Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-04 22:20 UTC

openai / whisper

Robust Speech Recognition via Large-Scale Weak Supervision

PythonMIT★ 106,632 stars⑂ 12,952 forkssince Sep 2022View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

openai/whisper holds a health index of 77 out of 100, placing it in the Good band. It scores highest on Community & Adoption (82/100) and lowest on Vitality (51/100). It was last updated 7 days ago. 4 contributors account for most of its recent work.

77
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.

77
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 66 is calibrated to 77 on the published index scale (record calibration 2026-08-02).

Ownership

OpenAIOrganization
128,583 followers268 public repossince Oct 2015

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIopenai-whisper202506254,295,66713404 days ago

Metrics by category

Vitality

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

51Moderate · 21% of overall
How it's scored
36/36Push recencylast push 7 days ago
2.1/36Commit cadence3/52 weeks with commits
6.3/18Commit volume4 commits in the last year
1/10OpenSSF Scorecard: Maintained2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
Inputs used
commits_last_year4
human_commit_share0.99
days_since_last_push7
active_weeks_last_year3
How it's scored
27/27Ships releases13 releases published
7.2/36Release recencylatest release 404 days ago
19.8/27Release cadencea release every ~93.4 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count13
latest_release_tagv20250625
releases_from_tagsno
days_since_latest_release404
mean_days_between_releases93.4
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?

82Excellent · 17% of overall

Popularity & adoption

100Exceptional
How it's scored
60/60Stars106,632 stars
25/25Forks12,952 forks
15/15Watchers754 watchers
Inputs used
forks12,952
stars106,632
watchers754
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized 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
80/80Monthly downloads4,295,667 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesopenai-whisper
dependents
ecosystemspypi
total_downloads
monthly_downloads4,295,667
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?

75Good · 23% of overall
How it's scored
43.2/54Bus factor4 contributor(s) cover half of all commits
12.8/22.5Commit distributiontop contributor authored 43% of commits
13.5/13.5Contributor breadth80 contributors
10/10OpenSSF Scorecard: Contributorsproject has 7 contributing companies or organizations
Inputs used
bus_factor4
contributors_sampled80
top_contributor_share0.431
How it's scored
0/42Issue resolutionno issues or no data
14/30PR acceptance122/261 decided PRs merged
1.4/13Newcomer PR acceptance1/9 first-time contributors' PRs merged in 30d
9/15OpenSSF Scorecard: Code-ReviewFound 18/29 approved changesets -- score normalized to 6
Inputs used
merged_prs122
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d3
prs_merged_30d1
prs_decided_30d9
issue_closed_ratio
closed_unmerged_prs139
first_time_authors_30d7
first_time_prs_merged_30d1
first_time_prs_decided_30d9
Excluded from scoring (no data or not applicable): Issue resolution. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
25/25Owner reach128,583 followers of openai
25/25Track record268 public repos, account ~10 yr old
Inputs used
followers128,583
owner_typeOrganization
is_verified
owner_loginopenai
public_repos268
account_age_days3,958
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
14/35Publish recencylatest publish 404 days ago
20/20Version history13 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesopenai-whisper
ecosystemspypi
any_deprecatedno
min_days_since_publish404

Engineering Quality

Are baseline engineering and documentation practices in place?

63Moderate · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
16/16Linter config.flake8
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
4/20OpenSSF Scorecard: CI-Tests6 out of 24 merged PRs checked by a CI test -- score normalized to 2
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics
has_wikino
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

62Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
0.5/2.5CI-Tests6 out of 24 merged PRs checked by a CI test -- score normalized to 2
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
4.5/7.5Code-ReviewFound 18/29 approved changesets -- score normalized to 6
2.5/2.5Contributorsproject has 7 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
0.8/7.5Maintained2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
0/5Packagingno data
2/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
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
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate5.3
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages14
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:openai-whisper@20250625 runtime dependency closure — what installing the published package pulls in — 14 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.

53Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
39.9/40Legible commit history74 of 99 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.747
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config.flake8
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance1 of the last 100 commits are automated dependency updates
4/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.01
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/20 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes32,155
source_files_sampled20
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesnotebooks
Inputs used
example_dirsnotebooks
has_mcp_signalno
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

106,632GitHub stars
80contributors
4commits, last 12 months
7days since last push
13releases
4bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 12,952 ⇿
0Stars
12,952Forks

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.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

11,50012,00012,50013,00012,952272026-042026-062026-08
OpenSSF Scorecard 5.3 / 10
5.3aggregate

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 · 2026-08-04 22:20 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
2CI-Tests6 out of 24 merged PRs checked by a CI test -- score normalized to 2
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6Code-ReviewFound 18/29 approved changesets -- score normalized to 6
10Contributorsproject has 7 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
1Maintained2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
n/aPackagingpackaging workflow not detected
4Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
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
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 7
RegistryPackageVersion constraintManifest
PyPImore-itertoolspyproject.toml
PyPInumbapyproject.toml
PyPInumpypyproject.toml
PyPItiktokenpyproject.toml
PyPItorchpyproject.toml
PyPItqdmpyproject.toml
PyPItriton>=2pyproject.toml
All dependencies 7

Full resolved dependency set from the GitHub dependency graph: 7 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPImore-itertoolsdirect
PyPInumbadirect
PyPInumpydirect
PyPItiktokendirect
PyPItorchdirect
PyPItqdmdirect
PyPItritondirect
Dependency advisories 0

Installing pypi:openai-whisper@20250625 pulls in 14 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.

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 v0.31.0 — full methodology · metrics wiki.

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