Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-17 00:06 UTC

lepture / mistune

A fast yet powerful Python Markdown parser with renderers and plugins.

PythonBSD-3-Clause★ 3,057 stars⑂ 290 forkssince Feb 2014View on GitHub ↗

lepture/mistune holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on Vitality (83/100) and lowest on AI Readiness (44/100). It was last updated 7 days ago. A single contributor accounts for most of its recent work.

83
overall / 100
Excellent

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.

83
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 70 is calibrated to 83 on the published index scale (record calibration 2026-08-02).

Ownership

Hsiaoming YangPersonal account
8,825 followers190 public repossince May 2010@hsiaoming

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 publish
PyPImistune3.3.3-557 days ago

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 recencylast push 7 days ago
13.2/36Commit cadence19/52 weeks with commits
18/18Commit volume109 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 22 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year109
human_commit_share
days_since_last_push7
active_weeks_last_year19
How it's scored
27/27Ships releases25 releases published
36/36Release recencylatest release 7 days ago
19.8/27Release cadencea release every ~56.1 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count25
latest_release_tagv3.3.3
releases_from_tagsno
days_since_latest_release7
mean_days_between_releases56.1
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?

69Good · 17% of overall
How it's scored
56.5/60Stars3,057 stars
20.5/25Forks290 forks
8.8/15Watchers39 watchers
Inputs used
forks290
stars3,057
watchers39
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (BSD-3-Clause)
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

Sustainability & Governance

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

66Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
2.7/22.5Commit distributiontop contributor authored 88% of commits
13.5/13.5Contributor breadth58 contributors
10/10OpenSSF Scorecard: Contributorsproject has 5 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled58
top_contributor_share0.882
How it's scored
39.6/42Issue resolution94% of issues closed
17.1/30PR acceptance76/133 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-ReviewFound 6/26 approved changesets -- score normalized to 2
Inputs used
merged_prs76
open_issues18
closed_issues300
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.943
closed_unmerged_prs57
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
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
25/25Owner reach8,825 followers of lepture
25/25Track record190 public repos, account ~16 yr old
Inputs used
followers8,825
owner_typeUser
is_verified
owner_loginlepture
public_repos190
account_age_days5,892
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 7 days ago
20/20Version history55 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesmistune
ecosystemspypi
any_deprecatedno
min_days_since_publish7

Engineering Quality

Are baseline engineering and documentation practices in place?

78Good · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
6.4/6.4.editorconfig
16/20OpenSSF Scorecard: CI-Tests5 out of 6 merged PRs checked by a CI test -- score normalized to 8
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configno
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttp://mistune.lepture.com/
10/10Repository description
10/10Topics1 topics
0/10Wiki
Inputs used
topicsmarkdown
has_wikino
homepagehttp://mistune.lepture.com/
docs_sitehttp://mistune.lepture.com/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

54Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
2/2.5CI-Tests5 out of 6 merged PRs checked by a CI test -- score normalized to 8
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1.5/7.5Code-ReviewFound 6/26 approved changesets -- score normalized to 2
2.5/2.5Contributorsproject has 5 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained30 commit(s) and 22 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
5/5SASTSAST tool is run on all commits
1.5/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.4
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.

44Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit historyno 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.
How it's scored
18/18One-command bootstrapMakefile, docs/Makefile
22/22Automated tests
0/11Lint / format config
11/11Static type checkingsrc/mistune/py.typed
0/10Reproducible environment
0/10Demonstrated agent practiceno data
0/8Automated maintenanceno data
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_configno
typecheck_configssrc/mistune/py.typed
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.
How it's scored
27/45Type-checkable codePython with type-check config (src/mistune/py.typed)
55/55Manageable file sizes0/57 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes30,613
source_files_sampled57
oversized_source_files0

Key facts

3,057GitHub stars
58contributors
109commits, last 12 months
7days since last push
25releases
1bus factor
18open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 5.4 / 10
5.4aggregate

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 · 2026-07-17 00:06 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
8CI-Tests5 out of 6 merged PRs checked by a CI test -- score normalized to 8
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 6/26 approved changesets -- score normalized to 2
10Contributorsproject has 5 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 22 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
3Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 1
RegistryPackageVersion constraintManifest
PyPItyping-extensionspyproject.toml
All dependencies 1

Full resolved dependency set from the GitHub dependency graph: 1 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPItyping-extensionsdirect
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 v0.11.0 — full methodology · metrics wiki.

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