Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 05:21 UTC

csurfer / rake-nltk

Python implementation of the Rapid Automatic Keyword Extraction algorithm using NLTK.

PythonMIT★ 1,083 stars⑂ 151 forkssince Jan 2017View on GitHub ↗
KindLibraryhow this is determined
#nltk#algorithm#python#text-mining#keyword-extraction

csurfer/rake-nltk holds a health index of 27 out of 100, placing it in the At Risk band. It scores highest on Engineering Quality (84/100) and lowest on Vitality (1/100). It was last updated 1342 days ago. A single contributor accounts for most of its recent work.

27
overall / 100
At Risk

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.

27
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 47 is calibrated to 45 on the published index scale (record calibration 2026-08-02).

Ownership

Vishwas B SharmaPersonal account
154 followers30 public repossince Dec 2011

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
PyPIrake_nltk1.0.6-71793 days agonlptext-miningalgorithmsdevelopment
PyPIrake-nltk1.0.6273,49971793 days agonlptext-miningalgorithmsdevelopment

Metrics by category

Vitality

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

1Critical · 21% of overall

Development activity

1Critical
How it's scored
0/36Push recency — last push 1,342 days ago
0/36Commit cadence — 0/52 weeks with commits
0/18Commit volume — 0 commits in the last year
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share0.989
days_since_last_push1,342
active_weeks_last_year0

Release discipline

1Critical
How it's scored
0/27Ships releases — no releases published
0/36Release recency — no releases
0/27Release cadence — no releases
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count0
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?

70Good · 17% of overall

Popularity & adoption

75Good
How it's scored
49.2/60Stars — 1,083 stars
18.1/25Forks — 151 forks
8/15Watchers — 28 watchers
Inputs used
forks151
stars1,083
watchers28
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
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, github.com, shields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

91Excellent
How it's scored
72.5/80Monthly downloads — 273,499 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesrake_nltk, rake-nltk
dependents—
ecosystemspypi
total_downloads—
monthly_downloads273,499
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?

44Weak · 23% of overall

Maintainer resilience (bus factor)

14Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.9/22.5Commit distribution — top contributor authored 96% of commits
4.1/13.5Contributor breadth — 3 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.958

Issue & PR responsiveness

44Weak
How it's scored
22.5/42Issue resolution — 54% of issues closed
15.6/30PR acceptance — 13/25 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/14 approved changesets -- score normalized to 0
Inputs used
merged_prs13
open_issues20
closed_issues23
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.535
closed_unmerged_prs12
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.

Ownership & stewardship

61Moderate
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
15.7/25Owner reach — 154 followers of csurfer
22.9/25Track record — 30 public repos, account ~14 yr old
Inputs used
followers154
owner_typeUser
is_verified—
owner_logincsurfer
public_repos30
account_age_days5,367
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

69Good
How it's scored
25/25Published & resolvable — 2 package(s) on pypi
4/35Publish recency — latest publish 1,793 days ago
20/20Version history — 7 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesrake_nltk, rake-nltk
ecosystemspypi
any_deprecatedno
min_days_since_publish1,793

Engineering Quality

Are baseline engineering and documentation practices in place?

84Excellent · 19% of overall

Engineering practices

74Good
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
16/16Linter config — tox.ini
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 10 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://csurfer.github.io/rake-nltk
10/10Repository description
10/10Topics — 5 topics
10/10Wiki
Inputs used
topicsnltk, algorithm, python, text-mining, keyword-extraction
has_wikiyes
homepagehttps://csurfer.github.io/rake-nltk
docs_sitehttps://csurfer.github.io/rake-nltk
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

44Weak · 16% of overall

Security posture

30At Risk
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
0/2.5CI-Tests — 0 out of 10 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
0/7.5Code-Review — Found 0/14 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
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 — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 68 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate3
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 advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages6
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:rake_nltk@1.0.6 runtime dependency closure — what installing the published package pulls in — 6 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.

43Weak · 4% of overall

Agent context & guidance

8Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
8/40Legible commit history — 14 of 93 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.151
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

69Good
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config — tox.ini
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 94
8/8Automated maintenance — 1 of the last 94 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
lockfilespoetry.lock
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.011

Code legibility for models

43Weak
How it's scored
0/45Type-checkable code — Python without a type-check config
43.4/55Manageable file sizes — 4/19 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes287,630
source_files_sampled19
oversized_source_files4

Key facts

1,083GitHub stars
3contributors
0commits, last 12 months
1,342days since last push
0releases
1bus factor
20open 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 ★ / 151 ⇿
0Stars
151Forks

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.

0255075100125150148122017-012021-092026-05

Each point covers 9 days.

OpenSSF Scorecard 3.0 / 10
3.0aggregate

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 · 2026-08-13 05:20 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 10 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/14 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
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
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities68 existing vulnerabilities detected
Direct dependencies 1
RegistryPackageVersion constraintManifest
PyPInltk^3.6.2pyproject.toml
All dependencies 56

Full resolved dependency set from the GitHub dependency graph: 2 direct and 54 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInltk—direct
PyPInltk3.6.2direct
PyPIalabaster0.7.12indirect
PyPIatomicwrites1.4.0indirect
PyPIattrs21.2.0indirect
PyPIbabel2.9.1indirect
PyPIbackports-entry-points-selectable1.1.0indirect
PyPIcertifi2021.5.30indirect
PyPIcharset-normalizer2.0.4indirect
PyPIclick8.0.1indirect
PyPIcolorama0.4.4indirect
PyPIdistlib0.3.2indirect
PyPIdocutils0.17.1indirect
PyPIfilelock3.0.12indirect
PyPIidna3.2indirect
PyPIimagesize1.2.0indirect
PyPIimportlib-metadata4.8.1indirect
PyPIimportlib-resources5.2.2indirect
PyPIiniconfig1.1.1indirect
PyPIjinja23.0.1indirect
PyPIjoblib1.0.1indirect
PyPIlivereload2.6.3indirect
PyPImarkupsafe2.0.1indirect
PyPIpackaging21.0indirect
PyPIplatformdirs2.3.0indirect
PyPIpluggy1.0.0indirect
PyPIpy1.10.0indirect
PyPIpygments2.10.0indirect
PyPIpyparsing2.4.7indirect
PyPIpytest—indirect
PyPIpytest6.2.5indirect
PyPIpython—indirect
PyPIpytz2021.1indirect
PyPIregex2021.8.28indirect
PyPIrequests2.26.0indirect
PyPIsix1.16.0indirect
PyPIsnowballstemmer2.1.0indirect
PyPIsphinx—indirect
PyPIsphinx4.2.0indirect
PyPIsphinx-autobuild—indirect
PyPIsphinx-autobuild2021.3.14indirect
PyPIsphinxcontrib-applehelp1.0.2indirect
PyPIsphinxcontrib-devhelp1.0.2indirect
PyPIsphinxcontrib-htmlhelp2.0.0indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp1.0.3indirect
PyPIsphinxcontrib-serializinghtml1.1.5indirect
PyPItoml0.10.2indirect
PyPItornado6.1indirect
PyPItox—indirect
PyPItox3.24.3indirect
PyPItqdm4.62.2indirect
PyPItyping-extensions3.10.0.2indirect
PyPIurllib31.26.6indirect
PyPIvirtualenv20.7.2indirect
PyPIzipp3.5.0indirect
Dependency advisories 0

Installing pypi:rake_nltk@1.0.6 pulls in 6 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

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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 statistics — PyPI.