No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by vstorm-co · Agent Tool · ★ 94
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is pydantic-ai-shields safe to install? View the security audit →
Pydantic AI Shields Guardrail Capabilities for Pydantic AI Agents Cost Tracking • Prompt Injection • PII Detection • Secret Redaction • Tool Permissions • Async Guardrails Pydantic AI Shields provides ready-to-use guardrail capabilities for Pydantic AI agents. Drop them into any agent for cost control, tool permissions, and safety checks — no middleware wrappers needed. Full framework? Check out Pydantic Deep Agents — complete agent framework with planning, filesystem, subagents, and skills. Installat
| Stars | 94 |
| Forks | 11 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 74.2152063699492/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-10 |
| Created | 2025-12-28 |
| Platforms | python |
| Est. Tokens | ~15k |
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pydantic-ai-shields is Guardrail capabilities for Pydantic AI — cost tracking, prompt injection detection, PII filtering, secret redaction, tool permissions, and async guardrails. Built on pydantic-ai's native capabilities . It is categorized as a Agent Tool with 94 GitHub stars.
pydantic-ai-shields is primarily written in Python. It covers topics such as ai-agents, ai-guardrails, ai-safety.
You can find installation instructions and usage details in the pydantic-ai-shields GitHub repository at github.com/vstorm-co/pydantic-ai-shields. The project has 94 stars and 11 forks, indicating an active community.
pydantic-ai-shields is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to pydantic-ai-shields on Agent Skills Hub include SimplerLLM, agentsilex, skene. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: