mcpbeat

Audit Integrity

github/audit-integrity

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.

4k tokens
context cost
the whole folder, loaded on every use
8
files
instructions only
0
copies elsewhere
how many repositories repackaged it
37394
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/github/awesome-copilot --skill audit-integrity

What comes with it

14 404 bytes besides the instruction
references/anti-rationalization-guard.md
references/clarification-protocol.md
references/non-negotiable-behaviors.md
references/retry-protocol.md
references/self-critique-loop.md
references/self-learning-system.md
references/self-reflection-quality-gate.md

The instruction itself

6 sections, as written by the author

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

How to use it

Copy the folder

Take github/audit-integrity from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.