Public recordGood
Software health reportschema 0.17.0 · metrics 1.13.0 · 2026-07-21 04:47 UTC
stanfordnlp / stanza
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
stanfordnlp/stanza holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Vitality (96/100) and lowest on AI Readiness (31/100). It was last updated today. A single contributor accounts for most of its recent work.
78
overall / 100Software health index
Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At risk ceiling of 49. AI Readiness sits outside the overall score.
78
Excellent85-100Exemplary; meets essentially all checked criteria
Good70-84Healthy; minor gaps
Moderate50-69Acceptable with notable gaps; review recommended
At risk30-49Significant weaknesses; adoption warrants caution
Critical1-29Severe problems (abandoned, single-maintainer, no hygiene)
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.
Ownership
Stanford NLPOrganization
2,684 followers55 public repossince Dec 2012
This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.
Package ecosystems
| Registry | Package | Version | Downloads / mo | Versions | Last publish | Tags |
|---|---|---|---|---|---|---|
| PyPI | stanza | 1.14.0 | - | 33 | 6 days ago | natural-language-processingnlpnatural-language-understandingstanford-nlpdeep-learning |
Metrics by category
Vitality
Is the project alive — is code being written and are releases shipping?
96
Development activity
98Excellent
How it's scored
| 36/36 | Push recency — last push 0 days ago |
| 33.9/36 | Commit cadence — 49/52 weeks with commits |
| 18/18 | Commit volume — 495 commits in the last year |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 24 issue activity found in the last 90 days -- score normalized to 10 |
Inputs used
| commits_last_year | 495 |
| human_commit_share | — |
| days_since_last_push | 0 |
| active_weeks_last_year | 49 |
Release discipline
92Excellent
How it's scored
| 27/27 | Ships releases — 35 releases published |
| 36/36 | Release recency — latest release 6 days ago |
| 19.8/27 | Release cadence — a release every ~74.5 days |
| 0/10 | OpenSSF Scorecard: Signed-Releases — no data |
Inputs used
| releases_count | 35 |
| latest_release_tag | v1.14.0 |
| releases_from_tags | no |
| days_since_latest_release | 6 |
| mean_days_between_releases | 74.5 |
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?
85
Popularity & adoption
97Excellent
How it's scored
| 60/60 | Stars — 7,845 stars |
| 24.8/25 | Forks — 946 forks |
| 11.9/15 | Watchers — 138 watchers |
Inputs used
| forks | 946 |
| stars | 7,845 |
| watchers | 138 |
| growth_state | organic |
| growth_factor_pct | 100 |
Community health
71Good
How it's scored
| 22.5/22.5 | README |
| 16.9/22.5 | License — license file present, not a recognized license |
| 18/18 | CONTRIBUTING guide |
| 0/13.5 | Code of conduct |
| 0/7.2 | Issue template |
| 6.3/6.3 | PR template |
Inputs used
| has_readme | yes |
| has_license | yes |
| has_contributing | yes |
| has_issue_template | no |
| has_code_of_conduct | no |
| has_pull_request_template | yes |
Sustainability & Governance
Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?
70
Maintainer resilience (bus factor)
38At risk
How it's scored
| 9/54 | Bus factor — 1 contributor(s) cover half of all commits |
| 6/22.5 | Commit distribution — top contributor authored 73% of commits |
| 13.5/13.5 | Contributor breadth — 60 contributors |
| 10/10 | OpenSSF Scorecard: Contributors — project has 18 contributing companies or organizations |
Inputs used
| bus_factor | 1 |
| contributors_sampled | 60 |
| top_contributor_share | 0.732 |
How it's scored
| 42.6/46.8 | Issue resolution — 91% of issues closed |
| 32.5/38.3 | PR acceptance — 521/614 decided PRs merged |
| 0/15 | OpenSSF Scorecard: Code-Review — Found 1/15 approved changesets -- score normalized to 0 |
Inputs used
| merged_prs | 521 |
| open_issues | 86 |
| closed_issues | 887 |
| issue_closed_ratio | 0.912 |
| closed_unmerged_prs | 93 |
Ownership & stewardship
79Good
How it's scored
| 30/30 | Ownership backing — organization-owned |
| 0/20 | Verified domain |
| 24.7/25 | Owner reach — 2,684 followers of stanfordnlp |
| 24.7/25 | Track record — 55 public repos, account ~13 yr old |
Inputs used
| followers | 2,684 |
| owner_type | Organization |
| is_verified | — |
| owner_login | stanfordnlp |
| public_repos | 55 |
| account_age_days | 4,966 |
Package maintenance
100Excellent
How it's scored
| 25/25 | Published & resolvable — 1 package(s) on pypi |
| 35/35 | Publish recency — latest publish 6 days ago |
| 20/20 | Version history — 33 published versions |
| 20/20 | Not deprecated — active, not deprecated or yanked |
Inputs used
| packages | stanza |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 6 |
Engineering Quality
Are baseline engineering and documentation practices in place?
80
Engineering practices
66Moderate
How it's scored
| 24/24 | CI workflows — 1 workflow(s) |
| 24/24 | Tests present |
| 0/16 | Linter config |
| 0/9.6 | Pre-commit hooks |
| 0/6.4 | .editorconfig |
| 18/20 | OpenSSF Scorecard: CI-Tests — 10 out of 11 merged PRs checked by a CI test -- score normalized to 9 |
Inputs used
| has_ci | yes |
| has_tests | yes |
| has_editorconfig | no |
| has_linter_config | no |
| has_precommit_config | no |
Documentation
100Excellent
How it's scored
| 30/30 | README |
| 25/25 | Documentation directory |
| 15/15 | Documentation / homepage site — https://stanfordnlp.github.io/stanza/ |
| 10/10 | Repository description |
| 10/10 | Topics — 10 topics |
| 10/10 | Wiki |
Inputs used
| topics | python, nlp, natural-language-processing, machine-learning, deep-learning, artificial-intelligence, pytorch, universal-dependencies, named-entity-recognition, corenlp |
| has_wiki | yes |
| homepage | https://stanfordnlp.github.io/stanza/ |
| has_readme | yes |
| has_docs_dir | yes |
| has_description | yes |
Security
Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?
52
Security posture
52Moderate
How it's scored
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — no data |
| 2.2/2.5 | CI-Tests — 10 out of 11 merged PRs checked by a CI test -- score normalized to 9 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 0/7.5 | Code-Review — Found 1/15 approved changesets -- score normalized to 0 |
| 2.5/2.5 | Contributors — project has 18 contributing companies or organizations |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 0/7.5 | Dependency-Update-Tool — no update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.2/2.5 | License — license file detected |
| 7.5/7.5 | Maintained — 30 commit(s) and 24 issue activity found in the last 90 days -- score normalized to 10 |
| 0/5 | Packaging — no data |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 0/5 | SAST — SAST tool is not run on all commits -- score normalized to 0 |
| 5/5 | Security-Policy — security policy file detected |
| 0/7.5 | Signed-Releases — no data |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Inputs used
| source | openssf_scorecard |
| checks_evaluated | 15 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 3 |
| scorecard_aggregate | 5.2 |
Excluded from scoring (no data or not applicable): branch_protection, packaging, signed_releases. Remaining weights renormalized.
AI Readiness
How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score.
31
Agent context & guidance
1Critical
How it's scored
| 0/45 | Agent instructions — no CLAUDE.md / AGENTS.md / editor rules |
| 0/15 | Machine-readable docs (llms.txt) |
| 0/40 | Legible commit history — no data |
Inputs used
| has_llms_txt | no |
| 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)
27Critical
How it's scored
| 0/18 | One-command bootstrap |
| 22/22 | Automated tests |
| 0/11 | Lint / format config |
| 0/11 | Static type checking |
| 0/10 | Reproducible environment |
| 0/10 | Demonstrated agent practice — no data |
| 0/8 | Automated maintenance — no data |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Inputs used
| has_nix | no |
| has_tests | yes |
| lockfiles | — |
| has_dockerfile | no |
| typed_language | no |
| bootstrap_files | — |
| has_devcontainer | no |
| has_linter_config | no |
| 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
54Moderate
How it's scored
| 0/45 | Type-checkable code — Python without a type-check config |
| 54.5/55 | Manageable file sizes — 5/611 source files over 60KB |
Inputs used
| primary_language | Python |
| largest_source_bytes | 75,769 |
| source_files_sampled | 611 |
| oversized_source_files | 5 |
How it's scored
| 40/40 | API schema (OpenAPI/GraphQL/proto) — doc/CoreNLP.proto |
| 0/20 | MCP server |
| 40/40 | Runnable examples — notebooks |
Inputs used
| example_dirs | notebooks |
| has_mcp_signal | no |
| api_schema_files | doc/CoreNLP.proto |
Key facts
7,845GitHub stars
60contributors
495commits, last 12 months
0days since last push
35releases
1bus factor
86open issues
PyPIpackage ecosystems
Data collection warnings
- deps.dev does not index pypi:stanza@1.14.0; advisories assessed against the repository dependency graph instead
- No resolved dependencies carried a version and a supported ecosystem
More detail
Star and fork history 7,845 ★ / 0 ⇿
7,845Stars
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.
Each point covers 3 days.
