Public recordGood
Software health reportschema 0.11.0 · metrics 1.13.0 · 2026-07-15 16:55 UTC
cognizant-ai-lab / neuro-san
Neuro AI System of Agent Networks
cognizant-ai-lab/neuro-san holds a health index of 79 out of 100, placing it in the Good band. It scores highest on Vitality (100/100) and lowest on AI Readiness (42/100). It was last updated today. A single contributor accounts for most of its recent work.
79
overall / 100Software 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.
79
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.
Ownership
Cognizant AI LabOrganization
188 followers18 public repossince Dec 2018
This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.
Package ecosystems
| Registry | Package | Version | Downloads / mo | Versions | Last publish | Tags |
|---|---|---|---|---|---|---|
| PyPI | neuro-san | 0.6.79 | - | 129 | 0 days ago | llmlangchainagentmulti-agent |
Metrics by category
Vitality
Is the project alive — is code being written and are releases shipping?
100
Development activity
100Excellent
How it's scored
| 36/36 | Push recency — last push 0 days ago |
| 36/36 | Commit cadence — 52/52 weeks with commits |
| 18/18 | Commit volume — 3,078 commits in the last year |
| 0/10 | OpenSSF Scorecard: Maintained — no data |
Inputs used
| commits_last_year | 3,078 |
| human_commit_share | — |
| days_since_last_push | 0 |
| active_weeks_last_year | 52 |
Release discipline
100Excellent
How it's scored
| 27/27 | Ships releases — 100 releases published |
| 36/36 | Release recency — latest release 0 days ago |
| 27/27 | Release cadence — a release every ~0.9 days |
| 0/10 | OpenSSF Scorecard: Signed-Releases — no data |
Inputs used
| releases_count | 100 |
| latest_release_tag | 0.6.79 |
| releases_from_tags | no |
| days_since_latest_release | 0 |
| mean_days_between_releases | 0.9 |
Community & Adoption
Does the project have users, downloads, attention, and a welcoming setup for contributors?
68
Popularity & adoption
53Moderate
How it's scored
| 34.6/60 | Stars — 136 stars |
| 13.5/25 | Forks — 43 forks |
| 5.3/15 | Watchers — 10 watchers |
Inputs used
| forks | 43 |
| stars | 136 |
| watchers | 10 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community health
85Excellent
How it's scored
| 22.5/22.5 | README |
| 22.5/22.5 | License — recognized license (Apache-2.0) |
| 18/18 | CONTRIBUTING guide |
| 13.5/13.5 | Code of conduct |
| 0/7.2 | Issue template |
| 0/6.3 | PR template |
Inputs used
| has_readme | yes |
| has_license | yes |
| has_contributing | yes |
| has_issue_template | no |
| has_code_of_conduct | yes |
| has_pull_request_template | no |
Sustainability & Governance
Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?
68
Maintainer resilience (bus factor)
37At risk
How it's scored
| 9/54 | Bus factor — 1 contributor(s) cover half of all commits |
| 10.7/22.5 | Commit distribution — top contributor authored 53% of commits |
| 13.5/13.5 | Contributor breadth — 21 contributors |
| 0/10 | OpenSSF Scorecard: Contributors — no data |
Inputs used
| bus_factor | 1 |
| contributors_sampled | 21 |
| top_contributor_share | 0.526 |
How it's scored
| 32.3/46.8 | Issue resolution — 69% of issues closed |
| 35.9/38.3 | PR acceptance — 709/756 decided PRs merged |
| 0/15 | OpenSSF Scorecard: Code-Review — no data |
Inputs used
| merged_prs | 709 |
| open_issues | 102 |
| closed_issues | 227 |
| issue_closed_ratio | 0.69 |
| closed_unmerged_prs | 47 |
Ownership & stewardship
68Moderate
How it's scored
| 30/30 | Ownership backing — organization-owned |
| 0/20 | Verified domain |
| 16.4/25 | Owner reach — 188 followers of cognizant-ai-lab |
| 21.3/25 | Track record — 18 public repos, account ~7 yr old |
Inputs used
| followers | 188 |
| owner_type | Organization |
| is_verified | — |
| owner_login | cognizant-ai-lab |
| public_repos | 18 |
| account_age_days | 2,778 |
Package maintenance
100Excellent
How it's scored
| 25/25 | Published & resolvable — 1 package(s) on pypi |
| 35/35 | Publish recency — latest publish 0 days ago |
| 20/20 | Version history — 129 published versions |
| 20/20 | Not deprecated — active, not deprecated or yanked |
Inputs used
| packages | neuro-san |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 0 |
Engineering Quality
Are baseline engineering and documentation practices in place?
