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.
适合你，如果你在构建或管理安全分析智能体，需要确保其输出可靠且持续改进。
npx oh-my-skill add boshi-xixixi/traeskill/audit-integritycurl -fsSL https://oh-my-skill.com/install.sh | bash -s -- boshi-xixixi/traeskill/audit-integritynpx oh-my-skill verify boshi-xixixi/traeskill/audit-integrity怎么用
商店整理自技能原文 · 版本 9cf38e6 · 表述以原文为准所有应用安全分析代理在输出结果前，会自动执行一系列质量检查：澄清范围、防止自我合理、强制二次自我批评、处理工具失败、遵守硬规则、自我评分（至少8分），并记录教训用于持续改进。
每次安全分析、代码审查、威胁建模或质量扫描完成后自动触发，作为后分析质量门。
技能原文 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.
| Component | Reference File | Purpose | |-----------|---------------|---------| | Clarification Protocol | [clarification-protocol.md](references/clarification-protocol.md) | Ask ≤2 targeted questions before analysis when scope is ambiguous | | Anti-Rationalization Guard | [anti-rationalization-guard.md](references/anti-rationalization-guard.md) | Table of prohibited rationalizations with mandatory responses | | Self-Critique Loop | [self-critique-loop.md](references/self-critique-loop.md) | Mandatory second-pass review after initial analysis | | Retry Protocol | [retry-protocol.md](references/retry-protocol.md) | Tool failure handling — retry once, then document | | Non-Negotiable Behaviors | [non-negotiable-behaviors.md](references/non-negotiable-behaviors.md) | Hard rules: never fabricate, always cite evidence, report gaps | | Self-Reflection Quality Gate | [self-reflection-quality-gate.md](references/self-reflection-quality-gate.md) | 1–10 scoring rubric with ≥8 threshold per category | | Self-Learning System | [self-learning-system.md](references/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