Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-10 21:08 UTC

makegov / tango-python

Official Python SDK for the Tango API — federal contracts, IDVs, entities, opportunities, grants, vehicles, and more, with dynamic response shaping.

PythonMIT★ 4 stars⑂ 0 forkssince Nov 2024View on GitHub ↗
KindLibraryCommand-line toolhow this is determined
#api-client#federal-contracts#govtech#grants#makegov#procurement#sdk#tango

makegov/tango-python holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Engineering Quality (90/100) and lowest on Community & Adoption (38/100). It was last updated today. A single contributor accounts for most of its recent work.

78
overall / 100
Good

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.

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

Ownership

MakeGovOrganization · verified domain
14 followers11 public repossince Aug 2024

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPItango-python1.16.018,939320 days agoapicontractsgovernmentsdktango

Metrics by category

Vitality

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

87Excellent · 21% of overall

Development activity

78Good
How it's scored
36/36Push recency — last push 0 days ago
14.5/36Commit cadence — 21/52 weeks with commits
17.4/18Commit volume — 85 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year85
human_commit_share0.46
days_since_last_push0
active_weeks_last_year21

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 23 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~6.8 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count23
latest_release_tagv1.16.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases6.8
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?

38Weak · 17% of overall

Popularity & adoption

8Critical
How it's scored
7.7/60Stars — 4 stars
0/25Forks — 0 forks
0/15Watchers — 1 watchers
Inputs used
forks0
stars4
watchers1
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_badges3
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

71Good
How it's scored
57/80Monthly downloads — 18,939 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagestango-python
dependents—
ecosystemspypi
total_downloads—
monthly_downloads18,939
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?

57Moderate · 23% of overall

Maintainer resilience (bus factor)

24At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
6.2/22.5Commit distribution — top contributor authored 72% of commits
2.7/13.5Contributor breadth — 2 contributors
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.725

Issue & PR responsiveness

49Weak
How it's scored
9.7/42Issue resolution — 23% of issues closed
25.5/30PR acceptance — 62/73 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_prs62
open_issues10
closed_issues3
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.231
closed_unmerged_prs11
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, OpenSSF Scorecard: Code-Review. Remaining weights renormalized.

Ownership & stewardship

71Good
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
8.5/25Owner reach — 14 followers of makegov
12.1/25Track record — 11 public repos, account ~2 yr old
Inputs used
followers14
owner_typeOrganization
is_verifiedyes
owner_loginmakegov
public_repos11
account_age_days771

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 32 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagestango-python
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall

Engineering practices

84Excellent
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 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_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://tango.dev
10/10Repository description
10/10Topics — 8 topics
10/10Wiki
Inputs used
topicsapi-client, federal-contracts, govtech, grants, makegov, procurement, sdk, tango
has_wikiyes
homepagehttps://tango.dev
docs_sitehttps://tango.dev
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

62Moderate · 16% of overall

Security posture

52Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — no data
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool is run on all commits
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
5.2/7.5Vulnerabilities — 3 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate5.2
Excluded from scoring (no data or not applicable): Code-Review, 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
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories5
affected_packages2
assessed_packages29
unassessed_packages0
affected_by_severitycritical 1, high 1
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 29 resolved dependencies against OSV. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

60Moderate · 4% of overall

Agent context & guidance

55Moderate
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.makegov.com/llms.txt)
40/40Legible commit history — 32 of 40 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.makegov.com/llms.txt
legible_history_share0.8
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

53Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 58 of the last 87 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.667
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

50Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
50.3/55Manageable file sizes — 6/70 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes243,419
source_files_sampled70
oversized_source_files6

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — notebooks
Inputs used
example_dirsnotebooks
has_mcp_signalno
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

4GitHub stars
2contributors
85commits, last 12 months
0days since last push
23releases
1bus factor
10open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:tango-python@1.16.0; advisories assessed against the repository dependency graph instead

More detail

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).Scorecard v5.5.0 · 2026-10-10 21:08 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-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
n/aCode-ReviewFound no human activity in the last 30 changesets
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 0 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
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7Vulnerabilities3 existing vulnerabilities detected
Direct dependencies 1
RegistryPackageVersion constraintManifest
PyPIhttpx>=0.27.0pyproject.toml
All dependencies 29

Full resolved dependency set from the GitHub dependency graph: 1 direct and 28 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIhttpx0.28.1direct
PyPIanyio4.13.0indirect
PyPIast-serialize0.5.0indirect
PyPIcertifi2026.5.20indirect
PyPIclick8.4.1indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.14.1indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIidna3.17indirect
PyPIiniconfig2.3.0indirect
PyPIlibrt0.11.0indirect
PyPImypy2.1.0indirect
PyPImypy-extensions1.1.0indirect
PyPIpackaging26.2indirect
PyPIpathspec1.1.1indirect
PyPIpluggy1.6.0indirect
PyPIpygments2.20.0indirect
PyPIpytest9.0.3indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-httpx0.36.2indirect
PyPIpytest-recording0.13.4indirect
PyPIpython-dotenv1.2.2indirect
PyPIpyyaml6.0.3indirect
PyPIruff0.15.15indirect
PyPItango-python1.16.0indirect
PyPItyping-extensions4.15.0indirect
PyPIvcrpy8.1.1indirect
PyPIwrapt2.2.1indirect
Dependency advisories 2

This repository publishes no package the index resolves, so its own dependency graph was assessed — 29 packages, which also include development and test pins that never ship: 2 carry known advisories, of which 0 are direct.

PackageVersionRelationSeverityAdvisoriesFixed in
anyio4.13.0indirectcritical44.14.2
vcrpy8.1.1indirecthigh18.2.1

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.

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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 v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.