Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-15 20:02 UTC

crabisoft / pdbstore

Publish PDB and PE files to symbols store

PythonMIT★ 2 stars⑂ 0 forkssince Oct 2023View on GitHub ↗
KindLibraryhow this is determined
#pdb#symbols#windows#pdbstore#pefiles#symstore

crabisoft/pdbstore holds a health index of 44 out of 100, placing it in the Weak band. It scores highest on Engineering Quality (100/100) and lowest on Security (1/100). It was last updated 93 days ago. A single contributor accounts for most of its recent work.

44
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.

44
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 46 is calibrated to 44 on the published index scale (record calibration 2026-08-02).

Ownership

CrabiSoftOrganization
0 followers4 public repossince Oct 2023

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIpdbstore1.1.0-9808 days agodevelopmentsymstorepdbpdbstore

Metrics by category

Vitality

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

33At Risk · 21% of overall

Development activity

15Critical
How it's scored
9.9/36Push recency — last push 93 days ago
0.7/36Commit cadence — 1/52 weeks with commits
2.7/18Commit volume — 1 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year1
human_commit_share—
days_since_last_push93
active_weeks_last_year1

Release discipline

60Moderate
How it's scored
27/27Ships releases — 9 releases published
0/36Release recency — latest release 808 days ago
27/27Release cadence — a release every ~23.3 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count9
latest_release_tagv1.1.0
releases_from_tagsno
days_since_latest_release808
mean_days_between_releases23.3

Community & Adoption

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

33At Risk · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 2 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars2
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 (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges—
has_contributingyes
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?

56Moderate · 23% of overall

Maintainer resilience (bus factor)

15Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
1.8/22.5Commit distribution — top contributor authored 92% of commits
2.7/13.5Contributor breadth — 2 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.921

Issue & PR responsiveness

100Exceptional
How it's scored
0/42Issue resolution — no issues or no data
30/30PR acceptance — 31/31 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_prs31
open_issues0
closed_issues0
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio—
closed_unmerged_prs0
first_time_authors_30d—
first_time_prs_merged_30d—
first_time_prs_decided_30d—
Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

51Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
0/25Owner reach — 0 followers of crabisoft
10.6/25Track record — 4 public repos, account ~2 yr old
Inputs used
followers0
owner_typeOrganization
is_verified—
owner_logincrabisoft
public_repos4
account_age_days1,013
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

69Good
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
4/35Publish recency — latest publish 808 days ago
20/20Version history — 9 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespdbstore
ecosystemspypi
any_deprecatedno
min_days_since_publish808

Engineering Quality

Are baseline engineering and documentation practices in place?

100Exceptional · 19% of overall

Engineering practices

100Exceptional
How it's scored
24/24CI workflows — 6 workflow(s)
24/24Tests present
16/16Linter config — tox.ini
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://pdbstore.readthedocs.io/
10/10Repository description
10/10Topics — 6 topics
10/10Wiki
Inputs used
topicspdb, symbols, windows, pdbstore, pefiles, symstore
has_wikiyes
homepagehttps://pdbstore.readthedocs.io/
docs_sitehttps://pdbstore.readthedocs.io/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

1Critical · 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
lockfiles—
manifestspyproject.toml, requirements-dev.txt, requirements-doc.txt, requirements-lint.txt, requirements-test.txt, requirements.txt, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. 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.

43Weak · 4% of overall

Agent context & guidance

1Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share—
agent_instruction_files—
agent_instruction_max_bytes—
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

71Good
How it's scored
18/18One-command bootstrap — Makefile, docs/Makefile
22/22Automated tests
11/11Lint / format config — tox.ini
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share—
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/84 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes17,804
source_files_sampled84
oversized_source_files0

Key facts

2GitHub stars
2contributors
1commits, last 12 months
93days since last push
9releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPIcolorama—pyproject.toml
PyPIpefile—pyproject.toml
PyPIJinja2—pyproject.toml
All dependencies 27

Full resolved dependency set from the GitHub dependency graph: 3 direct and 24 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcolorama—direct
PyPIjinja2—direct
PyPIpefile—direct
PyPIblack24.3.0indirect
PyPIbuild1.0.3indirect
PyPIcommitizen3.20.0indirect
PyPIcoverage—indirect
PyPIflake87.0.0indirect
PyPIisort5.13.2indirect
PyPImock—indirect
PyPImypy1.9.0indirect
PyPImyst-parser—indirect
PyPIpylint3.1.0indirect
PyPIpytest7.1.2indirect
PyPIpytest8.1.1indirect
PyPIpytest-console-scripts1.3.1indirect
PyPIpytest-cov—indirect
PyPIpytest-subprocess—indirect
PyPIrenku-sphinx-theme—indirect
PyPIsetuptools78.1.1indirect
PyPIsphinx6.2.1indirect
PyPIsphinx-notfound-page—indirect
PyPIsphinx-rtd-theme—indirect
PyPIsphinxcontrib-spelling—indirect
PyPItox—indirect
PyPItypes-setuptools65.7.0.4indirect
PyPIwheel0.41.2indirect
Raw JSON report machine-readable

Feedback

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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 v0.11.0 — full methodology · metrics wiki.

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