Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-16 17:21 UTC

GiacomoSaccaggi / scomp_link

End-to-end ML toolkit automating the complete workflow — data profiling, preprocessing, feature engineering, model selection, training, validation, explainability, drift monitoring, fairness checks, and interactive HTML reporting. Includes a full CLI for zero-code ML pipelines. Python 3.10+.

PythonMIT★ 2 stars⑂ 0 forkssince Feb 2026View on GitHub ↗
KindCommand-line toolLibraryMCP serverhow this is determined
#anomaly-detection#automl#cli#data-science#explainability#machine-learning#nlp#python#scikit-learn#time-series#agent-skills#agentic-workflow#mcp#mcp-server#ai-agent-tool#ai-tools#cli-app#cli-tool#claude-tool#kiro-tool

GiacomoSaccaggi/scomp_link holds a health index of 80 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (95/100) and lowest on Sustainability & Governance (46/100). It was last updated today.

80
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.

80
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 68 is calibrated to 80 on the published index scale (record calibration 2026-08-02).

Ownership

Giacomo SaccaggiPersonal account
7 followers18 public repossince Oct 2018

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
PyPIscomp-link1.3.02,313210 days agomachine-learningdata-scienceautomationpipelineautomlscikit-learnregressionclassificationclusteringdeep-learningnlptext-classificationcontrastive-learninganomaly-detectiontime-seriesensemble-learninghyperparameter-tuningmodel-selectioncross-validationfeature-selectionberttransformerstensorflowpytorchcomputer-visionimage-classificationhtml-reportplotlyedapreprocessingmcpmodel-context-protocolagent-toolai-agentdata-driftmodel-serving

Metrics by category

Vitality

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

79Good · 21% of overall

Development activity

65Good
How it's scored
36/36Push recency — last push 0 days ago
4.8/36Commit cadence — 7/52 weeks with commits
17.9/18Commit volume — 98 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year98
human_commit_share—
days_since_last_push0
active_weeks_last_year7

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 13 releases published
36/36Release recency — latest release 6 days ago
27/27Release cadence — a release every ~0.8 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count13
latest_release_tagv1.2.15
releases_from_tagsno
days_since_latest_release6
mean_days_between_releases0.8

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

47Weak · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 2 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars2
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges—
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services—
has_pull_request_templateyes

Ecosystem adoption (downloads)

56Moderate
How it's scored
44.9/80Monthly downloads — 2,313 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesscomp-link
dependents—
ecosystemspypi
total_downloads—
monthly_downloads2,313
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?

46Weak · 23% of overall

Issue & PR responsiveness

1Critical
How it's scored
0/42Issue resolution — no issues or no data
0/30PR acceptance — 0/25 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_prs0
open_issues0
closed_issues0
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio—
closed_unmerged_prs25
first_time_authors_30d—
first_time_prs_merged_30d—
first_time_prs_decided_30d—
Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

47Weak
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
6.5/25Owner reach — 7 followers of GiacomoSaccaggi
21.3/25Track record — 18 public repos, account ~7 yr old
Inputs used
followers7
owner_typeUser
is_verified—
owner_loginGiacomoSaccaggi
public_repos18
account_age_days2,833
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

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 — 21 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesscomp-link
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

95Exceptional · 19% of overall

Engineering practices

92Excellent
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 — no data
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://giacomosaccaggi.github.io/scomp_link/
10/10Repository description
10/10Topics — 20 topics
10/10Wiki
Inputs used
topicsanomaly-detection, automl, cli, data-science, explainability, machine-learning, nlp, python, scikit-learn, time-series, agent-skills, agentic-workflow, mcp, mcp-server, ai-agent-tool, ai-tools, cli-app, cli-tool, claude-tool, kiro-tool
has_wikiyes
homepagehttps://giacomosaccaggi.github.io/scomp_link/
docs_sitehttps://giacomosaccaggi.github.io/scomp_link/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

73Good · 16% of overall

Security posture

73Good
How it's scored
30/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfilesuv.lock
manifestsmcpb/pyproject.toml, pyproject.toml, requirements.txt, requirements/requirements-dev.txt, requirements/requirements-img-py310.txt, requirements/requirements-img-py311.txt, requirements/requirements-img-py312.txt, requirements/requirements-img-py313.txt, requirements/requirements-nlp-py310.txt, requirements/requirements-nlp-py311.txt, requirements/requirements-nlp-py312.txt, requirements/requirements-nlp-py313.txt, requirements/requirements-py310.txt, requirements/requirements-py311.txt, requirements/requirements-py312.txt, requirements/requirements-py313.txt, requirements/requirements-utils.txt, setup.py
has_codeql_workflowno
has_security_policyyes
has_dependabot_configyes
Excluded from scoring (no data or not applicable): Dependency lockfiles. 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.

