trust-layer

Verify AI-generated code and files via adversarial multi-agent checks.

Updated Mar 1, 2026
One-click install
npx skills add https://github.com/dnhess/spectra --skill trust-layer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: trust-layer
Source: https://github.com/dnhess/spectra/tree/main/trust-layer
Command: npx skills add https://github.com/dnhess/spectra --skill trust-layer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Trust Layer provides a structured adversarial verification workflow to validate AI-generated code, diffs, and Spectra session artifacts before acceptance, reducing hallucinations, misalignment, and insecure outputs.

Core Features & Use Cases

  • Multi-agent scrutiny: four personas (package-validator, intent-auditor, security-challenger, coherence-checker) critique outputs from multiple angles.
  • Lifecycle-enabled verification: context briefing, opening round, optional discussion rounds, and synthesis with a final trust verdict.
  • Spectra session integration: tracks inputs, artifacts, and results, ensuring verifiable provenance and traceability.

Quick Start

Spawn the trust-layer panel for a given artifact and follow the prompts to generate agent findings and a final trust verdict.

Frequently Asked Questions about trust-layer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I verify AI-generated code before merging it?▼

Adversarial verification checks AI-generated code across package integrity, intent alignment, security, and coherence using multiple agent roles to produce a final trust verdict before acceptance.

What is adversarial verification for AI outputs?▼

Adversarial verification is a structured workflow where multiple agent personas critique AI-generated outputs from different angles, computing a trust score and guardrails to reduce hallucinations and insecure code.

How do I audit AI session artifacts for security and coherence?▼

You can audit AI session artifacts by applying four adversarial roles—package-validator, intent-auditor, security-challenger, and coherence-checker—followed by a moderator synthesizing per-agent findings into a final trust score.

Can I run a security audit on AI-generated diffs without external dependencies?▼

Yes, the security audit runs without external dependencies by using internal agent roles to challenge the diff's package integrity, intent alignment, and security posture, yielding a final verdict and guardrails.

What is the best way to check AI code alignment with original intent?▼

The best way to check intent alignment is running an adversarial verification process that includes an intent-auditor role, which critiques the AI output alongside security and coherence checks to produce a unified trust score.

When should I use multi-agent verification for AI-generated files?▼

Use multi-agent verification when accepting AI-generated code, diffs, or session artifacts into production, as it reduces hallucinations and misalignment by scrutinizing outputs through package, intent, security, and coherence lenses.