Audit Integrity Skill

SkillAI & models

Adds quality checks to your agent's security audits, forcing honest self-review and retries until findings meet a high bar.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Audit Integrity Skill skill

About this capability

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 se

What this skill tells your AI

The instructions your AI receives, as published by github/awesome-copilot in skills/audit-integrity/SKILL.md and read by ahel’s review.

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

Signals

GitHub stars
39k
Forks
5k
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
audit-integrity
Source
github.com/github/awesome-copilot