87Excellent · 4% of overall

Agent context & guidance

100Exceptional
How it's scored
45/45Agent instructions — AGENTS.md
15/15Machine-readable docs (llms.txt) — llms.txt present
0/40Legible commit history — no data
Inputs used
has_llms_txtyes
llms_txt_url—
legible_history_share—
agent_instruction_filesAGENTS.md
agent_instruction_max_bytes4,895
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

74Good
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — tox.ini
11/11Static type checking — pyrightconfig.json, scomp_link/py.typed
10/10Reproducible environment — Dockerfile, lockfile
0/10Demonstrated agent practice — no data
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configspyrightconfig.json, scomp_link/py.typed
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (pyrightconfig.json, scomp_link/py.typed)
54.5/55Manageable file sizes — 1/105 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes81,108
source_files_sampled105
oversized_source_files1

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
40/40Runnable examples — examples
Inputs used
example_dirsexamples
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

2GitHub stars
-contributors
98commits, last 12 months
0days since last push
13releases
-bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Contributor list unavailable
  • Could not fetch pypi package 'scomp-link-mcpb' from its registry
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Direct dependencies 56
RegistryPackageVersion constraintManifest
PyPIscomp-link>=1.3.0mcpb/pyproject.toml
PyPInumpy>=1.22.0,<2.3.0pyproject.toml
PyPInumpy>=1.24.0,<1.27.0pyproject.toml
PyPInumpy>=1.26.0,<2.0.0pyproject.toml
PyPInumpy>=1.26.0,<3.0.0pyproject.toml
PyPInumpy>=2.0.0,<3.0.0pyproject.toml
PyPIpandas>=1.4.0,<2.4.0pyproject.toml
PyPIpandas>=2.0.0,<2.2.0pyproject.toml
PyPIpandas>=2.1.0,<2.3.0pyproject.toml
PyPIpandas>=2.1.0,<3.0.0pyproject.toml
PyPIpandas>=2.2.0,<3.0.0pyproject.toml
PyPIscipy>=1.8.0,<1.12.0pyproject.toml
PyPIscipy>=1.10.0,<1.12.0pyproject.toml
PyPIscipy>=1.11.0,<1.14.0pyproject.toml
PyPIscipy>=1.11.0,<2.0.0pyproject.toml
PyPIscipy>=1.14.0,<2.0.0pyproject.toml
PyPIscikit-learn>=1.2.0,<1.8.0pyproject.toml
PyPIscikit-learn>=1.3.0,<1.5.0pyproject.toml
PyPIscikit-learn>=1.3.0,<1.6.0pyproject.toml
PyPIscikit-learn>=1.3.0,<2.0.0pyproject.toml
PyPIscikit-learn>=1.5.0,<2.0.0pyproject.toml
PyPImatplotlib>=3.6.0,<3.9.0pyproject.toml
PyPImatplotlib>=3.7.0,<3.9.0pyproject.toml
PyPImatplotlib>=3.8.0,<3.11.0pyproject.toml
PyPImatplotlib>=3.8.0,<4.0.0pyproject.toml
PyPImatplotlib>=3.9.0,<4.0.0pyproject.toml
PyPIplotly>=5.0.0,<6.0.0pyproject.toml
PyPIseaborn>=0.11.0,<0.14.0pyproject.toml
PyPItorch>=1.13.0,<2.13.0pyproject.toml
PyPItorch>=2.0.0,<2.13.0pyproject.toml
PyPItorch>=2.0.0,<2.13.0pyproject.toml
PyPItorch>=2.0.0,<3.0.0pyproject.toml
PyPItorch>=2.4.0,<3.0.0pyproject.toml
PyPItransformers>=4.30.0,<6.0.0pyproject.toml
PyPIspacy>=3.5.0,<4.0.0pyproject.toml
PyPIfaiss-cpu>=1.7.0,<2.0.0pyproject.toml
PyPIsentence-transformers>=2.2.0,<6.0.0pyproject.toml
PyPItensorflow>=2.10.0,<2.16.0pyproject.toml
PyPItensorflow>=2.12.0,<2.16.0pyproject.toml
PyPItensorflow>=2.13.0,<2.18.0pyproject.toml
PyPItensorflow>=2.13.0,<3.0.0pyproject.toml
PyPIpillow>=9.0.0,<13.0.0pyproject.toml
PyPIpillow>=10.0.0,<13.0.0pyproject.toml
PyPIpytorch-tabnet2>=4.1.0,<5.0.0pyproject.toml
PyPIstatsmodels>=0.13.0,<1.0.0pyproject.toml
PyPItf-keras>=2.16.0pyproject.toml
PyPIpolars>=0.20.0,<2.0.0pyproject.toml
PyPIpyarrow>=12.0.0pyproject.toml
PyPIshap>=0.42.0,<1.0.0pyproject.toml
PyPIlime>=0.2.0,<1.0.0pyproject.toml
PyPIoptuna>=3.0.0,<5.0.0pyproject.toml
PyPItqdm>=4.50.0,<5.0.0pyproject.toml
PyPIPyJWT>=2.0.0,<3.0.0pyproject.toml
PyPImarkdown>=3.3.0,<4.0.0pyproject.toml
PyPIweasyprint>=57.0,<70.0pyproject.toml
PyPIplaywright>=1.40.0,<2.0.0pyproject.toml
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

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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 v0.11.0 — full methodology · metrics wiki.

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