leandroveronezi/go-recognizer holds a health index of 54 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (62/100) and lowest on Community & Adoption (45/100). It was last updated today. A single contributor accounts for most of its recent work.
54
overall / 100
Moderate
Software 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.
54
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.
Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25
Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40
No advisories left outstanding — no advisory carries a publication date
Inputs used
source
osv
advisories
0
affected_packages
0
assessed_packages
5
unassessed_packages
0
affected_by_severity
none
direct_affected_packages
0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 5 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.
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.
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.
Major 1Minor 0Patch 1
Each point covers 6 days.
OpenSSF Scorecard 4.7 / 10
4.7aggregate
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 · 2026-07-22 08:45 UTC
Full resolved dependency set from the GitHub dependency graph: 4 direct and 1 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
Registry
Package
Version
Relation
Go
github.com/fogleman/gg
v1.3.0
direct
Go
github.com/golang/freetype
v0.0.0-20170609003504-e2365dfdc4a0
direct
Go
github.com/leandroveronezi/go-face
v1.1.0
direct
Go
golang.org/x/image
v0.44.0
direct
Go
github.com/leandroveronezi/go-recognizer
v1.1.0
indirect
Dependency advisories 0
This repository publishes no package the index resolves, so its own dependency graph was assessed — 5 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct.
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
{
"data": {
"repo": {
"topics": [
"golang",
"face-recognition",
"face-detection",
"dlib-face-detection",
"dlib-face-recognition",
"cnn-classification",
"computer-vision",
"go"
],
"is_fork": false,
"size_kb": 29512,
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"homepage": "https://leandroveronezi.github.io/go-recognizer",
"languages": {
"Go": 36498
},
"pushed_at": "2026-07-21T13:46:45Z",
"created_at": "2020-02-29T19:07:10Z",
"owner_type": "User",
"updated_at": "2026-07-21T13:48:30Z",
"description": "Face detection and recognition using golang",
"is_archived": false,
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"license_spdx": "MIT",
"default_branch": "master",
"license_spdx_raw": "MIT",
"primary_language": "Go",
"significant_languages": [
"Go"
]
},
"owner": {
"blog": null,
"name": null,
"type": "User",
"login": "leandroveronezi",
"company": null,
"location": null,
"followers": 6,
"avatar_url": "https://avatars.githubusercontent.com/u/25439856?v=4",
"created_at": "2017-01-30T19:00:10Z",
"is_verified": null,
"public_repos": 21,
"account_age_days": 3459
},
"license": {
"state": "standard",
"spdx_id": "MIT",
"raw_spdx": "MIT",
"file_present": true,
"scorecard_found": true,
"profile_has_license": true
},
"activity": {
"releases": [
{
"tag": "v1.0.1",
"kind": "patch",
"published_at": "2023-04-17T18:00:38Z"
},
{
"tag": "v1.0.0",
"kind": "major",
"published_at": "2021-02-01T18:03:50Z"
}
],
"recent_commits": [
{
"oid": "d00c43f76ffb3a2b603c53e244c6204cea1d9fa1",
"body": null,
"is_bot": false,
"headline": "README: render the dlib note as a GitHub [!NOTE] callout",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-21T13:46:43Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "da2471e0465b738ef2f6f543321db519bd9a5d1a",
"body": "The shortened version pointing to go-face's README for specifics was\nless clear standalone -- use the same full paragraph in both.",
"is_bot": false,
"headline": "README: match go-face's full dlib-datedness note verbatim",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-21T13:41:49Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "62d71784b1549cba8a644eaf73b73c4bfc3a21c1",
"body": "Points to go-onnxface for actively-developed alternatives; see\ngo-face's README for the specifics behind the claim.",
"is_bot": false,
"headline": "README: note that dlib's face pipeline predates modern models",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-21T13:34:36Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "7817c13609cbcdf4ef4e137189cd1661d8625224",
"body": "RecognizeSingle genuinely returns ErrNotSingleFace (unlike\nRecognizeMultiples/IdentifyMultiples, which return an empty/partial\nlist instead of erroring), so it's worth showing the errors.Is check\nhere too.",
"is_bot": false,
"headline": "examples: demonstrate ErrNotSingleFace in the landmarks example",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-20T13:48:30Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "aec4919f9699f2a7fda9e02774bc6f2f7201108f",