OpenSSF Scorecard 5.2 / 10
5.2aggregate
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).
| 10 | Binary-Artifacts | no binaries found in the repo |
| n/a | Branch-Protection | internal 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 |
| 9 | CI-Tests | 10 out of 11 merged PRs checked by a CI test -- score normalized to 9 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 0 | Code-Review | Found 1/15 approved changesets -- score normalized to 0 |
| 10 | Contributors | project has 18 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 0 | Dependency-Update-Tool | no update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 9 | License | license file detected |
| 10 | Maintained | 30 commit(s) and 24 issue activity found in the last 90 days -- score normalized to 10 |
| n/a | Packaging | packaging workflow not detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 10 | Security-Policy | security policy file detected |
| n/a | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
All dependencies 26
Full resolved dependency set from the GitHub dependency graph: 0 direct and 26 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
| Registry | Package | Version | Relation |
|---|---|---|---|
| PyPI | check-manifest | — | indirect |
| PyPI | coverage | — | indirect |
| PyPI | datasets | — | indirect |
| PyPI | emoji | — | indirect |
| PyPI | huggingface-hub | — | indirect |
| PyPI | ipython | — | indirect |
| PyPI | jieba | — | indirect |
| PyPI | matplotlib | — | indirect |
| PyPI | morphseg | — | indirect |
| PyPI | networkx | — | indirect |
| PyPI | numpy | — | indirect |
| PyPI | peft | — | indirect |
| PyPI | platformdirs | — | indirect |
| PyPI | protobuf | — | indirect |
| PyPI | pytest | — | indirect |
| PyPI | pythainlp | — | indirect |
| PyPI | python-crfsuite | — | indirect |
| PyPI | requests | — | indirect |
| PyPI | spacy | — | indirect |
| PyPI | streamlit | — | indirect |
| PyPI | sudachidict-core | — | indirect |
| PyPI | sudachipy | — | indirect |
| PyPI | torch | — | indirect |
| PyPI | tqdm | — | indirect |
| PyPI | transformers | — | indirect |
| PyPI | udtools | — | 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
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"name": "High-Risk Jurisdiction Exposure",
"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
"meaning": "self-published location evidence; not nationality or citizenship",
"red_flag": false,
"exposures": [],
"policy_countries": [
"Russia",
"Iran",
"North Korea"
],
"review_only_matches": 0,
"assessed_self_published_locations": 12
},
"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "at_risk",
"name": "AI Readiness",
"value": 31,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "critical",
"name": "Agent context & guidance",
"note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"legible_commit_history"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 1,
"inputs": {
"has_llms_txt": false,
"legible_history_share": null,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
"name": "Machine-readable docs (llms.txt)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
"name": "Legible commit history",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "critical",
"name": "Verify loop (build / test / typecheck)",
"note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"demonstrated_agent_practice",
"automated_maintenance"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 27,
"inputs": {
"has_nix": false,
"has_tests": true,
"lockfiles": [],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [],
"has_devcontainer": false,
"has_linter_config": false,
"typecheck_configs": [],
"agent_commit_share": null,
"toolchain_manifests": [],
"dependency_bot_commit_share": null
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 18
},
{
"key": "automated_tests",
"name": "Automated tests",
"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
"name": "Lint / format config",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
"name": "Static type checking",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "reproducible_environment",
"name": "Reproducible environment",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 8
},
{
"key": "openssf_scorecard_pinned_dependencies",
"name": "OpenSSF Scorecard: Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
}
]
},
{
"key": "ai_code_legibility",
"band": "moderate",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 54,
"inputs": {
"primary_language": "Python",
"largest_source_bytes": 75769,
"source_files_sampled": 611,
"oversized_source_files": 5
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Python without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Python"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "5/611 source files over 60KB",
"points": 54.5,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 611,
"oversized": 5
}
}
],
"max_points": 55
}
]
},
{
"key": "ai_interfaces",
"band": "good",
"name": "Machine-readable interfaces",
"note": null,
"notes": [],
"value": 80,
"inputs": {
"example_dirs": [
"notebooks"
],
"has_mcp_signal": false,
"api_schema_files": [
"doc/CoreNLP.proto"
]
},
"components": [
{
"key": "api_schema_openapi_graphql_proto",
"name": "API schema (OpenAPI/GraphQL/proto)",
"detail": "doc/CoreNLP.proto",
"points": 40,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "doc/CoreNLP.proto"
}
}
],
"max_points": 40
},
{
"key": "mcp_server",
"name": "MCP server",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 20
},
{
"key": "runnable_examples",
"name": "Runnable examples",
"detail": "notebooks",
"points": 40,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "notebooks"
}
}
],
"max_points": 40
}
]
}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
}
],
"metrics_version": "1.13.0"
},
"warnings": [
"deps.dev does not index pypi:stanza@1.14.0; advisories assessed against the repository dependency graph instead",
"No resolved dependencies carried a version and a supported ecosystem"
],
"report_type": "repository",
"generated_at": "2026-07-21T04:47:09.772132Z",
"schema_version": "0.17.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/s/stanfordnlp/stanza.svg",
"full_name": "stanfordnlp/stanza",
"license_state": "custom",
"license_spdx": null
}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 v1.13.0, schema v0.17.0 — full methodology · metrics wiki.
How one result sits in the wider record: aggregate statistics — PyPI.