Audit integrity
Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot.
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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.
SKILL.md
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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.
| Component | Reference File | Purpose |
|---|---|---|
| Clarification Protocol | clarification-protocol.md | Ask ≤2 targeted questions before analysis when scope is ambiguous |
| Anti-Rationalization Guard | anti-rationalization-guard.md | Table of prohibited rationalizations with mandatory responses |
| Self-Critique Loop | self-critique-loop.md | Mandatory second-pass review after initial analysis |
| Retry Protocol | retry-protocol.md | Tool failure handling — retry once, then document |
| Non-Negotiable Behaviors | non-negotiable-behaviors.md | Hard rules: never fabricate, always cite evidence, report gaps |
| Self-Reflection Quality Gate | self-reflection-quality-gate.md | 1–10 scoring rubric with ≥8 threshold per category |
| Self-Learning System | self-learning-system.md | Lesson/Memory templates and governance rules |
Execution Flow
- Before analysis: Apply Clarification Protocol if scope is ambiguous
- During analysis: Apply Anti-Rationalization Guard at every decision point
- After initial pass: Execute Self-Critique Loop (mandatory second pass)
- On tool failure: Apply Retry Protocol
- Before delivery: Run Self-Reflection Quality Gate (all categories must score ≥8)
- 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