Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-04 22:31 UTC

karpathy / autoresearch

AI agents running research on single-GPU nanochat training automatically

Python · Jupyter NotebookNo license detected★ 93,082 stars⑂ 13,244 forkssince Mar 2026View on GitHub ↗

karpathy/autoresearch holds a health index of 26 out of 100, placing it in the At Risk band. It scores highest on Community & Adoption (65/100) and lowest on Security (15/100). It was last updated 131 days ago. A single contributor accounts for most of its recent work.

26
overall / 100
At Risk

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.

26
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 32 is calibrated to 26 on the published index scale (record calibration 2026-08-02).

Ownership

AndrejPersonal account
214,752 followers63 public repossince Apr 2010

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?

17Critical · 21% of overall
How it's scored
9.9/36Push recencylast push 131 days ago
2.8/36Commit cadence4/52 weeks with commits
14.1/18Commit volume36 commits in the last year
1/10OpenSSF Scorecard: Maintained0 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 1
Inputs used
commits_last_year36
human_commit_share1
days_since_last_push131
active_weeks_last_year4
How it's scored
0/27Ships releasesno releases published
0/36Release recencyno releases
0/27Release cadenceno releases
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count0
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?

65Good · 17% of overall

Popularity & adoption

100Exceptional
How it's scored
60/60Stars93,082 stars
25/25Forks13,244 forks
15/15Watchers718 watchers
Inputs used
forks13,244
stars93,082
watchers718
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
0/22.5Licenseno license file detected
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseno
readme_badges0
has_contributingno
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?

42Weak · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
5/22.5Commit distributiontop contributor authored 78% of commits
12.2/13.5Contributor breadth9 contributors
0/10OpenSSF Scorecard: Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled9
top_contributor_share0.778
How it's scored
21.8/42Issue resolution52% of issues closed
0.8/30PR acceptance7/262 decided PRs merged
0/13Newcomer PR acceptance0/7 first-time contributors' PRs merged in 30d
4.5/15OpenSSF Scorecard: Code-ReviewFound 7/22 approved changesets -- score normalized to 3
Inputs used
merged_prs7
open_issues54
closed_issues58
prs_merged_7d0
prs_decided_7d1
prs_merged_30d0
prs_decided_30d7
issue_closed_ratio0.518
closed_unmerged_prs255
first_time_authors_30d7
first_time_prs_merged_30d0
first_time_prs_decided_30d7
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
25/25Owner reach214,752 followers of karpathy
25/25Track record63 public repos, account ~16 yr old
Inputs used
followers214,752
owner_typeUser
is_verified
owner_loginkarpathy
public_repos63
account_age_days5,960
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

21At Risk · 19% of overall
How it's scored
0/24CI workflows
0/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 7 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsno
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
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?

15Critical · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
0/2.5CI-Tests0 out of 7 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
2.2/7.5Code-ReviewFound 7/22 approved changesets -- score normalized to 3
0/2.5Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
0/10Dangerous-Workflowno data
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
0/2.5Licenselicense file not detected
0.8/7.5Maintained0 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 1
0/5Packagingno data
0/5Pinned-Dependenciesno data
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-Permissionsno data
0/7.5Vulnerabilities29 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated13
scorecard_versionv5.5.0
checks_inconclusive5
scorecard_aggregate1.5
Excluded from scoring (no data or not applicable): Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. 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.

36Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
11.9/40Legible commit history8 of 36 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.222
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
0/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environmentlockfile
10/10Demonstrated agent practice3 of the last 36 commits agent-authored or agent-credited
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsno
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0.083
toolchain_manifests
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/2 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes26,230
source_files_sampled2
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

93,082GitHub stars
9contributors
36commits, last 12 months
131days since last push
0releases
1bus factor
54open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Could not fetch pypi package 'autoresearch' from its registry
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

More detail

Star and fork history 0 ★ / 13,244 ⇿
0Stars
13,244Forks

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.

12,25012,50012,75013,00013,25013,244422026-062026-072026-08
OpenSSF Scorecard 1.5 / 10
1.5aggregate

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 · 2026-08-04 22:31 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 7 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 7/22 approved changesets -- score normalized to 3
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
0Licenselicense file not detected
1Maintained0 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 1
n/aPackagingpackaging workflow not detected
n/aPinned-Dependenciesno dependencies found
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
0Vulnerabilities29 existing vulnerabilities detected
Direct dependencies 9
RegistryPackageVersion constraintManifest
PyPIkernels>=0.11.7pyproject.toml
PyPImatplotlib>=3.10.8pyproject.toml
PyPInumpy>=2.2.6pyproject.toml
PyPIpandas>=2.3.3pyproject.toml
PyPIpyarrow>=21.0.0pyproject.toml
PyPIrequests>=2.32.0pyproject.toml
PyPIrustbpe>=0.1.0pyproject.toml
PyPItiktoken>=0.11.0pyproject.toml
PyPItorch==2.9.1pyproject.toml
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 v0.31.0 — full methodology · metrics wiki.

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