Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-09 10:21 UTC

zhudotexe / fanoutqa

Companion code for FanOutQA: Multi-Hop, Multi-Document Question Answering for Large Language Models (ACL 2024)

Python · VueMIT★ 63 stars⑂ 7 forkssince Feb 2024View on GitHub ↗
KindWeb interfacehow this is determined
#benchmark#large-language-models#llms#natural-language-processing

zhudotexe/fanoutqa holds a health index of 45 out of 100, placing it in the Weak band. It scores highest on Engineering Quality (70/100) and lowest on Security (19/100). It was last updated 40 days ago. A single contributor accounts for most of its recent work.

45
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.

45
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 47 is calibrated to 45 on the published index scale (record calibration 2026-08-02).

Ownership

Andrew ZhuPersonal account
133 followers107 public repossince Sep 2014University of Pennsylvania

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 publish
PyPIfanoutqa1.1.11128698 days ago

Metrics by category

Vitality

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

48Weak · 21% of overall

Development activity

35Weak
How it's scored
18/36Push recency — last push 40 days ago
2.8/36Commit cadence — 4/52 weeks with commits
10.6/18Commit volume — 14 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year14
human_commit_share1
days_since_last_push40
active_weeks_last_year4

Release discipline

68Good
How it's scored
27/27Ships releases — 7 releases published
7.2/36Release recency — latest release 698 days ago
27/27Release cadence — a release every ~40 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count7
latest_release_tagv1.1.1
releases_from_tagsno
days_since_latest_release698
mean_days_between_releases40

Community & Adoption

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

40Weak · 17% of overall

Popularity & adoption

36Weak
How it's scored
29.1/60Stars — 63 stars
6.5/25Forks — 7 forks
0/15Watchers — 1 watchers
Inputs used
forks7
stars63
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
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_badges1
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

34At Risk
How it's scored
27.4/80Monthly downloads — 112 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesfanoutqa
dependents—
ecosystemspypi
total_downloads—
monthly_downloads112
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?

50Moderate · 23% of overall

Maintainer resilience (bus factor)

15Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.7/22.5Commit distribution — top contributor authored 97% of commits
4.1/13.5Contributor breadth — 3 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.97

Issue & PR responsiveness

55Moderate
How it's scored
14/42Issue resolution — 33% of issues closed
25.7/30PR acceptance — 12/14 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs12
open_issues4
closed_issues2
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.333
closed_unmerged_prs2
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

63Moderate
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
15.3/25Owner reach — 133 followers of zhudotexe
25/25Track record — 107 public repos, account ~11 yr old
Inputs used
followers133
owner_typeUser
is_verified—
owner_loginzhudotexe
public_repos107
account_age_days4,369
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

79Good
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
14/35Publish recency — latest publish 698 days ago
20/20Version history — 8 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesfanoutqa
ecosystemspypi
any_deprecatedno
min_days_since_publish698

Engineering Quality

Are baseline engineering and documentation practices in place?

70Good · 19% of overall

Engineering practices

50Moderate
How it's scored
24/24CI workflows — 4 workflow(s)
0/24Tests present
16/16Linter config — .eslintrc.cjs, pyproject.toml ([tool.black], [tool.isort])
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsno
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://fanoutqa.com/
10/10Repository description
10/10Topics — 4 topics
10/10Wiki
Inputs used
topicsbenchmark, large-language-models, llms, natural-language-processing
has_wikiyes
homepagehttps://fanoutqa.com/
docs_sitehttps://fanoutqa.com/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

19Critical · 16% of overall

Security posture

1Critical
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
lockfilespackage-lock.json
manifestsleaderboard/package.json, pyproject.toml, requirements.txt
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

Dependency advisories

89Excellent
How it's scored
26.9/35Direct dependencies free of known advisories — 1 affected: markdownify 0.11.6 (low 2.9)
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
37.3/40No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 500 days ago
Inputs used
sourceosv
advisories2
affected_packages1
assessed_packages50
unassessed_packages0
affected_by_severitylow 1
direct_affected_packages1
Matched the pypi:fanoutqa@1.1.1 runtime dependency closure — what installing the published package pulls in — 50 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.

