Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-19 19:40 UTC

miyakogi / m2r

Markdown to reStructuredText converter

PythonMIT★ 308 stars⑂ 118 forkssince May 2016archivedView on GitHub ↗
KindCommand-line toolLibraryhow this is determined

miyakogi/m2r holds a health index of 14 out of 100, placing it in the Critical band. It scores highest on Engineering Quality (64/100) and lowest on Security (1/100). The repository is archived, so no further maintenance is expected.

14
overall / 100
Critical

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.

14
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 39 is calibrated to 34 on the published index scale (record calibration 2026-08-02).

Ownership

miyacoPersonal account
254 followers68 public repossince Jan 2013

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
PyPIm2r0.3.147,150191432 days agomarkdownrestructuredtextsphinx-extension

Metrics by category

Vitality

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

13Critical · 21% of overall
How it's scored
0/36Push recency — last push 1,432 days ago
0/36Commit cadence — 0/52 weeks with commits
0/18Commit volume — 0 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year0
human_commit_share1
days_since_last_push1,432
active_weeks_last_year0
How it's scored
16.2/27Ships releases — 13 version tags (no GitHub releases)
0/36Release recency — latest release 1,432 days ago
12.6/27Release cadence — a release every ~213.3 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count13
latest_release_tagv0.3.1
releases_from_tagsyes
days_since_latest_release1,432
mean_days_between_releases213.3

Community & Adoption

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

60Moderate · 17% of overall
How it's scored
40.3/60Stars — 308 stars
17.2/25Forks — 118 forks
0/15Watchers — 1 watchers
Inputs used
forks118
stars308
watchers1
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_badges5
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, shields.io, travis-ci.org
has_pull_request_templateno
How it's scored
62.3/80Monthly downloads — 47,150 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesm2r
dependents—
ecosystemspypi
total_downloads—
monthly_downloads47,150
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?

53Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
2/22.5Commit distribution — top contributor authored 91% of commits
13.5/13.5Contributor breadth — 10 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled10
top_contributor_share0.912
How it's scored
14/42Issue resolution — 33% of issues closed
27.9/30PR acceptance — 13/14 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_prs13
open_issues34
closed_issues17
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.333
closed_unmerged_prs1
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
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
17.3/25Owner reach — 254 followers of miyakogi
25/25Track record — 68 public repos, account ~13 yr old
Inputs used
followers254
owner_typeUser
is_verified—
owner_loginmiyakogi
public_repos68
account_age_days5,032
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
4/35Publish recency — latest publish 1,432 days ago
20/20Version history — 19 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesm2r
ecosystemspypi
any_deprecatedno
min_days_since_publish1,432

Engineering Quality

Are baseline engineering and documentation practices in place?

64Moderate · 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 — no data
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 3 topics
10/10Wiki
Inputs used
topicsmarkdown, restructuredtext, sphinx-extension
has_wikiyes
homepage—
docs_site—
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
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestsrequirements-dev.txt, requirements-test.txt, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno

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.

39Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
5.9/40Legible commit history — 11 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.11
agent_instruction_files—
agent_instruction_max_bytes—
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 agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
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_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/8 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes23,425
source_files_sampled8
oversized_source_files0

Key facts

308GitHub stars
10contributors
0commits, last 12 months
1,432days since last push
13releases
1bus factor
34open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • No resolved dependencies carried a version and a supported ecosystem
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Star and fork history 0 ★ / 118 ⇿
0Stars
118Forks
13Releases

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.

0204060801008832017-032021-082025-12
Major 0Minor 2Patch 11

Each point covers 8 days.

All dependencies 11

Full resolved dependency set from the GitHub dependency graph: 0 direct and 11 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcoverage—indirect
PyPIdocutils—indirect
PyPIdoit—indirect
PyPIflake8—indirect
PyPIgreen—indirect
PyPIlivereload—indirect
PyPImistune—indirect
PyPImock—indirect
PyPIpygments—indirect
PyPIsphinx—indirect
PyPItox—indirect
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies carried a version and a supported ecosystem

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.