duriantaco/skylos
by Various
Open source local-first PR scanner that finds dead code, security bugs, secrets, quality regressions, and AI-code mistakes before merge. For first timers refer to https://duriantac
MCP
duriantaco/skylos
Added 1 June 2026
Overview
Open source PR scanner that runs locally to detect dead code, security bugs, secrets, quality regressions, and errors in AI-generated code before merge. Written in Python and designed to be triggered on pull requests, it provides an offline, privacy-preserving alternative to cloud-based scanning tools.
Best for
Best for
Teams wanting a self-hosted, privacy-focused pre-merge check that catches security and quality issues in pull requests
Use cases
- Catching security vulnerabilities and leaked secrets in pull requests before deployment
- Identifying dead code and quality regressions during code review
- Detecting mistakes in AI-generated code commits
Notes
Open source PR scanner that runs locally to detect dead code, security bugs, secrets, quality regressions, and errors in AI-generated code before merge. Written in Python and designed to be triggered on pull requests, it provides an offline, privacy-preserving alternative to cloud-based scanning tools.
446 stars on GitHub. Last updated 2026-05-30. Licensed Apache-2.0.
Use cases
- Catching security vulnerabilities and leaked secrets in pull requests before deployment
- Identifying dead code and quality regressions during code review
- Detecting mistakes in AI-generated code commits
Pros
- Local-first design keeps code and scan results private without external data transfer
- Addresses multiple issue categories in a single scan (security, quality, AI code errors)
- Free and open source with no licensing costs
Cons
- Requires Python runtime and manual setup on the developer’s machine or CI runner
- Smaller community and fewer integrations compared to established commercial scanners
- May need tuning to avoid false positives or cover project-specific rules
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Local-first design keeps code and scan results private without external data transfer
- Addresses multiple issue categories in a single scan (security, quality, AI code errors)
- Free and open source with no licensing costs
Cons
- Requires Python runtime and manual setup on the developer's machine or CI runner
- Smaller community and fewer integrations compared to established commercial scanners
- May need tuning to avoid false positives or cover project-specific rules
Pairs with
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