Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/neurofoo/agent-skills/redteamnpx skills add neurofoo/agent-skills --skill redteamgit clone --depth 1 https://github.com/neurofoo/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/neurofoo/agent-skills/redteam)<a href="https://agentmods.dev/skills/neurofoo/agent-skills/redteam"><img src="https://agentmods.dev/badge/skills/neurofoo/agent-skills/redteam.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00034 | $0.00685 |
| Opus 5 | $0.00017 | $0.00342 |
| Sonnet 5 | $0.00007 | $0.00137 |
| Haiku 4.5 | $0.00003 | $0.00068 |
Grade A, and why
redteam scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Red Team Analysis
Conduct an adversarial analysis to find weaknesses, vulnerabilities, and failure modes in a plan, system, or strategy.
Instructions
Think like an attacker. Your job is to break this, find the gaps, and expose what could go wrong. Be thorough and creative in your attacks.
Output Format
Target: [What we're attacking] Objective: [What would "breaking it" look like?]
Target Understanding
Summary of the Plan/System [Brief description of what we're analyzing]
Key Assumptions
- [Assumption 1]
- [Assumption 2]
Attack Surface Analysis
Entry Points / Vulnerabilities
| Vector | Description | Severity |
|---|---|---|
| [attack vector] | [how it could be exploited] | Critical/High/Med/Low |
Failure Mode Analysis
Technical/Operational Failures
| Failure Mode | Trigger | Impact |
|---|---|---|
| [what could fail] | [what causes it] | [effect] |
Human Failures
| Failure Mode | Trigger | Impact |
|---|---|---|
| [human error] | [situation] | [consequence] |
Adversary Scenarios
If I wanted this to fail, I would...
Scenario 1: [Attack Name]
- Attack method: [how they'd do it]
- Likelihood of success: [High/Med/Low]
- Impact if successful: [consequences]
Scenario 2: [Attack Name]
- Attack method: [how]
- Likelihood of success: [High/Med/Low]
- Impact if successful: [consequences]
Assumption Attacks
| Assumption | Attack | What If Wrong? |
|---|---|---|
| [assumption] | [challenge to it] | [consequences] |
Blind Spot Analysis
What are we not seeing?
- [Blind spot 1]
- [Blind spot 2]
What are we too optimistic about?
- [Over-optimism 1]
Red Team Findings
Critical Vulnerabilities (Must Address)
| Vulnerability | Risk | Mitigation |
|---|---|---|
| [vulnerability] | [risk level] | [how to fix] |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 127 lines · 34 tokens per session scan A 76d3b6a61bf7
redteam is a skill published in the GitHub repository neurofoo/agent-skills (111 stars, last pushed 7mo ago), licensed MIT. It adds 34 tokens to every session and 685 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…