"body": "Makes the ErrNoFace/ErrNotSingleFace check visible where it actually\nhappens (AddImageToDataset), instead of only in the README's Errors\nsection.",
"is_bot": false,
"headline": "examples: demonstrate sentinel error handling with errors.Is",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-20T13:44:42Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "4c2041a2b91937112bb10f624deee2db4e8b00a2",
"body": null,
"is_bot": false,
"headline": "examples: bump go-recognizer/go-face to v1.1.0 (Identify rename)",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-20T13:32:43Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "67037a81bb0e652599977fa8983ab007f6c3084c",
"body": "Aligns with go-face's Identify/IdentifyThreshold rename (breaking, no\nalias) and biometric terminology (Detect -> Recognize -> Compare ->\nIdentify).\n\nAlso replaces string-matched error messages with exported sentinel\nerrors (ErrNoFace, ErrNotSingleFace, ErrNoMatch, ErrDatasetFileNotFound)\ncheckable via errors.Is, and fixes a stale doc comment on Identify that\nclaimed it returns an empty list on no match (it returns ErrNoMatch).\n\nRequires go-face v1.1.0.",
"is_bot": false,
"headline": "Rename Classify to Identify/IdentifyMultiples; add sentinel errors",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-20T13:30:15Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "54bef48e25f885bfc8b7105a9ac28ed2531fb3ee",
"body": "Downloads shape_predictor_5_face_landmarks.dat,\ndlib_face_recognition_resnet_model_v1.dat, and\nmmod_human_face_detector.dat from the dlib-models repository into a\ngiven directory, skipping any file that's already there -- safe to\ncall unconditionally before Init on every startup, similar to how\nlibr\n[…]\nhe real models.\n\nNote: this adds a real ~30s network download to the test suite's\ndefault run (test suite went from ~26s to ~66s) -- flagging in case\nthat's worth gating behind `go test -short` later.",
"is_bot": false,
"headline": "Add DownloadModels to fetch default model files if missing",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T16:47:30Z",
"body_truncated": true,
"is_coding_agent": false
},
{
"oid": "de9e3b2aceb0af80c2c7d7f81a9f7ead876807e0",
"body": "Multi-stage build: compiles dlib from source on Alpine (which has no\ndlib package), builds the detection example against it (dlib links\nstatically, so the runtime stage doesn't need it), and produces a\n~50MB runtime image with just the shared libraries the compiled binary\nactually needs (found via a\n[…]\nts dlib's old cmake_minimum_required() declarations)\nwithout them.\n\nVerified by actually building and running the image: all 7 faces in\nelenco3.jpg detected and labeled correctly inside the container.",
"is_bot": false,
"headline": "examples: add Docker build example (Kagami/go-face#76)",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T16:33:25Z",
"body_truncated": true,
"is_coding_agent": false
},
{
"oid": "dc7693171a26271640971761c2a7aa58520383f0",
"body": null,
"is_bot": false,
"headline": "examples: bump go-recognizer to v1.0.9",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T15:27:02Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "3d9546b40c461773c9f024e34d5e5736814a1151",
"body": "AddImageToDataset, RecognizeSingle, and RecognizeMultiples used to\nwrite a grayscale JPEG to a temp file just so go-face could immediately\ndecode that same JPEG back into pixels. With go-face v1.0.7's\nRecognizeRaw (Kagami/go-face#69), the already-decoded, already-grayed\npixels go straight to goFace \n[…]\n- faces.jpg/faces2.jpg came\nout byte-identical (annotation draws over the original color image, not\nthe internal recognition path), landmarks.jpg shifted by ordinary\ndecoder-rounding differences only.",
"is_bot": false,
"headline": "Skip the temp-file/JPEG round trip when UseGray is set",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T15:25:15Z",
"body_truncated": true,
"is_coding_agent": false
},
{
"oid": "5f2db5d9d52705d9204b9b5b550af0242cd185ea",
"body": null,
"is_bot": false,
"headline": "README: add CI status badge",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T14:57:15Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "91747a5214211ece495bf24c354f7574cf656914",
"body": null,
"is_bot": false,
"headline": "ci: use go mod tidy instead of go mod download to populate go.sum",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T14:53:33Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "528d6cf5fcd3f2e3167c325175b9993c9e1bc4e7",
"body": null,
"is_bot": false,
"headline": "ci: download deps before build (go.sum isn't tracked in this repo)",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T14:52:19Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "0dc93978ca457b4d628cb1dd7956b67f639a2bd2",