88
Engineering practices
80Good
How it's scored
| 24/24 | CI workflows — 6 workflow(s) |
| 24/24 | Tests present |
| 16/16 | Linter config — .flake8, .pylintrc |
| 0/9.6 | Pre-commit hooks |
| 0/6.4 | .editorconfig |
| 0/20 | OpenSSF Scorecard: CI-Tests — no data |
Inputs used
| has_ci | yes |
| has_tests | yes |
| has_editorconfig | no |
| has_linter_config | yes |
| has_precommit_config | no |
Documentation
100Excellent
How it's scored
| 30/30 | README |
| 25/25 | Documentation directory |
| 15/15 | Documentation / homepage site — https://decisionai.ml/neuro-san |
| 10/10 | Repository description |
| 10/10 | Topics — 14 topics |
| 10/10 | Wiki |
Inputs used
| topics | agents, ai, ai-agents, mas, multi-agent-systems, mutli-agent, ai-agents-framework, langchain, multi-agent-framework, agentic-ai, agentic-framework, llms, aaosa, sly-data |
| has_wiki | yes |
| homepage | https://decisionai.ml/neuro-san |
| has_readme | yes |
| has_docs_dir | yes |
| has_description | yes |
Security
Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?
67
Security posture
67Moderate
How it's scored
| 30/30 | Security policy (SECURITY.md) |
| 0/25 | Dependabot config |
| 0/25 | Dependency lockfiles — published library — lockfiles are an application concern, not expected |
| 20/20 | CodeQL workflow |
Inputs used
| source | file_signals |
| lockfiles | — |
| manifests | pyproject.toml, requirements-build.txt, requirements.txt, setup.py |
| has_codeql_workflow | yes |
| has_security_policy | yes |
| has_dependabot_config | no |
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? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score.
42
Agent context & guidance
1Critical
How it's scored
| 0/45 | Agent instructions — no CLAUDE.md / AGENTS.md / editor rules |
| 0/15 | Machine-readable docs (llms.txt) |
| 0/40 | Legible commit history — no data |
Inputs used
| has_llms_txt | no |
| legible_history_share | — |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
Verify loop (build / test / typecheck)
60Moderate
How it's scored
| 0/18 | One-command bootstrap |
| 22/22 | Automated tests |
| 11/11 | Lint / format config — .flake8, .pylintrc |
| 0/11 | Static type checking |
| 10/10 | Reproducible environment — Dockerfile |
| 0/10 | Demonstrated agent practice — no data |
| 0/8 | Automated maintenance — no data |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — no data |
Inputs used
| has_nix | no |
| has_tests | yes |
| lockfiles | — |
| has_dockerfile | yes |
| typed_language | no |
| bootstrap_files | — |
| has_devcontainer | no |
| has_linter_config | yes |
| typecheck_configs | — |
| agent_commit_share | — |
| toolchain_manifests | — |
| dependency_bot_commit_share | — |
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.
