NVIDIA / NVIDIA/SkillSpector

Add pre-commit hook support and GitHub Actions CI workflow

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#72 2 comments 2 reactions 0 assignees View on GitHub

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Dominant language
Python
Stars
17.9k
Forks
1.5k
Avg merge
5d 10h
Merged PRs (30d)
66

Description

Summary

SkillSpector currently has no pre-commit hook definition or GitHub Actions workflow,
making it harder for downstream projects to integrate scanning into their CI pipelines.

Motivation

Many security tools (ruff, semgrep, trivy) ship a .pre-commit-hooks.yaml so
developers can add them to pre-commit with a single config block. SkillSpector's
SARIF output is already CI/CD-ready, but there is no example of how to wire it up.

Proposed solution

  1. .pre-commit-hooks.yaml — defines a skillspector hook that runs
    skillspector scan. --no-llm (no API key required). Downstream projects
    pin to a release tag and get automatic skill scanning before every commit.

  2. .github/workflows/skillspector.yml — a GitHub Actions workflow that
    scans on push/PR and uploads SARIF results to GitHub Code Scanning so
    Findings appear inline on the PR diff.

  3. GitHub community templates — PR template and issue templates so
    contributors follow a consistent format.

  4. README update — new "CI/CD Integration" section with copy-paste
    Examples for both integrations.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the proposed files .pre-commit-hooks.yaml and .github/workflows/skillspector.yml, then review the existing skillspector scan . --no-llm command and SARIF output behavior. Add the hook, push/PR workflow, GitHub community templates, and README CI/CD Integration examples, and verify that the documented integrations match the repository's commands and outputs.

Written by the indexing model from the issue text.

Assessment

Tech stack
github-actions, python
Domain
ci-cd, devops, documentation
Issue type
Feature
Difficulty
3/5
Estimated time
1-2 days
Activity status
Active
Clarity
Clearly specified
Newbie friendliness
72/100

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