"body": "No CI existed before this -- the exact gap that let the GrayScale/JPEG\nregression found earlier this session land on master undetected, since\ngo build/go vet don't exercise runtime behavior. This runs the full\ntest suite (and govulncheck) automatically instead of relying on\nsomeone noticing manually.",
"is_bot": false,
"headline": "Add CI: build, vet, test -race, govulncheck on every push/PR",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T14:51:20Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "3dbf889a76e9d98650a7dc0f5635fd421445cd22",
"body": null,
"is_bot": false,
"headline": "examples: bump go-recognizer to v1.0.8",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T14:35:36Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "5cd0550f2357731b55b5b3f778f5627ec69334b6",
"body": null,
"is_bot": false,
"headline": "Bump go-face to v1.0.5 (fixes upstream Kagami/go-face#82 build error)",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T14:34:12Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "b21880ed01bb0b60d30bf7f2fc14009f64ebd973",
"body": "go-face's own file loader only understands JPEG, but go-recognizer\nalready worked around this: with the default UseGray=true,\nAddImageToDataset/RecognizeFile decode the source with Go's standard\nimage package (PNG is supported here via fogleman/gg's transitive\nimage/png import) and re-encode as JPEG\n[…]\nhich case is covered: with UseGray=false the file\ngoes straight to go-face's JPEG-only loader, so PNG fails there --\ndocumented and tested as the boundary of the workaround, not silently\nglossed over.",
"is_bot": false,
"headline": "Document and test PNG support via UseGray (Kagami/go-face#45)",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T14:20:37Z",
"body_truncated": true,
"is_coding_agent": false
},
{
"oid": "726d9000dbdbfd5c7b53a8a96b650a6379cebc94",
"body": "Same pattern as Model.Landmark: set before Init to point the resnet\ndescriptor and/or CNN detector loading at differently-named or\nfine-tuned model files, instead of go-face's defaults. Backed by\ngo-face v1.0.4's generalized NewRecognizerWithModels.\n\nAdded regression tests proving both are genuinely honored (a wrong\nfilename fails to load; a renamed file loads and produces working\ndescriptors/detections through the configured name, not the default).",
"is_bot": false,
"headline": "Expose Model.Descriptor and Model.CNN alongside Model.Landmark",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T14:08:05Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "eb7f62d4cf0cc7a2b15b3f9112b7fe99d541c961",
"body": "No tests existed before this -- the grayscale/JPEG regression found\nearlier this session was only caught by manually exercising\nAddImageToDataset end-to-end, not by build/vet. Uses the models/photos\nalready checked into examples/ rather than duplicating fixtures.\n\nrecognizer_test.go:\n- Init loads th\n[…]\n), with no dlib/model files needed.\n- DrawFaces/DrawFaces2/DrawLandmarks smoke tests using synthesized\n Face/goFace.Face values, also without needing real detection.\n- SaveImage/LoadImage round trip.",
"is_bot": false,
"headline": "Add automated test suite",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T13:53:42Z",
"body_truncated": true,
"is_coding_agent": false
},
{
"oid": "b569b2ba4d4c79871e36ab82a932e97ea9129c5b",
"body": null,
"is_bot": false,
"headline": "README: document rec.Model.Landmark (68-point landmark option)",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T13:48:45Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "34692ab181c16593f3cbcb1a56297273cdcccfa8",
"body": "Set rec.Model.Landmark = \"shape_predictor_68_face_landmarks.dat\" before\nInit for full facial contour landmarks (jawline, eyebrows, nose bridge,\neyes, lips) in Face.Shapes, instead of the default 5-point model. Backed\nby go-face v1.0.3's NewRecognizerWithShapePredictor.\n\nVerified end-to-end: 68-point model returns 68 shapes and draws the full\ncontour via DrawLandmarks; default (empty Model.Landmark) still returns\n5 shapes as before.",
"is_bot": false,
"headline": "Add Model.Landmark to select a non-default shape predictor",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T13:47:41Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "b75cfd85fd0ed16532367a7c7fdbf50a47be4cc7",
"body": "- New Features bullets for incremental dataset updates, match\n distance/confidence, and landmarks.\n- Face recognition example updated to match recognition/main.go (no\n more SetSamples() call, prints Distance/Confidence per match).\n- New Face landmarks section with the landmarks/ example and result\n image.\n- Note that examples now live one per subfolder and must be run from\n inside examples/.",
