Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-22 18:35 UTC

phoongkhangzhie / research-vault

Research Vault — an AI research-assistant framework

PythonAGPL-3.0★ 7 stars⑂ 0 forkssince Jun 2026View on GitHub ↗
KindLibraryCommand-line toolhow this is determined

phoongkhangzhie/research-vault holds a health index of 53 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (66/100) and lowest on Community & Adoption (39/100). It was last updated 36 days ago. A single contributor accounts for most of its recent work.

53
overall / 100
Moderate

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.

53
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 52 is calibrated to 53 on the published index scale (record calibration 2026-08-02).

Ownership

Phoong Khang Zhie (He/Him)Personal account
0 followers1 public reposince Feb 2017

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 publishTags
PyPIresearch-vault0.3.72261937 days agoaibatteries-includedclidagllmresearchresearch-assistant

Metrics by category

Vitality

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

57Moderate · 21% of overall

Development activity

37Weak
How it's scored
18/36Push recency — last push 36 days ago
1.4/36Commit cadence — 2/52 weeks with commits
18/18Commit volume — 159 commits in the last year
0/10OpenSSF Scorecard: Maintained — project was created within the last 90 days. Please review its contents carefully
Inputs used
commits_last_year159
human_commit_share1
days_since_last_push36
active_weeks_last_year2

Release discipline

88Excellent
How it's scored
16.2/27Ships releases — 19 version tags (no GitHub releases)
36/36Release recency — latest release 37 days ago
27/27Release cadence — a release every ~0.8 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count19
latest_release_tagv0.3.7
releases_from_tagsyes
days_since_latest_release37
mean_days_between_releases0.8
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?

39Weak · 17% of overall

Popularity & adoption

13Critical
How it's scored
12.6/60Stars — 7 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars7
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

70Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (AGPL-3.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

39Weak
How it's scored
31.4/80Monthly downloads — 226 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesresearch-vault
dependents—
ecosystemspypi
total_downloads—
monthly_downloads226
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?

48Weak · 23% of overall

Maintainer resilience (bus factor)

14Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.4/22.5Commit distribution — top contributor authored 98% of commits
4.1/13.5Contributor breadth — 3 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.981

Issue & PR responsiveness

65Good
How it's scored
0/42Issue resolution — no issues or no data
29.2/30PR acceptance — 287/295 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs287
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio—
closed_unmerged_prs8
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

30At Risk
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
0/25Owner reach — 0 followers of phoongkhangzhie
14.2/25Track record — 1 public repos, account ~9 yr old
Inputs used
followers0
owner_typeUser
is_verified—
owner_loginphoongkhangzhie
public_repos1
account_age_days3,478
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 37 days ago
20/20Version history — 19 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesresearch-vault
ecosystemspypi
any_deprecatedno
min_days_since_publish37

Engineering Quality

Are baseline engineering and documentation practices in place?

66Good · 19% of overall

Engineering practices

66Good
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests — 27 out of 28 merged PRs checked by a CI test -- score normalized to 9
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

65Good
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://khangzhie.io
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepagehttps://khangzhie.io
docs_sitehttps://khangzhie.io
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

51Moderate · 16% of overall

Security posture

39Weak
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.2/2.5CI-Tests — 27 out of 28 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/30 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
0/7.5Maintained — project was created within the last 90 days. Please review its contents carefully
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
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_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate3.9
Excluded from scoring (no data or not applicable): Branch-Protection, 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_packages166
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:research-vault@0.3.7 runtime dependency closure — what installing the published package pulls in — 166 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.

48Weak · 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 — 98 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.98
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

32At Risk
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
10/10Demonstrated agent practice — 28 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0.28
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

53Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
52.9/55Manageable file sizes — 13/341 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes189,250
source_files_sampled341
oversized_source_files13

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 — examples
Inputs used
example_dirsexamples
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

7GitHub stars
3contributors
159commits, last 12 months
36days since last push
19releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

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

More detail

OpenSSF Scorecard 3.9 / 10
3.9aggregate

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 · 2026-08-22 18:34 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
9CI-Tests27 out of 28 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
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
10Licenselicense file detected
0Maintainedproject was created within the last 90 days. Please review its contents carefully
10Packagingpackaging workflow 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
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 29
RegistryPackageVersion constraintManifest
PyPIanthropic>=0.25pyproject.toml
PyPIlitellm>=1.30pyproject.toml
PyPItiktoken>=0.6pyproject.toml
PyPIscikit-learn>=1.4pyproject.toml
PyPIdatasets>=2.18pyproject.toml
PyPIpandas>=2.1pyproject.toml
PyPInumpy>=1.26pyproject.toml
PyPIpyarrow>=15.0pyproject.toml
PyPIscipy>=1.11pyproject.toml
PyPIstatsmodels>=0.14pyproject.toml
PyPIinspect-ai>=0.3pyproject.toml
PyPIevaluate>=0.4pyproject.toml
PyPIsacrebleu>=2.3pyproject.toml
PyPIrouge-score>=0.1pyproject.toml
PyPIsentencepiece>=0.1pyproject.toml
PyPIsacremoses>=0.0.53pyproject.toml
PyPIlangdetect>=1.0pyproject.toml
PyPIwandb>=0.16pyproject.toml
PyPIweave>=0.53.1pyproject.toml
PyPIpyzotero>=1.5pyproject.toml
PyPIkeyring>=24.0pyproject.toml
PyPItenacity>=8.2pyproject.toml
PyPItqdm>=4.65pyproject.toml
PyPIorjson>=3.9pyproject.toml
PyPIpydantic>=2.5pyproject.toml
PyPIjinja2>=3.1pyproject.toml
PyPIrich>=13.7pyproject.toml
PyPIpython-dotenv>=1.0pyproject.toml
PyPIpymupdf>=1.24pyproject.toml
All dependencies 40

Full resolved dependency set from the GitHub dependency graph: 29 direct and 11 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIanthropic—direct
PyPIdatasets—direct
PyPIevaluate—direct
PyPIinspect-ai—direct
PyPIjinja2—direct
PyPIkeyring—direct
PyPIlangdetect—direct
PyPIlitellm—direct
PyPInumpy—direct
PyPIorjson—direct
PyPIpandas—direct
PyPIpyarrow—direct
PyPIpydantic—direct
PyPIpymupdf—direct
PyPIpython-dotenv—direct
PyPIpyzotero—direct
PyPIrich—direct
PyPIrouge-score—direct
PyPIsacrebleu—direct
PyPIsacremoses—direct
PyPIscikit-learn—direct
PyPIscipy—direct
PyPIsentencepiece—direct
PyPIstatsmodels—direct
PyPItenacity—direct
PyPItiktoken—direct
PyPItqdm—direct
PyPIwandb—direct
PyPIweave—direct
PyPIaccelerate—indirect
PyPIbert-score—indirect
PyPIfasttext—indirect
PyPIhuggingface-hub—indirect
PyPIlm-eval—indirect
PyPIpytest—indirect
PyPIpytest-forked—indirect
PyPIsglang—indirect
PyPItorch—indirect
PyPItransformers—indirect
PyPIvllm—indirect
Dependency advisories 0

Installing pypi:research-vault@0.3.7 pulls in 166 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

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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.