From Napkin
Enforces output quality and intellectual honesty for AppSec agents via self-critique, quality gates, and anti-rationalization guards. Use for any security analysis or code review.
How this skill is triggered — by the user, by Claude, or both
Slash command
/napkin:audit-integrityThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Enforces output quality, intellectual honesty, and continuous improvement across all AppSec agents.
Enforces output quality, intellectual honesty, and continuous improvement across all AppSec agents.
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 |
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.
npx claudepluginhub ani1797/forge --plugin copilot-sdk3plugins reuse this skill
First indexed Jun 6, 2026
Enforces output quality and intellectual honesty for AppSec agents via self-critique, quality gates, and anti-rationalization guards. Use for any security analysis or code review.
Deep security audit of the agent setup. Runs all deterministic security rules (prompt injection, credential access, data exfiltration, obfuscation, reverse shells, AST behavioral analysis, taint tracking, MCP permission analysis, tool poisoning, YARA signatures, CVE lookups) plus LLM-based semantic security review. Use when the user asks about security, safety, wants to audit their setup, or needs a pre-deployment security check.
Scans AI agent codebases against OWASP Agentic Security Initiative Top 10 risks and generates a compliance report.