"is_bot": false,
"headline": "README: document landmarks/distance/confidence, add landmarks example",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T13:33:12Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "4c59ba72d888319fcb142ba907e8ff95bd81e5dc",
"body": "- Move detection.go and recognition.go into their own detection/ and\n recognition/ packages: both were package main with their own\n func main() in the same directory, so go build ./... in this module\n has never actually succeeded until now.\n- New landmarks/ example: runs RecognizeSingle on fotos/\n[…]\nfier in sync incrementally as of\n go-recognizer v1.0.5) and prints each match's Distance/Confidence.\n- Bump to go-recognizer v1.0.5 / go-face v1.0.2.\n- Regenerate faces.jpg/faces2.jpg output samples.",
"is_bot": false,
"headline": "examples: reorganize into subfolders, add landmarks example",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T13:31:51Z",
"body_truncated": true,
"is_coding_agent": false
},
{
"oid": "50b70e945b8157233b64f75e7f79315da04ea323",
"body": "…ssion\n\n- Face gains Shapes ([]image.Point, the facial landmark points already\n returned by go-face but previously dropped), Distance (squared\n Euclidean distance to the matched Dataset entry), and Confidence (a\n convenience 1-Distance/Tolerance score in [0,1], not a calibrated\n probability). Po\n[…]\ngeToDataset end-to-end with real models\n during this change, not by build/vet alone. Now builds an *image.NRGBA\n from grayscale-converted pixels instead, which still encodes as a\n 3-component JPEG.",
"is_bot": false,
"headline": "Expose landmarks, match distance/confidence; fix grayscale JPEG regre…",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T13:29:34Z",
"body_truncated": true,
"is_coding_agent": false
},
{
"oid": "6580ae7af2dbffa5726fa87eafd7a710e176d0ea",
"body": null,
"is_bot": false,
"headline": "examples: bump go-recognizer to v1.0.4 (arch-aware go-face CXXFLAGS)",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T13:11:14Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "d0c10919c9fdae6793b226ca935760b62d7369d7",
"body": "- go-face v1.0.1 fixes an ARM/Apple Silicon build regression introduced\n by v1.0.0's hardcoded -march=x86-64.\n- Drop the Go Report Card badge: the service has been sunset (the page\n now shows a static \"thank you\" notice instead of grading repos).\n- Document that go-face needs CGO_ENABLED=1; without it the build fails\n with confusing \"undefined: face.NewRecognizer\" errors instead of a\n compiler error.",
"is_bot": false,
"headline": "Bump go-face to v1.0.1 (arch-aware CXXFLAGS); README cleanup",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T13:09:40Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "7975d6ef7b35ab3edcb745a3943f2862c68882ed",
"body": "- Add an intro paragraph and a features list instead of jumping\n straight to install instructions.\n- Swap the dead godoc.org badge for pkg.go.dev, add a latest-tag badge.\n- Fix grammar issues and tidy formatting/spacing.\n- Point the examples at examples/ so the README code stays honest\n about being runnable, and fix the faces2.jpeg/faces2.jpg mismatch.\n- Add Contributing and License sections.",
"is_bot": false,
"headline": "Rewrite README for clarity and discoverability",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T12:52:18Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "e634136b4a9451e60898f870d5c3ea3a23ca3a71",
"body": "Classify/ClassifyMultiples index into Dataset using positions captured\nat the last SetSamples call, so those positions go stale as soon as\nAddImageToDataset, LoadDataset, or Init change Dataset underneath them.\nThis was already true before the mutex work; it just wasn't written\ndown anywhere.",
"is_bot": false,
"headline": "Document the SetSamples/Dataset consistency contract",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T12:44:41Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "87ed4ee68cdf21ae70ac6f19eb0d6026b1d6ab47",
"body": null,
"is_bot": false,
"headline": "examples: bump go-recognizer to v1.0.3 (leandroveronezi/go-face fork)",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T12:36:34Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "84557c1c6397e6120bd0e6b135e1287df2c0bea6",
"body": "Upstream Kagami/go-face has had no recent activity and ships a\nhardcoded -march=native CXXFLAGS that breaks builds on CI/containers\nwhose compiler doesn't recognize the reported host architecture.\nSwitch to a maintained fork that fixes it, so this build-portability\nfix reaches everyone who depends on go-recognizer instead of only\nworking when go-recognizer's own go.mod has a replace directive\n(which wouldn't propagate to downstream consumers).",