Code legibility for models
55Moderate
How it's scored
| 0/45 | Type-checkable code — Python without a type-check config |
| 55/55 | Manageable file sizes — 0/519 source files over 60KB |
Inputs used
| primary_language | Python |
| largest_source_bytes | 36,180 |
| source_files_sampled | 519 |
| oversized_source_files | 0 |
Machine-readable interfaces
60Moderate
How it's scored
| 40/40 | API schema (OpenAPI/GraphQL/proto) — neuro_san/api/grpc/agent.proto, neuro_san/api/grpc/chat.proto, neuro_san/api/grpc/concierge.proto, neuro_san/api/grpc/google/api/annotations.proto, neuro_san/api/grpc/google/api/http.proto, neuro_san/api/grpc/mime_data.proto |
| 20/20 | MCP server |
| 0/40 | Runnable examples |
Inputs used
| example_dirs | — |
| has_mcp_signal | yes |
| api_schema_files | neuro_san/api/grpc/agent.proto, neuro_san/api/grpc/chat.proto, neuro_san/api/grpc/concierge.proto, neuro_san/api/grpc/google/api/annotations.proto, neuro_san/api/grpc/google/api/http.proto, neuro_san/api/grpc/mime_data.proto |
Key facts
136GitHub stars
21contributors
3,078commits, last 12 months
0days since last push
100releases
1bus factor
102open issues
PyPIpackage ecosystems
Data collection warnings
- OpenSSF Scorecard timed out after 240s; skipping Scorecard checks
More detail
All dependencies 62
Full resolved dependency set from the GitHub dependency graph: 0 direct and 62 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
| Registry | Package | Version | Relation |
|---|---|---|---|
| PyPI | aiobotocore | — | indirect |
| PyPI | aiofiles | — | indirect |
| PyPI | aiohttp | — | indirect |
| PyPI | boto3 | — | indirect |
| PyPI | botocore | — | indirect |
| PyPI | bs4 | — | indirect |
| PyPI | build | — | indirect |
| PyPI | cmarkgfm | — | indirect |
| PyPI | coverage | 7.6.1 | indirect |
| PyPI | croniter | — | indirect |
| PyPI | flake8 | 7.3.0 | indirect |
| PyPI | grpcio | — | indirect |
| PyPI | grpcio-tools | — | indirect |
| PyPI | httpx | — | indirect |
| PyPI | idna | — | indirect |
| PyPI | janus | — | indirect |
| PyPI | json-repair | — | indirect |
| PyPI | jsonschema | — | indirect |
| PyPI | langchain | — | indirect |
| PyPI | langchain-anthropic | — | indirect |
| PyPI | langchain-aws | — | indirect |
| PyPI | langchain-classic | — | indirect |
| PyPI | langchain-community | — | indirect |
| PyPI | langchain-core | — | indirect |
| PyPI | langchain-google-genai | — | indirect |
| PyPI | langchain-mcp-adapters | — | indirect |
| PyPI | langchain-nvidia-ai-endpoints | — | indirect |
| PyPI | langchain-ollama | — | indirect |
| PyPI | langchain-openai | — | indirect |
| PyPI | langchain-openrouter | — | indirect |
| PyPI | langfuse | — | indirect |
| PyPI | leaf-common | — | indirect |
| PyPI | leaf-server-common | — | indirect |
| PyPI | mcp | — | indirect |
| PyPI | objsize | — | indirect |
| PyPI | openfga-sdk | — | indirect |
| PyPI | parameterized | — | indirect |
| PyPI | protobuf | — | indirect |
| PyPI | psutil | — | indirect |
| PyPI | pydantic | — | indirect |
| PyPI | pyhocon | — | indirect |
| PyPI | pylint | 4.0.2 | indirect |
| PyPI | pylint-protobuf | 0.22.0 | indirect |
| PyPI | pymarkdownlnt | 0.9.30 | indirect |
| PyPI | pyopenssl | — | indirect |
| PyPI | pytest | 9.0.3 | indirect |
| PyPI | pytest-asyncio | 1.3.0 | indirect |
| PyPI | pytest-cov | 5.0.0 | indirect |
| PyPI | pytest-timeout | — | indirect |
| PyPI | pytest-timer | 1.0.0 | indirect |
| PyPI | pytest-xdist | — | indirect |
| PyPI | readme-renderer | — | indirect |
| PyPI | ruamel-yaml | — | indirect |
| PyPI | setuptools | — | indirect |
| PyPI | setuptools-scm | 8.1.0 | indirect |
| PyPI | timedinput | — | indirect |
| PyPI | timeout-decorator | 0.5.0 | indirect |
| PyPI | tornado | — | indirect |
| PyPI | urllib3 | — | indirect |
| PyPI | validators | — | indirect |
| PyPI | watchdog | — | indirect |
| PyPI | wheel | — | indirect |
Raw JSON report machine-readable
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"requirements.txt",
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],
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},
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"status": "met",
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"max_points": 30
},
{
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"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "dependency_lockfiles",
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"points": 0,
"status": "excluded",
"details": [
{
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"params": {}
}
],
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},
{
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}
]
},
{
"key": "high_risk_jurisdiction_exposure",
"band": "excellent",
"name": "High-Risk Jurisdiction Exposure",
"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
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"red_flag": false,
"exposures": [],
