CAD Skills vs Hacktron: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of CAD Skills and Hacktron — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
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CAD Skills
earthtojake
Open-source library of agent skills for CAD, robotics, fabrication, and simulation — generate STEP/STL, URDF/SRDF/SDF, DXF, and slicer G-code from prompts.
Key features
- Prompt-to-CAD Generation: The CAD skill creates and edits parametric CAD models from natural language or image requests, exporting to STEP, STL, 3MF, and GLB.
- URDF Robot Description: Writes robot structure files with links, joints, limits, inertials, and meshes ready for ROS-based stacks.
- SRDF for MoveIt2: Adds planning groups, end effectors, named poses, and collision rules on top of a URDF for MoveIt2 planning.
- SDF Simulation Worlds: Creates simulator models and worlds with frames, physics, sensors, and lights.
- 2D DXF Drawings: Produces cut-ready DXF profiles, templates, gaskets, and layouts from Python or CAD geometry.
- G-code Slicing: Slices supported mesh files into validated, printer-profiled FDM G-code using real slicer CLIs.
- Bambu Lab Print Jobs: Dry runs, uploads, and cautiously starts local Bambu Lab prints from validated G-code.
- CAD Viewer Previews: Local browser previews for CAD, G-code, URDF, and other robot files for fast agent iteration.
Best for
- Agentic Mechanical Design: Let a coding agent iterate on brackets, flanges, and enclosures directly from natural-language specs.
- Robot Description Authoring: Generate URDF/SRDF/SDF files for new robot arms or mobile bases without hand-writing XML.
- Rapid Prototyping: Take a CAD model to sliced, printer-ready G-code and kick off a Bambu Lab print from within an agent workflow.
- Custom Part Fabrication: Produce DXF/STEP files pre-checked for SendCutSend, then order laser-cut or CNC parts.
- Simulation Setup: Author SDF worlds for physics simulators with the right frames, sensors, and lighting for robotics research.
- Off-the-Shelf Sourcing: Use step.parts to pull ready-made STEP models for common hardware like screws, bearings, and connectors.
Hacktron
Hacktron AI
An AI security engineer that reviews every pull request, traces exploitable vulnerabilities and proves them with a working exploit before code ships.
Key features
- Exploit-Proven PR Review: Reviews every pull and merge request on GitHub, GitLab or Bitbucket and only reports a finding when it can attach a working exploit demonstrating real impact.
- Attacker-Path Taint Tracing: Indexes the codebase and traces tainted input through call paths to determine what an attacker can actually reach, rather than pattern-matching on syntax.
- Fix with AI in the Thread: Delivers a remediation prompt and suggested diff inside the pull request comment so the fix happens where the review already is.
- Security Automations: Set trigger conditions once and Hacktron verifies, fixes and tests every matching finding, then notifies the team in Slack or email.
- Whitebox Pentests: Launches a full-scope assessment that deploys a sandbox, builds a call graph, maps the attack surface and validates exploits, delivering an audit-ready SOC 2 or ISO 27001 report in hours instead of weeks.
- Versioned Project Rules: A .hacktron/rules.md file lives and versions with your code, encoding which paths are high risk and which findings to suppress, cutting false positives without going blind to real bugs.
- Threat Models from Your Documents: Upload architecture notes, security policies or past pentest reports and Hacktron builds and updates a versioned threat model for the application.
- Triage as Training: Every finding you accept, dismiss or downgrade teaches the system that codebase's threat model, so reviews sharpen the longer it stays embedded.
- MCP and REST API Access: Pull findings into Cursor, Claude Code or Codex over MCP to analyse and fix, or build custom workflows on the REST API, plus Jira and Linear ticket creation.
Best for
- Pre-Merge Vulnerability Gating: Catching an IDOR or injection introduced by a pull request before it reaches production, with the exploit attached so nobody debates severity.
- Replacing Annual Pentests: Running continuous whitebox assessments instead of relying on a once-a-year engagement that misses everything shipped in between.
- SOC 2 and ISO 27001 Evidence: Producing an audit-ready penetration test report in hours to satisfy a compliance deadline or a customer security review.
- Cutting Scanner Alert Fatigue: Replacing a noisy SAST queue with findings that come with proof, so the security team spends its time on real issues.
- Scaling a Small Security Team: Giving one or two security engineers coverage across every repository and every developer's pull requests.
- Dependency Supply-Chain Checks: Scanning a lock file for malicious packages before they land in the build.
- Fixing Findings from Your Editor: Pulling confirmed vulnerabilities into Claude Code or Cursor over MCP and remediating them without leaving the IDE.
