Public record
Software health reportschema 0.27.0 · metrics 2.5.0 · 2026-07-30 22:12 UTC

kaitai-io / kaitai_struct_python_runtime

Kaitai Struct: runtime for Python

PythonMIT★ 107 stars⑂ 32 forkssince Feb 2016View on GitHub ↗

kaitai-io/kaitai_struct_python_runtime holds a health index of 63 out of 100, placing it in the Moderate band. It scores highest on Sustainability & Governance (71/100) and lowest on AI Readiness (27/100). It was last updated today. 2 contributors account for most of its recent work.

63
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.

63
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 59 is calibrated to 63 on the published index scale (record calibration 2026-08-02).

Ownership

Kaitai teamOrganization
201 followers59 public repossince Feb 2016

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIkaitaistruct0.118,087,6279325 days agokaitaistructconstructksydeclarativedata-structuredata-formatfile-formatpacket-formatbinaryparserparsingunpackdevelopment

Metrics by category

Vitality

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

42Weak · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
9/36Commit cadence — 13/52 weeks with commits
16/18Commit volume — 59 commits in the last year
8/10OpenSSF Scorecard: Maintained — 10 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 8
Inputs used
commits_last_year59
human_commit_share0.95
days_since_last_push0
active_weeks_last_year13
How it's scored
0/27Ships releases — no releases published
0/36Release recency — no releases
0/27Release cadence — no releases
0/10OpenSSF Scorecard: Signed-Releases — no 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?

63Moderate · 17% of overall
How it's scored
32.9/60Stars — 107 stars
12.4/25Forks — 32 forks
6/15Watchers — 13 watchers
Inputs used
forks32
stars107
watchers13
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_badges
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno
How it's scored
80/80Monthly downloads — 8,087,627 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packageskaitaistruct
dependents
ecosystemspypi
total_downloads
monthly_downloads8,087,627
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?

71Good · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
11.8/22.5Commit distribution — top contributor authored 48% of commits
13.5/13.5Contributor breadth — 13 contributors
10/10OpenSSF Scorecard: Contributors — project has 32 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled13
top_contributor_share0.475
How it's scored
31.9/42Issue resolution — 76% of issues closed
25.4/30PR acceptance — 39/46 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/25 approved changesets -- score normalized to 0
Inputs used
merged_prs39
open_issues7
closed_issues22
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.759
closed_unmerged_prs7
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
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
16.6/25Owner reach — 201 followers of kaitai-io
24.9/25Track record — 59 public repos, account ~10 yr old
Inputs used
followers201
owner_typeOrganization
is_verified
owner_loginkaitai-io
public_repos59
account_age_days3,815
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
26/35Publish recency — latest publish 325 days ago
20/20Version history — 9 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packageskaitaistruct
ecosystemspypi
any_deprecatedno
min_days_since_publish325

Engineering Quality

Are baseline engineering and documentation practices in place?

56Moderate · 19% of overall
How it's scored
24/24CI workflows — 3 workflow(s)
0/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
6.4/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 5 out of 5 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsno
has_editorconfigyes
has_linter_configno
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://pypi.org/project/kaitaistruct/
10/10Repository description
10/10Topics — 2 topics
0/10Wiki
Inputs used
topicskaitai-struct, python
has_wikino
homepagehttps://pypi.org/project/kaitaistruct/
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

70Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 5 out of 5 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 0/25 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 32 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
6/7.5Maintained — 10 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 8
5/5Packaging — packaging workflow detected
2.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
5/5SAST — SAST tool is run on all commits
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate7
Excluded from scoring (no data or not applicable): signed_releases. 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.

27At Risk · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
32/40Legible commit history — 57 of 95 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
legible_history_share0.6
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
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 5 of the last 100 commits are automated dependency updates
5/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
Inputs used
has_nixno
has_testsno
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.05
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/2 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes41,261
source_files_sampled2
oversized_source_files0

Key facts

107GitHub stars
13contributors
59commits, last 12 months
0days since last push
0releases
2bus factor
7open 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 ★ / 32 ⇿
0Stars
32Forks

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.

01325383222016-082021-012025-06

Each point covers 9 days.

OpenSSF Scorecard 7.0 / 10
7.0aggregate

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 · 2026-07-30 22:12 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests5 out of 5 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 0/25 approved changesets -- score normalized to 0
10Contributorsproject has 32 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
8Maintained10 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 8
10Packagingpackaging workflow detected
5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 5
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 0

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

RegistryPackageVersionRelation
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies to assess

Raw JSON report machine-readable

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 v2.5.0, schema v0.27.0 — full methodology · metrics wiki.

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