audit-integrity

v2026.09.24

Shared audit integrity framework for all AppSec agents — enforces output quality, intellectual honesty, and continuous improvement through anti-rationalization guards, self-critique loops, retry protocols, non-negotiable behaviors, self-reflection quality gates (1-10 scoring, ≥8 threshold), and a self-learning system with lesson/memory governance for security analysis agents.

GitHub
Install command
npx skhub add github/audit-integrity
Markdown
SKILL.md

Audit Integrity Skill

Enforces output quality, intellectual honesty, and continuous improvement across all AppSec agents.

When to Use

  • Every security analysis, code review, threat model, or quality scan agent run
  • Applied automatically as a post-analysis quality gate
  • Applicable to any agent performing SAST, SCA, threat modeling, or code quality analysis

Components

This skill provides 7 reusable capabilities. Agents apply all 7 unless their scope excludes a specific component.

ComponentReference FilePurpose
Clarification Protocolclarification-protocol.mdAsk ≤2 targeted questions before analysis when scope is ambiguous
Anti-Rationalization Guardanti-rationalization-guard.mdTable of prohibited rationalizations with mandatory responses
Self-Critique Loopself-critique-loop.mdMandatory second-pass review after initial analysis
Retry Protocolretry-protocol.mdTool failure handling — retry once, then document
Non-Negotiable Behaviorsnon-negotiable-behaviors.mdHard rules: never fabricate, always cite evidence, report gaps
Self-Reflection Quality Gateself-reflection-quality-gate.md1–10 scoring rubric with ≥8 threshold per category
Self-Learning Systemself-learning-system.mdLesson/Memory templates and governance rules

Execution Flow

  1. Before analysis: Apply Clarification Protocol if scope is ambiguous
  2. During analysis: Apply Anti-Rationalization Guard at every decision point
  3. After initial pass: Execute Self-Critique Loop (mandatory second pass)
  4. On tool failure: Apply Retry Protocol
  5. Before delivery: Run Self-Reflection Quality Gate (all categories must score ≥8)
  6. After delivery: Create Lessons/Memories for novel findings, false positives, or methodology gaps (see Self-Learning System)

Agent-Specific Adaptation

Each agent customizes the Self-Critique Loop checklist and Self-Reflection Quality Gate categories to match its domain. The reference files provide the base templates; agents extend them with domain-specific items.

Example extensions per agent type

  • SAST/SCA agents: Add taint trace completeness and manifest coverage checks
  • SonarQube-style agents: Add rating sanity check (A–E consistency with findings)
  • Threat modeling agents: Add STRIDE category completeness per trust boundary
  • Code review agents: Add trust boundary audit with data flow tracing
Discovery
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Version
Latest version metadata

Version

v2026.09.24

Published

Sep 24, 2026

Category

Uncategorized

License

MIT

Source path

skills/audit-integrity

Default branch

main

Latest commit

1f56440

Tree SHA

04e334f