"is_bot": false,
"headline": "Depend on github.com/leandroveronezi/go-face instead of Kagami/go-face",
"author_name": "Leandro",
"author_login": null,
"committed_at": "2026-07-18T12:34:39Z",
"body_truncated": false,
"is_coding_agent": false
},
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"status": "partial",
"details": [
{
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}
],
"max_points": 25
},
{
"key": "track_record",
"name": "Track record",
"detail": "21 public repos, account ~9 yr old",
"points": 21.8,
"status": "partial",
"details": [
{
"code": "public_repos",
"params": {
"count": 21
}
},
{
"code": "account_age_years",
"params": {
"years": 9
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}
],
"max_points": 25
}
]
},
{
"key": "package_maintenance",
"band": "excellent",
"name": "Package maintenance",
"note": null,
"notes": [],
"value": 100,
"inputs": {
"packages": [
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],
"ecosystems": "go",
"any_deprecated": false,
"min_days_since_publish": 1
},
"components": [
{
"key": "published_resolvable",
"name": "Published & resolvable",
"detail": "1 package(s) on go",
"points": 25,
"status": "met",
"details": [
{
"code": "packages_published",
"params": {
"count": 1,
"ecosystems": "go"
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}
],
"max_points": 25
},
{
"key": "publish_recency",
"name": "Publish recency",
"detail": "latest publish 1 days ago",
"points": 35,
"status": "met",
"details": [
{
"code": "publish_recency",
"params": {
"days": 1
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}
],
"max_points": 35
},
{
"key": "version_history",
"name": "Version history",
"detail": "11 published versions",
"points": 20,
"status": "met",
"details": [
{
"code": "published_versions",
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}
}
],
"max_points": 20
},
{
"key": "not_deprecated",
"name": "Not deprecated",
"detail": "active, not deprecated or yanked",
"points": 20,
"status": "met",
"details": [
{
"code": "package_not_deprecated",
"params": {}
}
],
"max_points": 20
}
]
}
],
"description": "Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?"
},
{
"key": "engineering",
"band": "moderate",
"name": "Engineering Quality",
"value": 62,
"weight": 0.2,
"metrics": [
{
"key": "engineering_practices",
"band": "moderate",
"name": "Engineering practices",
"note": "Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.",
"notes": [
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"code": "excluded_no_data",
"params": {
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},
{
"code": "weights_renormalized",
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"inputs": {
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"has_tests": true,
"has_editorconfig": false,
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"components": [
{
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"points": 24,
"status": "met",
"details": [
{
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}
}
],
"max_points": 24
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{
"key": "tests_present",
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"detail": null,
"points": 24,
"status": "met",
"details": [],
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},
{
"key": "linter_config",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
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},
{
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"points": 0,
"status": "missed",
"details": [],
"max_points": 9.6
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{
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{
"key": "openssf_scorecard_ci_tests",
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"points": 0,
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],
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},
{
"key": "documentation",
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"note": null,
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"inputs": {
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"components": [
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{
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{
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},
{
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"points": 10,
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"details": [
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"name": "Wiki",
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"points": 0,
"status": "missed",
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}
],
"description": "Are baseline engineering and documentation practices in place?"
