Public record
Software health reportschema 0.31.0 · metrics 2.5.0 · 2026-08-08 19:40 UTC

mozilla-releng / redo

Utilities to retry Python callables

PythonMPL-2.0★ 101 stars⑂ 36 forkssince May 2014View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

mozilla-releng/redo holds a health index of 56 out of 100, placing it in the Moderate band. It scores highest on Sustainability & Governance (67/100) and lowest on Engineering Quality (44/100). It was last updated 4 days ago. 2 contributors account for most of its recent work.

56
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.

56
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 54 is calibrated to 56 on the published index scale (record calibration 2026-08-02).

Ownership

Mozilla RelengOrganization
20 followers100 public repossince May 2016

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIredo3.0.0-16752 days ago

Metrics by category

Vitality

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

46Weak · 21% of overall
How it's scored
36/36Push recency — last push 4 days ago
8.3/36Commit cadence — 12/52 weeks with commits
12.6/18Commit volume — 24 commits in the last year
4/10OpenSSF Scorecard: Maintained — 5 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 4
Inputs used
commits_last_year24
human_commit_share0.99
days_since_last_push4
active_weeks_last_year12
How it's scored
16.2/27Ships releases — 5 version tags (no GitHub releases)
0/36Release recency — latest release 752 days ago
5.4/27Release cadence — a release every ~526.7 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count5
latest_release_tag3.0.0
releases_from_tagsyes
days_since_latest_release752
mean_days_between_releases526.7
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?

57Moderate · 17% of overall
How it's scored
32.4/60Stars — 101 stars
12.9/25Forks — 36 forks
4.7/15Watchers — 8 watchers
Inputs used
forks36
stars101
watchers8
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MPL-2.0)
0/18CONTRIBUTING guide
13.5/13.5Code 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_conductyes
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

67Good · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
12.6/22.5Commit distribution — top contributor authored 44% of commits
13.5/13.5Contributor breadth — 24 contributors
10/10OpenSSF Scorecard: Contributors — project has 8 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled24
top_contributor_share0.44
How it's scored
28/42Issue resolution — 67% of issues closed
20.2/30PR acceptance — 60/89 decided PRs merged
13/13Newcomer PR acceptance — 1/1 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs60
open_issues6
closed_issues12
prs_merged_7d2
prs_decided_7d2
prs_merged_30d3
prs_decided_30d3
issue_closed_ratio0.667
closed_unmerged_prs29
first_time_authors_30d1
first_time_prs_merged_30d1
first_time_prs_decided_30d1
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
9.5/25Owner reach — 20 followers of mozilla-releng
25/25Track record — 100 public repos, account ~10 yr old
Inputs used
followers20
owner_typeOrganization
is_verified
owner_loginmozilla-releng
public_repos100
account_age_days3,725
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
4/35Publish recency — latest publish 752 days ago
20/20Version history — 16 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesredo
ecosystemspypi
any_deprecatedno
min_days_since_publish752

Engineering Quality

Are baseline engineering and documentation practices in place?

44Weak · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
16/16Linter config — tox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 21 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configyes
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
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

56Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
0/2.5CI-Tests — 0 out of 21 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 8 contributing companies or organizations
0/10Dangerous-Workflow — no data
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
3/7.5Maintained — 5 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 4
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 — no data
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated13
scorecard_versionv5.5.0
checks_inconclusive5
scorecard_aggregate5.6
Excluded from scoring (no data or not applicable): branch_protection, dangerous_workflow, packaging, signed_releases, token_permissions. 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.

45Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
31.2/40Legible commit history — 58 of 99 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
legible_history_share0.586
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — tox.ini
0/11Static type checking
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 1 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_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.01
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/6 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes13,312
source_files_sampled6
oversized_source_files0

Key facts

101GitHub stars
24contributors
24commits, last 12 months
4days since last push
5releases
2bus factor
6open 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 ★ / 36 ⇿
0Stars
36Forks
5Releases

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.

01325383632014-052020-062026-07
Major 1Minor 0Patch 4

Each point covers 12 days.

OpenSSF Scorecard 5.6 / 10
5.6aggregate

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 · 2026-08-08 19:40 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
0CI-Tests0 out of 21 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 8 contributing companies or organizations
n/aDangerous-Workflowno workflows found
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
4Maintained5 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 4
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
n/aToken-PermissionsNo tokens found
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 v0.31.0 — full methodology · metrics wiki.

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