jagmarques/asqav-sdk

0

/ 100

Documentation100
Engineering80
Health100
Python173MIT1d ago
Grade a repo

Polished and well engineered. Punching above its star count.

Python and TypeScript SDKs for verifiable evidence of AI agent actions. Signed receipts, policy enforcement, audit trails. Works with LangChain, CrewAI, MCP.

Documentation

100

README12pt100

README is present.

Install and run instructions9pt100

README documents how to install the project.

License6pt100

Licensed under MIT.

Contributing guide5pt100

Contributing guide is detailed and thorough.

Engineering

80

Linting and formatting5pt0

No linter or formatter config found.

→ Add a linter config such as .eslintrc.json, .prettierrc, ruff.toml, or .golangci.yml to enforce consistent code style.

Tests18pt80

Test files detected (github-action-risk-acceptance/test_risk_acceptance.py).

Reproducibility6pt80

Lockfile present (python/uv.lock). Installs are reproducible.

CI/CD14pt100

CI is configured (.github/workflows/build-verifier-binary.yml).

Issue and PR templates6pt100

Issue or PR templates present.

Project health

100

Dependency manifest6pt100

Dependency manifest found (python/pyproject.toml).

Repository metadata5pt100

Repository has a description.

Activity5pt100

Actively maintained (pushed within the last month).

Housekeeping3pt100

.gitignore present.

Repository health signals

Activity, community, and responsiveness at scan time

Activity

  • —
    Commits (30d / 90d)
  • 20
    Forks
  • 71
    Releaseslatest 2mo ago

Community

  • —
    Community health
  • —
    authors own >50% of commits
  • 173
    Watchers

Responsiveness

  • 4d 22h
    Median issue response
  • <1h
    Median PR merge time
  • 5
    Open issues
Repository files15 root entries
  • .github
    Good: CI is configured (.github/workflows/build-verifier-binary.yml).
    Good: Issue or PR templates present.
  • conformance
  • docs
  • examples
  • github-action
  • github-action-risk-acceptance
    Good: Test files detected (github-action-risk-acceptance/test_risk_acceptance.py).
  • python
    Good: Lockfile present (python/uv.lock). Installs are reproducible.
    Good: Environment pinned via python/src/asqav/templates/shadow-ai/docker-compose.yml.
    Good: Dependency manifest found (python/pyproject.toml).
  • typescript
  • verifier
  • .gitignore
    Good: .gitignore present.
  • CHANGELOG.md
  • CONTRIBUTING.md
    Good: Contributing guide is detailed and thorough.
    Good: Contributing guide includes setup/install instructions.
    Good: Contributing guide describes code style expectations.
    Good: Contributing guide explains how to run tests.
    Good: Contributing guide describes the PR/review workflow.
    Good: Contributing guide includes code examples.
  • LICENSE
    Good: Licensed under MIT.
  • README.md
    Good: README is present.
    Good: README is well structured with multiple sections.
    Good: README includes screenshots or visuals. Great for first impressions.
    Good: README has code examples.
    Good: README links to a live demo or deployed app.
    Good: README includes status badges.
    Good: README documents how to install the project.
    Good: README documents how to run the project.
  • SECURITY.md
    Good: Security policy present.