},
{
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"name": "Security",
"value": 58,
"weight": 0.16,
"metrics": [
{
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"notes": [
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"params": {
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},
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],
"value": 47,
"inputs": {
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"points": 7.5,
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},
{
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"points": 0,
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},
{
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{
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},
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"status": "met",
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},
{
"key": "dependency_update_tool",
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"detail": "update tool detected",
"points": 7.5,
"status": "met",
"details": [],
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},
{
"key": "fuzzing",
"name": "Fuzzing",
"detail": "project is not fuzzed",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "license",
"name": "License",
"detail": "license file detected",
"points": 2.5,
"status": "met",
"details": [],
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},
{
"key": "maintained",
"name": "Maintained",
"detail": "30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10",
"points": 7.5,
"status": "met",
"details": [],
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},
{
"key": "packaging",
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"detail": "packaging workflow not detected",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 5
},
{
"key": "pinned_dependencies",
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"status": "missed",
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},
{
"key": "sast",
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"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "security_policy",
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"detail": "security policy file not detected",
"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "signed_releases",
"name": "Signed-Releases",
"detail": "no releases found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
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},
{
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"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
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"points": 7.5,
"status": "met",
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}
]
},
{
"key": "dependency_advisories",
"band": "excellent",
"name": "Dependency advisories",
"note": "Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 5 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.",
"notes": [
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"code": "excluded_no_data",
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},
{
"code": "advisories_scope_repository",
"params": {
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}
},
{
"code": "advisories_repo_graph_caveat",
"params": {}
},
{
"code": "advisories_reachability",
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}
],
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"inputs": {
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"direct_affected_packages": 0
},
"components": [
{
"key": "direct_dependencies_free_of_known_advisories",
"name": "Direct dependencies free of known advisories",
"detail": "no direct dependency carries a known advisory",
"points": 35,
"status": "met",
"details": [
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}
],
"max_points": 35
},
{
"key": "indirect_dependencies_free_of_known_advisories",
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"points": 0,
"status": "excluded",
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"max_points": 25
},
{
"key": "no_advisories_left_outstanding",
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"points": 0,
"status": "excluded",
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],
"max_points": 40
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]
},
{
"key": "malicious_dependencies",
"band": "excellent",
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"note": null,
"notes": [],
"value": 100,
"inputs": {
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"meaning": "reported as a malicious package by the OpenSSF corpus; the remedy is removal or moving off the compromised name, never an upgrade of the same artifact. Versions the registry has since pulled are listed but not scored",
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"direct_malicious_packages": 0,
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"components": [
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"points": 100,
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"details": [
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"code": "no_malicious_dependencies",
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}
],
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]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
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"name": "AI Readiness",
"value": 58,
"weight": 0,
"metrics": [
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"key": "ai_agent_context",
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"note": null,
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"inputs": {
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"components": [
{
"key": "agent_instructions",
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"details": [
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],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
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"points": 0,
"status": "missed",
"details": [],
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{
"key": "legible_commit_history",
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"points": 27.5,
"status": "partial",
"details": [
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"code": "legible_history",
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]
},
{
"key": "ai_verify_loop",
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"note": null,
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"status": "partial",
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{
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"points": 22,
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{
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"points": 0,
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{
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{
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],
"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."
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],
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"warnings": [],
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"generated_at": "2026-07-22T08:45:48.249276Z",
"schema_version": "0.26.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/l/leandroveronezi/go-recognizer.svg",
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"license_state": "standard",
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}
Related records
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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 v1.13.0, schema v0.26.0 — full methodology · metrics wiki.
