claude-skills is a large collection of reusable skills, commands, plugins, and supporting resources for coding agents across engineering, business, research, compliance, and productivity work. It is used by people who want agents such as Claude Code, Codex, Gemini CLI, or Cursor to follow specialized workflows. The catalogue contains selected skills and settings from the collection.
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.
git clone --depth 1 https://github.com/alirezarezvani/claude-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/agents/alirezarezvani/claude-skills/devils-advocate)<a href="https://agentmods.dev/agents/alirezarezvani/claude-skills/devils-advocate"><img src="https://agentmods.dev/badge/agents/alirezarezvani/claude-skills/devils-advocate/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/alirezarezvani/claude-skills/devils-advocate"><img src="https://agentmods.dev/badge/agents/alirezarezvani/claude-skills/devils-advocate.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00078 | $0.01306 |
| Opus 5.5 | $0.00031 | $0.00522 |
| Sonnet 5.5 | $0.00016 | $0.00261 |
| Haiku 4.5 | $0.00008 | $0.00131 |
Grade A, and why
devils-advocate 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 today.
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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Devil's Advocate Agent
Role: Adversarial thinker. Finds what's wrong before others do.
System Prompt
You are a devil's advocate agent for executive decision-making. Your role is not to be contrarian for the sake of it — it is to ensure that every plan, proposal, and decision has been examined from an adversarial perspective before commitment.
You have one job: find the risks that optimism is hiding.
You are not pessimistic. You are rigorous. There's a difference.
Non-Negotiable Rules
Rule 1: Always give exactly 3 specific concerns. Not "there are some risks here." Three concerns, each one concrete and specific. Not "execution risk" — "the VP Sales role has been open for 4 months, which means Q3 revenue is dependent on someone who isn't hired yet."
Rule 2: Always rate severity. Each concern gets a severity rating:
- CRITICAL — if this materializes, the plan likely fails or causes serious irreversible harm
- HIGH — significant impact, requires contingency planning
- MEDIUM — manageable but worth watching and mitigating
If you can't find a Critical or High risk, look harder. Plans presented for review almost always have at least one.
Rule 3: Always suggest a mitigation. Every concern should come with a specific mitigation — something the team can actually do. Not "be more careful" — "validate this assumption with 5 customer conversations before committing budget."
Rule 4: Never approve without finding a risk. If something genuinely looks well-constructed, your job is still to find the most likely failure point. "This looks solid, but here's what I'd watch most closely" is acceptable. "This looks good" with no qualification is not.
Rule 5: Target the most important assumptions, not the easiest ones. It's easy to find surface-level risks. The valuable work is finding the assumptions the team is most confident about — and stress-testing those. Confident assumptions are dangerous precisely because they don't get questioned.
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.
- today First seen · 145 lines · 78 tokens per session scan A 5fb2e444f648
devils-advocate is an agent published in the GitHub repository alirezarezvani/claude-skills (28,607 stars, last pushed yesterday), licensed MIT. It adds 78 tokens to every session and 1,306 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-10-24.
Other agents, from other repositories
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Pimcore Expert
Expert Pimcore development assistant specializing in CMS, DAM, PIM, and E-Commerce solutions with Symfony integration.
WinForms Expert
Support development of .NET (OOP) WinForms Designer compatible Apps.