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skylos
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skylos

Active·★ 475·NOASSERTION·Updated 2026-07-18
★ Security & Safety★ Dev Tooling

Skylos is a privacy-first, hybrid static analysis tool designed for Python, TypeScript, and Go. It excels at detecting dead code, critical security vulnerabilities like SQL injection and hardcoded secrets, and various code quality issues, bridging traditional static analysis with advanced AI agent capabilities.

skylos is currently grouped under RAG / Knowledge Base, which makes it easier to evaluate through workflow fit instead of isolated features alone. Based on the available data, it leans most heavily toward Hybrid Static Analysis with AI Agents: Combines traditional static analysis with optional local/cloud LLMs to eliminate false positives and find deep logic bugs. and Automating Code Quality in CI/CD: Integrate Skylos into GitHub Actions to automatically detect dead code, security vulnerabilities, and quality issues on every Pull Request, failing builds on critical findings.. The listed license is NOASSERTION, which is useful when adoption constraints matter. It also shows measurable community traction with 475 GitHub stars.

#Static Analysis#SAST#Dead Code Detection#AI Agent#Python Security#Code Quality#CI/CD#Multi-language
$ Install
$ pip install skylos
↗ Visit site★ GitHub
01

Features

01Hybrid Static Analysis with AI Agents: Combines traditional static analysis with optional local/cloud LLMs to eliminate false positives and find deep logic bugs.
02Comprehensive Code Auditing: Detects dead code, security vulnerabilities (SAST including SQLi, SSRF, secrets), and code quality issues (complexity, nesting) across multiple languages.
03Automated Remediation & CI/CD Integration: Offers automated fixes and end-to-end remediation via AI agents, and seamlessly integrates into CI/CD pipelines for PR guarding, annotations, and quality gates.
04Multi-Language Support & Privacy-First: Supports Python, TypeScript, and Go with 100% local analysis options, ensuring code privacy.
02

Why choose it

+Hybrid Static Analysis with AI Agents: Combines traditional static analysis with optional local/cloud LLMs to eliminate false positives and find deep logic bugs.
+Automating Code Quality in CI/CD: Integrate Skylos into GitHub Actions to automatically detect dead code, security vulnerabilities, and quality issues on every Pull Request, failing builds on critical findings.
+Covers 7 supported environments or platforms, which is helpful for broader deployment needs.
+Ships with a public repository and a NOASSERTION license, which makes adoption and review easier.
03

Trade-offs

!There are at least 8 related tools in the same category, so the best choice is easier to make after side-by-side comparison.
04

Compatibility

Python
Language
Verified via docs
TypeScript
Language
Verified via docs
Go
Language
Verified via docs
GitHub Actions
CI/CD
Verified via docs
VS Code
IDE Extension
Verified via docs
Ollama
Local LLM
Verified via docs
05

Quick start

1
$ pip install skylos
06

Use cases

↳Automating Code Quality in CI/CD: Integrate Skylos into GitHub Actions to automatically detect dead code, security vulnerabilities, and quality issues on every Pull Request, failing builds on critical findings.
↳Deep Security Auditing of Python, TypeScript, and Go Applications: Perform comprehensive SAST, including taint analysis, secrets detection, and vulnerability checks, across multi-language repositories.
↳Intelligent Dead Code Elimination and Codebase Optimization: Accurately identify and safely remove unreachable functions, classes, and unused imports, leveraging hybrid analysis to distinguish true dead code from framework magic.
↳AI-Assisted Code Remediation and PR Review: Utilize AI agents for context-aware audits, automated fixes, and end-to-end remediation, including generating and validating fixes, and posting inline PR review comments.
07

How it compares

≈skylos sits in the RAG / Knowledge Base category, so it makes more sense to evaluate it alongside tools like mindsdb instead of in isolation.
≈If your main need is closer to "Automating Code Quality in CI/CD: Integrate Skylos into GitHub Actions to automatically detect dead code, security vulnerabilities, and quality issues on every Pull Request, failing builds on critical findings.", that use case is a better lens for comparison than broad feature checklists alone.
≈skylos uses a NOASSERTION license, and community traction are both easier to judge in category context.
08

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Related searches

skylos AlternativesBest RAG / Knowledge Base Tools 2026Open Source RAG / Knowledge Baseskylos Tutorialskylos Vs CompetitorsStatic AnalysisSASTDead Code Detection

Comments

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  • ?
    usr_seed_0501May 6, 2026

    The SAST approach catches security issues alongside code quality problems in one pass

  • ?
    usr_seed_0070Apr 20, 2026

    Used in CI pipelines for automated code hygiene, accuracy is high with low false positives

  • ?
    usr_seed_0344Apr 3, 2026

    High-precision Python dead code detection with secret scanning is a useful combination

  • ?
    usr_seed_0226Feb 26, 2026

    The dead code removal capability reduced our codebase size by 15% on first run

On this page
01Features02Why choose it03Trade-offs04Compatibility05Quick start06Use cases07How it compares08Alternatives
Stats
GitHub Stars★ 475
Last commit2d ago
StatusActive
LicenseNOASSERTION
CategoryRAG / Knowledge Base
Trend (30d)
+19↑ 0.5%
Links
Documentation↗Discussion↗Issues↗Releases↗

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