Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-16 13:45 UTC

openai / whisper

Robust Speech Recognition via Large-Scale Weak Supervision

PythonMIT★ 109,218 stars⑂ 13,238 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 (49/100). It was last updated 15 days ago. 5 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 · verified domain
133,632 followers272 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-whisper202506254,295,66713447 days ago

Metrics by category

Vitality

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

49Weak · 21% of overall
How it's scored
28.8/36Push recency — last push 15 days ago
2.8/36Commit cadence — 4/52 weeks with commits
7/18Commit volume — 5 commits in the last year
2/10OpenSSF Scorecard: Maintained — 3 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 2
Inputs used
commits_last_year5
human_commit_share0.99
days_since_last_push15
active_weeks_last_year4
How it's scored
27/27Ships releases — 13 releases published
7.2/36Release recency — latest release 447 days ago
19.8/27Release cadence — a release every ~93.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count13
latest_release_tagv20250625
releases_from_tagsno
days_since_latest_release447
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
60/60Stars — 109,218 stars
25/25Forks — 13,238 forks
15/15Watchers — 783 watchers
Inputs used
forks13,238
stars109,218
watchers783
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
80/80Monthly downloads — 4,295,667 downloads/month across pypi
0/20Registry dependents — not 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?

77Good · 23% of overall
How it's scored
45.9/54Bus factor — 5 contributor(s) cover half of all commits
12.9/22.5Commit distribution — top contributor authored 43% of commits
13.5/13.5Contributor breadth — 82 contributors
10/10OpenSSF Scorecard: Contributors — project has 7 contributing companies or organizations
Inputs used
bus_factor5
contributors_sampled82
top_contributor_share0.426
How it's scored
0/42Issue resolution — no issues or no data
13.9/30PR acceptance — 123/266 decided PRs merged
3.2/13Newcomer PR acceptance — 1/4 first-time contributors' PRs merged in 30d
9/15OpenSSF Scorecard: Code-Review — Found 19/29 approved changesets -- score normalized to 6
Inputs used
merged_prs123
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d1
prs_merged_30d1
prs_decided_30d4
issue_closed_ratio—
closed_unmerged_prs143
first_time_authors_30d4
first_time_prs_merged_30d1
first_time_prs_decided_30d4
Excluded from scoring (no data or not applicable): Issue resolution. Remaining weights renormalized.
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
25/25Owner reach — 133,632 followers of openai
25/25Track record — 272 public repos, account ~10 yr old
Inputs used
followers133,632
owner_typeOrganization
is_verifiedyes
owner_loginopenai
public_repos272
account_age_days4,000
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
14/35Publish recency — latest publish 447 days ago
20/20Version history — 13 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesopenai-whisper
ecosystemspypi
any_deprecatedno
min_days_since_publish447

Engineering Quality

Are baseline engineering and documentation practices in place?

62Moderate · 19% of overall
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
16/16Linter config — .flake8, pyproject.toml ([tool.black], [tool.isort])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
2/20OpenSSF Scorecard: CI-Tests — 4 out of 24 merged PRs checked by a CI test -- score normalized to 1
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?

63Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
0.2/2.5CI-Tests — 4 out of 24 merged PRs checked by a CI test -- score normalized to 1
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
4.5/7.5Code-Review — Found 19/29 approved changesets -- score normalized to 6
2.5/2.5Contributors — project has 7 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
1.5/7.5Maintained — 3 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 2
0/5Packaging — no data
2/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate5.4
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 advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages41
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 — 41 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.

54Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
39.9/40Legible commit history — 74 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, pyproject.toml ([tool.black], [tool.isort])
0/11Static type checking
0/10Reproducible environment
2/10Demonstrated agent practice — 1 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 1 of the last 100 commits are automated dependency updates
4/10OpenSSF Scorecard: Pinned-Dependencies — dependency 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_share0.01
toolchain_manifests—
dependency_bot_commit_share0.01
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/20 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 server — not applicable to this kind of software
40/40Runnable examples — notebooks
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

109,218GitHub stars
82contributors
5commits, last 12 months
15days since last push
13releases
5bus 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 'openai-whisper' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • pypi download figures for openai-whisper carried forward from the previous scan (stats endpoint unavailable this scan)

More detail

Star and fork history 0 ★ / 13,238 ⇿
0Stars
13,238Forks

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.

12,00012,25012,50012,75013,00013,25013,238222026-062026-072026-09
OpenSSF Scorecard 5.4 / 10
5.4aggregate

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 · 2026-09-16 13:44 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
1CI-Tests4 out of 24 merged PRs checked by a CI test -- score normalized to 1
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6Code-ReviewFound 19/29 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
2Maintained3 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 2
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-itertools—pyproject.toml
PyPInumba—pyproject.toml
PyPInumpy—pyproject.toml
PyPItiktoken—pyproject.toml
PyPItorch—pyproject.toml
PyPItqdm—pyproject.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-itertools—direct
PyPInumba—direct
PyPInumpy—direct
PyPItiktoken—direct
PyPItorch—direct
PyPItqdm—direct
PyPItriton—direct
Dependency advisories 0

Installing pypi:openai-whisper@20250625 pulls in 41 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 v0.34.0 — full methodology · metrics wiki.

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