SigmaShake vs Value System Kernel

SigmaShake and Value System Kernel are both guardrails & safety tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

SigmaShake

SigmaShake intercepts tool calls from agents running in Claude Code, Cursor, VS Code Copilot, and Gemini CLI, evaluating each action against a rule set before it executes. The vendor states decisions resolve in roughly 85 ms using deterministic native evaluation — no model inference, no GPU, no token spend. Rules follow an Allow/Ask/Deny pattern, where Ask routes the action to a human approval queue rather than blunting everything with a hard block. The desktop app installs in about 30 seconds with no admin rights; the CLI drops into any shell or CI hook chain. Self-hosting is supported, which means the guardrail layer stays offline and never sends your code or commands to a third-party model.

Value System Kernel

The repo describes a blueprint for accelerator-native guardrail logic: input vectors are geometrically verified against pre-loaded danger references using IEEE 754 bit-masking and native FMA intrinsics, with the explicit goal of eliminating branch misprediction and warp divergence that stall GPU pipelines. V1 and V2 architectures are both present, with V2 repositioning the scan space as a multi-dimensional physical memory address structure rather than a semantic parsing layer. The vendor states this is a concept-proof blueprint, not a production-ready drop-in — teams expecting a plug-and-play safety layer will need to adapt the kernel to their inference stack. Community activity is minimal: zero forks, one star at the time of listing.

Attribute	SigmaShake	Value System Kernel
Pricing	Paid	Free
Price	$5/mo	—
Free trial	No	No
Open source	No	Yes
Has API	No	No
Self-hosted option	Yes	Yes
Platforms	Windows 10+, macOS 14+, Linux (Ubuntu 22.04+ / Fedora 38+ / Pop!_OS)	CUDA, C++20
Pros	Deterministic local evaluation at roughly 85 ms per check, so you avoid the latency and per-token cost of routing every agent action through a model-based policy guard. Ask mode holds a risky action in a human approval queue rather than blocking it outright, which means your agent keeps moving on safe tasks while you review the one call that needs a second look. PreToolUse hook integration for Claude Code and MCP server integration for Cursor, Codex, and VS Code Copilot, so the guardrail wires into agents your team is already running without a custom shim. Self-hosted deployment with no model inference, so your code, file paths, and shell commands never leave the machine — critical for teams with data-handling obligations. Per-user install with no admin or UAC rights required, which means individual developers can adopt it without waiting for IT to sign off on an organization-wide rollout.	IEEE 754 bit-masking for injection detection avoids the token-parsing overhead of Python middleware, so guardrail checks do not add a separate model-inference round-trip to your latency budget. FMA intrinsic optimization targets branch misprediction and warp divergence elimination, which means the kernel is designed to keep GPU utilization high during safety checks rather than stalling the pipeline. V1 and V2 architectures are both included with test headers, so researchers can diff the two design approaches and benchmark the trade-offs before committing to either direction. Self-hosted and free with public source available, so there is no vendor dependency or usage-based cost when running experiments on your own CUDA hardware.
Cons	No API is exposed, so teams building custom agent runtimes or embedding safety checks inside their own orchestration code cannot call SigmaShake programmatically — they wrap the CLI binary, which introduces a process boundary and complicates error handling at scale. The SHAKEDOWN benchmark that positions SigmaShake as the top-ranked guardrail was authored by SigmaShake, and competitor scores were modeled from public docs rather than measured runs; teams doing their own evaluation should run independent tests before treating the benchmark as a neutral comparison. Fleet management and team-level policy enforcement are paid-only features, which means a free-tier team cannot centrally audit what rules individual developers are running — a gap that matters the moment more than one engineer is using an AI coding agent on shared infrastructure. Windows support is the primary release target based on page emphasis and download prominence; macOS and Linux builds are listed but community reports on edge cases outside Windows are sparse, so teams running heterogeneous developer environments should validate on non-Windows machines before committing.	The repo is explicitly a blueprint concept, not a production kernel — teams trying to wire it into an existing inference pipeline find no integration documentation, no package distribution, and no API surface, which means any adoption requires writing the glue layer from scratch. No license is stated on the page, so any team operating under legal review for open-source dependencies cannot safely incorporate the code until licensing is clarified — the most direct path at that point is to reference the architecture and reimplement independently. The entire tool assumes CUDA hardware; teams running inference on CPU, Apple Silicon, or non-NVIDIA accelerators have no supported path and no fallback, which is the condition under which they abandon this repo entirely in favor of CPU-compatible guardrail libraries or hosted safety APIs. Community activity is at floor level — zero forks, one star — which means bug reports go unanswered, undocumented edge cases stay undocumented, and teams carrying this into longer research projects are effectively maintaining a fork from day one.

Bottom line

SigmaShake is paid while Value System Kernel is free; Value System Kernel is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between SigmaShake and Value System Kernel?

SigmaShake is Paid, while Value System Kernel is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is SigmaShake better than Value System Kernel?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.