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 · ★ 76
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is pydantic-ai-todo safe to install? View the security audit →
Todo Toolset for Pydantic AI Task Planning and Tracking for AI Agents Capabilities API — plug-and-play with one line • Subtasks & Dependencies — hierarchical task management • PostgreSQL Storage — persistent multi-tenant tasks • Event System — webhooks and callbacks Todo Toolset for Pydantic AI adds task planning capabilities to any Pydantic AI agent. Your agent can create, track, and complete tasks with full support for subtasks, dependencies, and persistent storage. Full
| Stars | 76 |
| Forks | 18 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 74.134281622839/100 |
| Open Issues | 2 |
| Last Updated | 2026-08-14 |
| Created | 2025-12-23 |
| Platforms | browser, gemini, python |
| Est. Tokens | ~15k |
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pydantic-ai-todo is Task Planning and Tracking toolset for Pydantic AI agents, enabling hierarchical task management with subtasks, PostgreSQL storage for multi-tenancy, and an event system for webhooks and callbacks.. It is categorized as a Agent Tool with 76 GitHub stars.
pydantic-ai-todo is primarily written in Python. It covers topics such as ai, ai-agent-framework, ai-agents.
You can find installation instructions and usage details in the pydantic-ai-todo GitHub repository at github.com/vstorm-co/pydantic-ai-todo. The project has 76 stars and 18 forks, indicating an active community.
pydantic-ai-todo is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to pydantic-ai-todo on Agent Skills Hub include SimplerLLM, airbyte-agent-connectors, mcp-server. 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: