/2.5CI-Tests0 out of 9 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-ReviewFound 1/9 approved changesets -- score normalized to 1
0/2.5Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.2/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities23 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate2.4
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. 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.

16Critical · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit historyno data
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
0/18One-command bootstrap
0/22Automated tests
11/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno data
0/8Automated maintenanceno data
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsno
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/34 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes55,169
source_files_sampled34
oversized_source_files0

Key facts

351GitHub stars
3contributors
0commits, last 12 months
641days since last push
14releases
1bus factor
10open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 2.4 / 10
2.4aggregate

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 · 2026-07-18 16:16 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal 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
0CI-Tests0 out of 9 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 1/9 approved changesets -- score normalized to 1
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not 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
0Vulnerabilities23 existing vulnerabilities detected
All dependencies 14

Full resolved dependency set from the GitHub dependency graph: 0 direct and 14 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcustomtkinter5.2.1indirect
PyPImoviepy1.0.3indirect
PyPImypy1.11.0indirect
PyPIopenai1.36.0indirect
PyPIpre-commit3.7.1indirect
PyPIpyaudio0.2.14indirect
PyPIpydub0.25.1indirect
PyPIpython-dotenv1.0.1indirect
PyPIpytubefix6.5.2indirect
PyPIspeechrecognition3.9.0indirect
PyPItorch2.2.1indirect
PyPItorchaudio2.2.1indirect
PyPItorchvision0.17.1indirect
PyPIwhisperx3.1.5indirect
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 v0.13.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics.