Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-04 21:55 UTC

microsoft / markitdown

Python tool for converting files and office documents to Markdown.

PythonMIT★ 171,454 stars⑂ 12,484 forkssince Nov 2024View on GitHub ↗
KindMCP serverCommand-line toolLibraryPluginhow this is determined

microsoft/markitdown holds a health index of 92 out of 100, placing it in the Excellent band. It scores highest on Community & Adoption (88/100) and lowest on AI Readiness (64/100). It was last updated 6 days ago. 2 contributors account for most of its recent work.

92
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.

92
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 78 is calibrated to 92 on the published index scale (record calibration 2026-08-02).

Ownership

MicrosoftOrganization
126,853 followers8,242 public repossince Dec 2013

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPImarkitdown0.1.713,625,458236 days ago
PyPImarkitdown-mcp0.0.1a4-4438 days ago
PyPImarkitdown-ocr0.1.063,6881147 days agodocxllmmarkitdownocrpdfpptxvisionxlsx
PyPImarkitdown-sample-plugin0.1.0a1-3516 days ago

Metrics by category

Vitality

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

78Good · 21% of overall
How it's scored
36/36Push recencylast push 6 days ago
9/36Commit cadence13/52 weeks with commits
14.1/18Commit volume36 commits in the last year
10/10OpenSSF Scorecard: Maintained8 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year36
human_commit_share0.99
days_since_last_push6
active_weeks_last_year13
How it's scored
27/27Ships releases20 releases published
36/36Release recencylatest release 6 days ago
19.8/27Release cadencea release every ~54.9 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count20
latest_release_tagv0.1.7
releases_from_tagsno
days_since_latest_release6
mean_days_between_releases54.9
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?

88Excellent · 17% of overall

Popularity & adoption

100Exceptional
How it's scored
60/60Stars171,454 stars
25/25Forks12,484 forks
15/15Watchers550 watchers
Inputs used
forks12,484
stars171,454
watchers550
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
0/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingno
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateno
How it's scored
80/80Monthly downloads13,689,146 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesmarkitdown, markitdown-mcp, markitdown-ocr, markitdown-sample-plugin
dependents
ecosystemspypi
total_downloads
monthly_downloads13,689,146
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?

73Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
14.9/22.5Commit distributiontop contributor authored 34% of commits
13.5/13.5Contributor breadth79 contributors
10/10OpenSSF Scorecard: Contributorsproject has 10 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled79
top_contributor_share0.338
How it's scored
13.4/42Issue resolution32% of issues closed
13.5/30PR acceptance183/408 decided PRs merged
0/13Newcomer PR acceptance0/11 first-time contributors' PRs merged in 30d
10.5/15OpenSSF Scorecard: Code-ReviewFound 23/30 approved changesets -- score normalized to 7
Inputs used
merged_prs183
open_issues379
closed_issues177
prs_merged_7d2
prs_decided_7d4
prs_merged_30d6
prs_decided_30d45
issue_closed_ratio0.318
closed_unmerged_prs225
first_time_authors_30d10
first_time_prs_merged_30d0
first_time_prs_decided_30d11
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
25/25Owner reach126,853 followers of microsoft
25/25Track record8,242 public repos, account ~12 yr old
Inputs used
followers126,853
owner_typeOrganization
is_verified
owner_loginmicrosoft
public_repos8,242
account_age_days4,620
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable4 package(s) on pypi
35/35Publish recencylatest publish 6 days ago
20/20Version history23 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesmarkitdown, markitdown-mcp, markitdown-ocr, markitdown-sample-plugin
ecosystemspypi
any_deprecatedno
min_days_since_publish6

Engineering Quality

Are baseline engineering and documentation practices in place?

80Excellent · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics7 topics
10/10Wiki
Inputs used
topicslangchain, openai, autogen-extension, autogen, markdown, microsoft-office, pdf
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

74Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
3/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2.5/2.5CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
5.2/7.5Code-ReviewFound 23/30 approved changesets -- score normalized to 7
2.5/2.5Contributorsproject has 10 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained8 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
1.5/5SASTSAST tool is not run on all commits -- score normalized to 3
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_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6.7
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages19
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:markitdown@0.1.7 runtime dependency closure — what installing the published package pulls in — 19 packages. Reachability is not analyzed.

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.

64Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history91 of 99 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.919
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
11/11Static type checkingpackages/markitdown-mcp/src/markitdown_mcp/py.typed, packages/markitdown-sample-plugin/src/markitdown_sample_plugin/py.typed, packages/markitdown/src/markitdown/py.typed
10/10Reproducible environmentdevcontainer, Dockerfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance1 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_files
has_devcontaineryes
has_linter_configyes
typecheck_configspackages/markitdown-mcp/src/markitdown_mcp/py.typed, packages/markitdown-sample-plugin/src/markitdown_sample_plugin/py.typed, packages/markitdown/src/markitdown/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.01
How it's scored
27/45Type-checkable codePython with type-check config (packages/markitdown-mcp/src/markitdown_mcp/py.typed, packages/markitdown-sample-plugin/src/markitdown_sample_plugin/py.typed, packages/markitdown/src/markitdown/py.typed)
55/55Manageable file sizes0/72 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes45,659
source_files_sampled72
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
20/20MCP server
40/40Runnable examplesnotebooks
Inputs used
example_dirsnotebooks
has_mcp_signalyes
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto). Remaining weights renormalized.

Key facts

171,454GitHub stars
79contributors
36commits, last 12 months
6days since last push
20releases
2bus factor
379open issues
package ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • First-time contributor figures cover 12 of 41 authors (cap 12)

More detail

Star and fork history 0 ★ / 12,484 ⇿
0Stars
12,484Forks
1Releases

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.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

11,00011,50012,00012,50012,484592026-072026-072026-08
Major 0Minor 0Patch 1
OpenSSF Scorecard 6.7 / 10
6.7aggregate

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 · 2026-08-04 21:55 UTC

10Binary-Artifactsno binaries found in the repo
4Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7Code-ReviewFound 23/30 approved changesets -- score normalized to 7
10Contributorsproject has 10 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained8 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
3SASTSAST tool is not run on all commits -- score normalized to 3
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 20
RegistryPackageVersion constraintManifest
PyPImcp~=1.8.0packages/markitdown-mcp/pyproject.toml
PyPImarkitdown>=0.1.1,<0.2.0packages/markitdown-mcp/pyproject.toml
PyPImarkitdown>=0.1.0packages/markitdown-ocr/pyproject.toml
PyPIpdfminer.six>=20251230packages/markitdown-ocr/pyproject.toml
PyPIpdfplumber>=0.11.9packages/markitdown-ocr/pyproject.toml
PyPIPyMuPDF>=1.24.0packages/markitdown-ocr/pyproject.toml
PyPImammoth~=1.11.0packages/markitdown-ocr/pyproject.toml
PyPIpython-docxpackages/markitdown-ocr/pyproject.toml
PyPIpython-pptxpackages/markitdown-ocr/pyproject.toml
PyPIpandaspackages/markitdown-ocr/pyproject.toml
PyPIopenpyxlpackages/markitdown-ocr/pyproject.toml
PyPIPillow>=9.0.0packages/markitdown-ocr/pyproject.toml
PyPImarkitdown>=0.1.0a1packages/markitdown-sample-plugin/pyproject.toml
PyPIstriprtfpackages/markitdown-sample-plugin/pyproject.toml
PyPIbeautifulsoup4packages/markitdown/pyproject.toml
PyPIrequestspackages/markitdown/pyproject.toml
PyPImarkdownifypackages/markitdown/pyproject.toml
PyPImagika~=0.6.1packages/markitdown/pyproject.toml
PyPIcharset-normalizerpackages/markitdown/pyproject.toml
PyPIdefusedxmlpackages/markitdown/pyproject.toml
All dependencies 15

Full resolved dependency set from the GitHub dependency graph: 13 direct and 2 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPImagikadirect
PyPImammothdirect
PyPImarkitdowndirect
PyPImcpdirect
PyPIopenpyxldirect
PyPIpandasdirect
PyPIpdfminer-sixdirect
PyPIpdfplumberdirect
PyPIpillowdirect
PyPIpymupdfdirect
PyPIpython-docxdirect
PyPIpython-pptxdirect
PyPIstriprtfdirect
PyPIazure-ai-contentunderstandingindirect
PyPIyoutube-transcript-apiindirect
Dependency advisories 0

Installing pypi:markitdown@0.1.7 pulls in 19 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

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 v0.31.0 — full methodology · metrics wiki.

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