Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-09 00:14 UTC

ramdhavepreetam / NervaPack

PythonMIT★ 1 star⑂ 0 forkssince Jun 2026View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

ramdhavepreetam/NervaPack holds a health index of 53 out of 100, placing it in the Moderate band. It scores highest on Vitality (75/100) and lowest on Security (14/100). It was last updated 15 days ago. A single contributor accounts for most of its recent work.

53
overall / 100
Moderate

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.

53
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 52 is calibrated to 53 on the published index scale (record calibration 2026-08-02).

Ownership

Preetam RamdhavePersonal account
3 followers58 public repossince Nov 2013

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
PyPInervapack0.8.0-3915 days agoknowledge-graphragastcode-searchofflinellmdeveloper-tools

Metrics by category

Vitality

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

75Good · 21% of overall

Development activity

58Moderate
How it's scored
28.8/36Push recency — last push 15 days ago
6.2/36Commit cadence — 9/52 weeks with commits
17.4/18Commit volume — 85 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year85
human_commit_share1
days_since_last_push15
active_weeks_last_year9

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 10 releases published
36/36Release recency — latest release 34 days ago
27/27Release cadence — a release every ~6.5 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count10
latest_release_tagv0.7.6
releases_from_tagsno
days_since_latest_release34
mean_days_between_releases6.5

Community & Adoption

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

33At Risk · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 1 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars1
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

70Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges6
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

61Moderate · 23% of overall

Maintainer resilience (bus factor)

12Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0/22.5Commit distribution — top contributor authored 100% of commits
1.4/13.5Contributor breadth — 1 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1

Issue & PR responsiveness

100Exceptional
How it's scored
0/42Issue resolution — no issues or no data
30/30PR acceptance — 2/2 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_prs2
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d1
prs_decided_30d1
issue_closed_ratio—
closed_unmerged_prs0
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

49Weak
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
4.3/25Owner reach — 3 followers of ramdhavepreetam
24.9/25Track record — 58 public repos, account ~12 yr old
Inputs used
followers3
owner_typeUser
is_verified—
owner_loginramdhavepreetam
public_repos58
account_age_days4,674
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 15 days ago
20/20Version history — 39 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesnervapack
ecosystemspypi
any_deprecatedno
min_days_since_publish15

Engineering Quality

Are baseline engineering and documentation practices in place?

64Moderate · 19% of overall

Engineering practices

60Moderate
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

70Good
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://nervapack.readthedocs.io
0/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics—
has_wikino
homepage—
docs_sitehttps://nervapack.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionno

Security

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

14Critical · 16% of overall

Security posture

1Critical
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestsbenchmarks/requirements.txt, docs/requirements.txt, pyproject.toml
has_codeql_workflowno
has_security_policyno
has_dependabot_configno

Dependency advisories

65Good
How it's scored
7.6/35Direct dependencies free of known advisories — 1 affected: chromadb 1.5.9 (critical 9.8)
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
32.1/40No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 113 days ago
Inputs used
sourceosv
advisories5
affected_packages1
assessed_packages107
unassessed_packages0
affected_by_severitycritical 1
direct_affected_packages1
Matched the pypi:nervapack@0.8.0 runtime dependency closure — what installing the published package pulls in — 107 packages. 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.

63Moderate · 4% of overall

Agent context & guidance

85Excellent
How it's scored
45/45Agent instructions — CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 84 of 85 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.988
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes5,224

Verify loop (build / test / typecheck)

36Weak
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
10/10Demonstrated agent practice — 77 of the last 85 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0.906
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

53Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
53.3/55Manageable file sizes — 2/65 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes468,813
source_files_sampled65
oversized_source_files2

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

1GitHub stars
1contributors
85commits, last 12 months
15days since last push
10releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi download statistics for 'nervapack' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit; 2026/09/09 00:10:47 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

More detail

Direct dependencies 11
RegistryPackageVersion constraintManifest
PyPItyper>=0.9.0pyproject.toml
PyPIrich>=13.0.0pyproject.toml
PyPItree-sitter>=0.22.3pyproject.toml
PyPItree-sitter-python>=0.21.0pyproject.toml
PyPItree-sitter-javascript>=0.21.2pyproject.toml
PyPItree-sitter-typescript>=0.21.2pyproject.toml
PyPInetworkx>=3.1pyproject.toml
PyPIollama>=0.2.0pyproject.toml
PyPIgitpython>=3.1.30pyproject.toml
PyPIchromadb>=0.4.24pyproject.toml
PyPIpyvis>=0.3.2pyproject.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

Dependency advisories 1

Installing pypi:nervapack@0.8.0 pulls in 107 packages, direct and transitive: 1 carry known advisories, of which 1 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
chromadb1.5.9directcritical5—

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

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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.