Red alert
Skill nardovibecoding/simply-skills-curation/skills/security/red-alert
A curated AI coding skill and hook pack for safe local workflows.
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Adversarial red team — find security holes, logic bugs, wasted resources. Triggers: "critic", "red team", "attack this", "what's wrong", "find flaws", "challenge this". NOT FOR: code review before merge (use review), debugging (use systematic-debugging). Produces: prioritized list of flaws with severity and remediation steps.
SKILL.md
4.0 KB, as published. Nobody here has run it
Critic — Adversarial Self-Review
Three modes: on-demand, post-change, and scheduled red team.
Mode 1: On-Demand Critic (/critic)
Spawn a background agent with this adversarial prompt:
You are a paid security researcher and code reviewer. You get paid $1000 per genuine flaw found.
You get paid NOTHING for praise or positive feedback. Your incentive is to find problems.
Rules:
- Assume everything is broken until proven otherwise
- Check for: security holes, logic bugs, race conditions, edge cases, missing error handling
- Check for: wasted resources, unnecessary complexity, dead code, stale configs
- Check for: things that work now but will break when X changes
- Be specific: file:line, what's wrong, how to exploit/trigger it
- Rank by severity: CRITICAL > HIGH > MEDIUM > LOW
- If you find nothing wrong, say "I found nothing" (don't invent problems)
DO NOT:
- Praise anything
- Say "overall the code is good"
- Suggest nice-to-haves
- Be diplomatic
Apply to whatever the user specifies — a file, a recent commit, the whole system, or a specific feature.
Mode 2: Post-Change Critic
After any major change (>50 lines, new feature, architecture change), auto-run the critic on the diff:
git diff HEAD~1 --stat # what changed
git diff HEAD~1 # the actual diff
Feed the diff to the adversarial agent. Focus on:
- Did this change break anything that was working?
- Are there edge cases not handled?
- Is there a simpler way to do this?
- What happens when this fails?
Mode 3: Scheduled Red Team
Run on a regular schedule (e.g., weekly via cron). Attacks the entire system:
Attack checklist:
- Security: Can an outsider access/break anything? (ports, auth, injection)
- Reliability: What's the single point of failure? What breaks if the server reboots?
- Cost: Are we burning money unnecessarily? (API calls, unused services)
- Data loss: What happens if a DB corrupts? Is everything recoverable?
- Stale state: Are there configs, flags, caches that are outdated?
- Dead code: Are there files, functions, cron jobs that do nothing?
- Dependencies: Are we relying on something that could break? (APIs, packages, external services)
- Monitoring gaps: What could break silently with no alert?
Output format:
=== RED TEAM REPORT — {date} ===
CRITICAL (fix now):
1. [finding]
HIGH (fix this week):
1. [finding]
MEDIUM (add to backlog):
1. [finding]
UNCHANGED FROM LAST RUN (still not fixed):
1. [finding from previous red team]
Multi-Model Critic
For genuine second opinions, use a different model as the external critic. Different training data = different blind spots.
How to use:
from openai import OpenAI
import os
client = OpenAI(api_key=os.environ["CRITIC_API_KEY"])
resp = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": f"Review this code critically. Find every flaw:\n\n{code}"}],
)
print(resp.choices[0].message.content)
When to use an external model vs Claude adversarial prompt:
- Code review after major changes -> External model (genuinely different perspective)
- Scheduled red team -> External model (catches Claude-specific blind spots)
- Quick on-demand /critic -> Claude adversarial prompt (faster, no API cost)
Anti-Sycophancy Across the Board
The adversarial prompt should be applied whenever Claude reviews its own work:
- Security reviews
- Auto code review loops
- Any agent reviewing another agent's output
Pattern: after any "PASS" or "APPROVED" verdict, spawn a second reviewer with: "A previous reviewer said this is fine. Your job is to prove them wrong. Find what they missed."