"policy_countries": [
"Russia",
"Iran",
"North Korea"
],
"review_only_matches": 0,
"assessed_self_published_locations": 1
},
"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "at_risk",
"name": "AI Readiness",
"value": 42,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "critical",
"name": "Agent context & guidance",
"note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"legible_commit_history"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 1,
"inputs": {
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"legible_history_share": null,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
"name": "Machine-readable docs (llms.txt)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
"name": "Legible commit history",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "moderate",
"name": "Verify loop (build / test / typecheck)",
"note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
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]
}
},
{
"code": "weights_renormalized",
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}
],
"value": 60,
"inputs": {
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"lockfiles": [],
"has_dockerfile": true,
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"bootstrap_files": [],
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"typecheck_configs": [],
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"toolchain_manifests": [],
"dependency_bot_commit_share": null
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 18
},
{
"key": "automated_tests",
"name": "Automated tests",
"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
"name": "Lint / format config",
"detail": ".flake8, .pylintrc",
"points": 11,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
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}
],
"max_points": 11
},
{
"key": "static_type_checking",
"name": "Static type checking",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "reproducible_environment",
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"detail": "Dockerfile",
"points": 10,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "Dockerfile"
}
}
],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
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"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 8
},
{
"key": "openssf_scorecard_pinned_dependencies",
"name": "OpenSSF Scorecard: Pinned-Dependencies",
"detail": "OpenSSF Scorecard unavailable",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 10
}
]
},
{
"key": "ai_code_legibility",
"band": "moderate",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 55,
"inputs": {
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"largest_source_bytes": 36180,
"source_files_sampled": 519,
"oversized_source_files": 0
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Python without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Python"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "0/519 source files over 60KB",
"points": 55,
"status": "met",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 519,
"oversized": 0
}
}
],
"max_points": 55
}
]
},
{
"key": "ai_interfaces",
"band": "moderate",
"name": "Machine-readable interfaces",
"note": null,
"notes": [],
"value": 60,
"inputs": {
"example_dirs": [],
"has_mcp_signal": true,
"api_schema_files": [
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"neuro_san/api/grpc/google/api/http.proto",
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]
},
"components": [
{
"key": "api_schema_openapi_graphql_proto",
"name": "API schema (OpenAPI/GraphQL/proto)",
"detail": "neuro_san/api/grpc/agent.proto, neuro_san/api/grpc/chat.proto, neuro_san/api/grpc/concierge.proto, neuro_san/api/grpc/google/api/annotations.proto, neuro_san/api/grpc/google/api/http.proto, neuro_san/api/grpc/mime_data.proto",
"points": 40,
"status": "met",
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{
"code": "file_list",
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}
}
],
"max_points": 40
},
{
"key": "mcp_server",
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"detail": null,
"points": 20,
"status": "met",
"details": [],
"max_points": 20
},
{
"key": "runnable_examples",
"name": "Runnable examples",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 40
}
]
}
],
"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."
}
],
"metrics_version": "1.13.0"
},
"warnings": [
"OpenSSF Scorecard timed out after 240s; skipping Scorecard checks"
],
"report_type": "repository",
"generated_at": "2026-07-15T16:55:54.807362Z",
"schema_version": "0.11.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/c/cognizant-ai-lab/neuro-san.svg",
"full_name": "cognizant-ai-lab/neuro-san",
"license_state": "standard",
"license_spdx": "Apache-2.0"
}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 v0.11.0 — full methodology · metrics wiki.
How one result sits in the wider record: aggregate statistics — PyPI.