Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-12 12:18 UTC

AgamiAI / agami-core

The trust layer between AI and your data. Turns your database schema - messy joins, undocumented tables, into a governed semantic model so AI answers with correct SQL and a receipt on every answer. Run it locally, or self-host a shared team server with Docker.

PythonCustom license★ 28 stars⑂ 1 forksince May 2026View on GitHub ↗

AgamiAI/agami-core holds a health index of 81 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (96/100) and lowest on Community & Adoption (46/100). It was last updated today. 2 contributors account for most of its recent work.

81
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.

81
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 69 is calibrated to 81 on the published index scale (record calibration 2026-08-02).

Ownership

Agami AIOrganization
1 follower1 public reposince May 2024

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIagami-core0.9.133,338530 days ago

Metrics by category

Vitality

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

87Excellent · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
15.2/36Commit cadence — 22/52 weeks with commits
18/18Commit volume — 942 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 6 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year942
human_commit_share1
days_since_last_push0
active_weeks_last_year22

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 55 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~2.7 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count55
latest_release_tagv0.9.13
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases2.7
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?

46Weak · 17% of overall
How it's scored
23.2/60Stars — 28 stars
0/25Forks — 1 forks
0/15Watchers — 0 watchers
Inputs used
forks1
stars28
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno
How it's scored
47/80Monthly downloads — 3,338 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesagami-core
dependents—
ecosystemspypi
total_downloads—
monthly_downloads3,338
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?

58Moderate · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
11.4/22.5Commit distribution — top contributor authored 50% 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_factor2
contributors_sampled3
top_contributor_share0.495
How it's scored
25.8/42Issue resolution — 62% of issues closed
28/30PR acceptance — 329/353 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 1/26 approved changesets -- score normalized to 0
Inputs used
merged_prs329
open_issues35
closed_issues56
prs_merged_7d13
prs_decided_7d13
prs_merged_30d59
prs_decided_30d60
issue_closed_ratio0.615
closed_unmerged_prs24
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.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
2.2/25Owner reach — 1 followers of AgamiAI
7.1/25Track record — 1 public repos, account ~2 yr old
Inputs used
followers1
owner_typeOrganization
is_verifiedno
owner_loginAgamiAI
public_repos1
account_age_days892

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 — 53 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesagami-core
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall
How it's scored
24/24CI workflows — 5 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 26 out of 26 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

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://www.agami.ai
10/10Repository description
10/10Topics — 9 topics
10/10Wiki
Inputs used
topicsanalytics, business-intelligence, claude-skills, context-layer, context-layer-for-ai, mcp, nl2sql, semantic-layer, text-to-sql
has_wikiyes
homepagehttps://www.agami.ai
docs_sitehttps://www.agami.ai
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

52Moderate · 16% of overall
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 — 26 out of 26 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 — Found 1/26 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
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 6 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
3.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 7
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.2
Excluded from scoring (no data or not applicable): Packaging, 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.

76Good · 4% of overall
How it's scored
45/45Agent instructions — CLAUDE.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://www.agami.ai/llms.txt)
36.8/40Legible commit history — 69 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://www.agami.ai/llms.txt
legible_history_share0.69
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes5,318
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 — Dockerfile
10/10Demonstrated agent practice — 60 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
7/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 7
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.6
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
52.1/55Manageable file sizes — 18/337 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes371,316
source_files_sampled337
oversized_source_files18
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
40/40Runnable examples — samples
Inputs used
example_dirssamples
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

28GitHub stars
3contributors
942commits, last 12 months
0days since last push
55releases
2bus factor
35open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • deps.dev does not index pypi:agami-core@0.9.13; 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 · 2026-10-12 12:18 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests26 out of 26 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 1/26 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
10Maintained30 commit(s) and 6 issue activity found in the last 90 days -- score normalized to 10
n/aPackaginginternal error: Client.Actions.ListWorkflowRunsByFileName: internal error: ListWorkflowRunsByFileName: GET https://api.github.com/repos/AgamiAI/agami-core/actions/workflows/release-image.yml/runs?status=success: 502 Server Error []
7Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 7
0SASTSAST tool is not run on all commits -- score normalized to 0
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

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 v0.34.0 — full methodology · metrics wiki.

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