AI-Infra-Guard is an AI security red-teaming platform that scans agents, skills, MCP servers, and AI infrastructure and evaluates LLM jailbreak resistance. It is used to identify security risks and vulnerabilities in AI systems. Catalogue add-ons support its scanning and evaluation workflows.
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 skills add Tencent/AI-Infra-Guard --skill edgeone-skill-scannergit clone --depth 1 https://github.com/Tencent/AI-Infra-GuardWrote 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/tencent/ai-infra-guard/edgeone-skill-scanner)<a href="https://agentmods.dev/skills/tencent/ai-infra-guard/edgeone-skill-scanner"><img src="https://agentmods.dev/badge/skills/tencent/ai-infra-guard/edgeone-skill-scanner/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/skills/tencent/ai-infra-guard/edgeone-skill-scanner"><img src="https://agentmods.dev/badge/skills/tencent/ai-infra-guard/edgeone-skill-scanner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 206 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
- high System Prompt Leakage · line 299 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
- medium Agent Snooping · line 105 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Excessive Agency · line 193 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- low Excessive Agency · line 93 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
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 | $0.00148 | $0.03832 |
| Opus 5 | $0.00074 | $0.01916 |
| Sonnet 5 | $0.00030 | $0.00766 |
| Haiku 4.5 | $0.00015 | $0.00383 |
Grade A, and why
edgeone skill scanner scanned grade A with 1 finding 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 12d 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.
Enumerates other installed skillslowAgent snooping
Other skills' SKILL.md files reveal prompts, capabilities and secrets that should be invisible to peers.
Once the platform is identified, use the platform-specific method below to enumerate all installed skills. Do **NOT** output a list of all discovered skill names and paths before scanning — proceed Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 365 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tencent Zhuque Skill Scanner
Agent Skills security scanner powered by Tencent Zhuque Lab A.I.G. Compatible with any agent platform that supports skills (e.g. OpenClaw, Qclaw, WorkBuddy, CodeBuddy, Cursor, Windsurf, Claude Code, etc.).
Security Declaration
Local-only analysis: this scanner performs static analysis by reading skill files only. No file contents, credentials, or personal data are sent externally.
Language Detection Rule — EXECUTE BEFORE ANYTHING ELSE
Detect the language of the user's triggering message and lock the output language for the entire run. This detection is an internal step only — do NOT output any text that reveals the detection result, such as "当前输出语言为中文", "Detected language: English", or similar meta-statements. Simply use the detected language silently for all subsequent output.
| User message language | Output language |
|---|---|
| Chinese | Chinese — entire output in Chinese |
| English | English — entire output in English |
| Other language | Match that language |
| Cannot determine | Default to Chinese |
All output — scan start prompt, table headers, labels, prose, verdict, and footer — must be written exclusively in the detected language. Do NOT mix languages or announce the language choice at any point.
Scan Start Prompt
Before starting the scan, output the following line with {skill} replaced by the actual skill name.
Translate it to match the detected output language.
🔍 腾讯朱雀实验室 A.I.G Skill Scanner 正在检测 {skill} 的安全性，请稍候...
Scan Workflow
Determine which mode to use based on the user's request:
| User intent | Mode |
|---|---|
| Scan all skills on a platform, or asks "are my skills safe?" without specifying a file | Mode A — Full-platform scan |
| Scan a specific skill file or a named skill | Mode B — Single-skill audit |
Mode A — Full-platform scan
Use this mode when the user wants to check the security of all skills on a given agent platform.
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.
- 12d ago First seen · 365 lines · 148 tokens per session scan A 08ef14a57915
edgeone skill scanner is a skill published in the GitHub repository Tencent/AI-Infra-Guard (6,237 stars, last pushed yesterday), licensed Apache-2.0. It adds 148 tokens to every session and 3,832 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (enumerates other installed skills). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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