62Moderate · 4% of overall

Agent context & guidance

40Weak
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 87 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.87
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

56Moderate
How it's scored
18/18One-command bootstrap — docs/Makefile
0/22Automated tests
11/11Lint / format config — .eslintrc.cjs, pyproject.toml ([tool.black], [tool.isort])
11/11Static type checking — leaderboard/tsconfig.json
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsno
lockfilespackage-lock.json
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configsleaderboard/tsconfig.json
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (leaderboard/tsconfig.json)
55/55Manageable file sizes — 0/44 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes10,607
source_files_sampled44
oversized_source_files0

Machine-readable interfaces

100Exceptional
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

63GitHub stars
3contributors
14commits, last 12 months
40days since last push
7releases
1bus factor
4open issues
npm, PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit; 2026/09/09 10:18:24 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 7 ⇿
0Stars
7Forks
6Releases

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.

123456612024-022025-042026-06
Major 0Minor 1Patch 5

Each point covers 3 days.

Direct dependencies 12
RegistryPackageVersion constraintManifest
npm@fortawesome/fontawesome-svg-core^6.1.2leaderboard/package.json
npm@fortawesome/free-brands-svg-icons^6.1.2leaderboard/package.json
npm@fortawesome/free-solid-svg-icons^6.1.2leaderboard/package.json
npm@fortawesome/vue-fontawesome^3.0.1leaderboard/package.json
npmbulma^0.9.4leaderboard/package.json
npmclick-outside-vue3^4.0.1leaderboard/package.json
npmvue^3.4.15leaderboard/package.json
PyPIftfy>=6.1.3,<=7.0.0pyproject.toml
PyPIhttpx>=0.26.0,<1.0.0pyproject.toml
PyPImarkdownify~=0.11.6pyproject.toml
PyPIpywikibot>=11.0.0,<12.0.0pyproject.toml
PyPIspacy>=3.7.2,<4.0.0pyproject.toml
All dependencies 312

Full resolved dependency set from the GitHub dependency graph: 12 direct and 300 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

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npmsource-map-js1.2.1indirect
npmstrip-ansi6.0.1indirect
npmstrip-json-comments3.1.1indirect
npmsupports-color7.2.0indirect
npmsynckit0.11.13indirect
npmtext-table0.2.0indirect
npmtinyglobby0.2.17indirect
npmto-regex-range5.0.1indirect
npmts-api-utils1.4.3indirect
npmtype-check0.4.0indirect
npmtype-fest0.20.2indirect
npmtypescript5.9.3indirect
npmundici-types6.21.0indirect
npmuri-js4.4.1indirect
npmutil-deprecate1.0.2indirect
npmvite7.3.6indirect
npmvscode-uri3.1.0indirect
npmvue-eslint-parser9.4.3indirect
npmvue-tsc3.3.8indirect
npmwhich2.0.2indirect
npmwhich3.0.1indirect
npmword-wrap1.2.5indirect
npmwrappy1.0.2indirect
npmxml-name-validator4.0.0indirect
npmyocto-queue0.1.0indirect
PyPIaccelerate—indirect
PyPIaiolimiter—indirect
PyPIanthropic—indirect
PyPIbeautifulsoup4—indirect
PyPIblack—indirect
PyPIbleurt—indirect
PyPIbuild—indirect
PyPIen-core-web-sm—indirect
PyPIfuro—indirect
PyPIisort—indirect
PyPIkani—indirect
PyPImatplotlib—indirect
PyPImyst-parser—indirect
PyPIopenai—indirect
PyPIprotobuf—indirect
PyPIpymediawiki—indirect
PyPIrank-bm25—indirect
PyPIrouge-score—indirect
PyPIsentencepiece—indirect
PyPIsphinx—indirect
PyPIsphinx-copybutton—indirect
PyPIsphinx-inline-tabs—indirect
PyPIsphinx-sitemap—indirect
PyPIsphinxemoji—indirect
PyPIsphinxext-opengraph—indirect
PyPItiktoken—indirect
PyPItorch—indirect
PyPItqdm—indirect
PyPItransformers—indirect
PyPItwine—indirect
Dependency advisories 1

Installing pypi:fanoutqa@1.1.1 pulls in 50 packages, direct and transitive: 1 carry known advisories, of which 1 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
markdownify0.11.6directlow20.14.1

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.

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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.