Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-02 05:55 UTC

psykei / psyke-python

PSyKE: a (Python) platform for symbolic knowledge extraction

PythonApache-2.0★ 21 stars⑂ 7 forkssince Oct 2021View on GitHub ↗

psykei/psyke-python holds a health index of 67 out of 100, placing it in the Good band. It scores highest on Vitality (83/100) and lowest on AI Readiness (43/100). It was last updated today. A single contributor accounts for most of its recent work.

67
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.

67
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 61 is calibrated to 67 on the published index scale (record calibration 2026-08-02).

Ownership

4 followers6 public repossince Oct 2021

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIpsyke1.0.43,962476339 days agoknowledge-extractionsymbolic-aiskeextractorrulesprolog

Metrics by category

Vitality

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

83Excellent · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
15.1/36Commit cadence — 35/52 weeks with commits, discounted for automation: 25 of the last 100 commits human-authored, spanning 339 days
11.2/18Commit volume — 141 commits in the last year, discounted for automation: 25 of the last 100 commits human-authored, spanning 339 days
10/10OpenSSF Scorecard: Maintained — 20 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year141
human_commit_share0.25
days_since_last_push0
active_weeks_last_year35

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~5.5 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tag1.0.4.dev70
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases5.5
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?

44Weak · 17% of overall
How it's scored
21.1/60Stars — 21 stars
6.5/25Forks — 7 forks
0/15Watchers — 1 watchers
Inputs used
forks7
stars21
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
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
48/80Monthly downloads — 3,962 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespsyke
dependents—
ecosystemspypi
total_downloads—
monthly_downloads3,962
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?

57Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
6.3/22.5Commit distribution — top contributor authored 72% of commits
8.1/13.5Contributor breadth — 6 contributors
10/10OpenSSF Scorecard: Contributors — project has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled6
top_contributor_share0.72
How it's scored
26.7/42Issue resolution — 64% of issues closed
28.7/30PR acceptance — 415/434 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_prs415
open_issues32
closed_issues56
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.636
closed_unmerged_prs19
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.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
5/25Owner reach — 4 followers of psykei
16.1/25Track record — 6 public repos, account ~4 yr old
Inputs used
followers4
owner_typeOrganization
is_verifiedno
owner_loginpsykei
public_repos6
account_age_days1,809
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
26/35Publish recency — latest publish 339 days ago
20/20Version history — 476 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespsyke
ecosystemspypi
any_deprecatedno
min_days_since_publish339

Engineering Quality

Are baseline engineering and documentation practices in place?

61Moderate · 19% of overall
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
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?

61Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
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
2.5/2.5Contributors — project has 3 contributing companies or organizations -- score normalized to 10
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
7.5/7.5Maintained — 20 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
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_aggregate5.1
Excluded from scoring (no data or not applicable): 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_packages17
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:psyke@1.0.4 runtime dependency closure — what installing the published package pulls in — 17 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.

43Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 19 of 25 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.76
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 75 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.75
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/66 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes26,275
source_files_sampled66
oversized_source_files0

Key facts

21GitHub stars
6contributors
141commits, last 12 months
0days since last push
100releases
1bus factor
32open 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 ★ / 7 ⇿
0Stars
7Forks

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.

1234567712021-102023-042024-10

Each point covers 3 days.

OpenSSF Scorecard 5.1 / 10
5.1aggregate

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 · 2026-10-02 05:55 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained20 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not 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
All dependencies 27

Full resolved dependency set from the GitHub dependency graph: 0 direct and 27 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPI2ppy—indirect
PyPI2ppy0.4.1indirect
PyPIbuild1.6.1indirect
PyPIdeap1.4.4indirect
PyPIjoblib—indirect
PyPIkeras—indirect
PyPIkneed—indirect
PyPIkneed0.8.6indirect
PyPImatplotlib3.11.2indirect
PyPIml-dtypes—indirect
PyPInumpy—indirect
PyPInumpy2.3.5indirect
PyPIonnx1.23.1indirect
PyPIonnxconverter-common1.16.0indirect
PyPIonnxruntime1.30.0indirect
PyPIpandas—indirect
PyPIpandas3.0.6indirect
PyPIparameterized0.9.0indirect
PyPIprotobuf—indirect
PyPIscikit-fuzzy0.5.0indirect
PyPIscikit-learn—indirect
PyPIsetuptools84.0.0indirect
PyPIskl2onnx1.20.0indirect
PyPIsympy—indirect
PyPIsympy1.14.0indirect
PyPItensorflow2.21.0indirect
PyPItwine7.0.0indirect
Dependency advisories 0

Installing pypi:psyke@1.0.4 pulls in 17 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.