C — Moderate risk signals Graded October 16, 2026Several concerns worth a closer look before you install.Based on public adoption and transparency signals as of October 16, 2026. Our opinion, not a code audit or security guarantee.
AI agent skill · Developer tools, Files & documents
awesome-design-skills
List of 67 awesome DESIGN.md and SKILL.md design skill files for agentic tools like Claude Design, Google Stitch, Codex, Cursor, and other AI tools
Bottom line: Signal-based grade (3/7 points): well starred on GitHub, public source code. This reflects adoption and transparency, not a code audit.
- Popularity score
- 40/100
- Rank
- Not ranked: outside the 500 most popular tools
- GitHub stars
- 3.2k
What it does
Curates 67 design skill files (DESIGN.md and SKILL.md) that document patterns and capabilities for AI agents and agentic tools like Claude, Google Stitch, and Cursor. Serves as a reference library to help teams build consistent, reusable design patterns for AI-assisted workflows.
Who it’s for
Product teams, AI engineers, and builders using Claude Desktop, Cursor, or similar agentic platforms who want to standardize how AI agents handle design tasks. Executives evaluating AI tooling can use this to understand design patterns emerging in the agent ecosystem.
Copy-paste setup
Check these steps against the project’s own instructions before running anything.
This is a curated reference repository rather than an installable package. Verify the exact setup against the repo README at https://github.com/bergside/awesome-design-skills (opens external site). Likely usage: clone the repo and reference the skill files in your agent configuration or documentation pipeline. No npm package is published; integration depends on your specific tool (e.g., Claude Desktop mcpServers config or similar).
Risks
- Prompt injection via skill definitions: Malicious or poorly-reviewed skill files could inject harmful instructions into agent behavior.
- Supply-chain trust: Repository quality depends on community contributions; no apparent review gates mean skills of varying security maturity may be included.
- Data leakage in agent outputs: Design skills that touch customer data or internal APIs could inadvertently expose sensitive context if not carefully scoped.
- Third-party tool coupling: Skills are tailored to external tools (Claude, Cursor, Google Stitch); changes to those tools could break skill implementations.
- Credential scope creep: Agents using these skills may inherit overly-broad permissions if skills assume wide access to design systems or APIs.
How to stay secure
Least-privilege permissions
- Grant each AI agent access only to the specific design files and tools it needs for its assigned task, not blanket access to all 67 skill files
- Require agents to authenticate separately for each external service (Claude, Cursor, Google Stitch) rather than sharing one master credential across all tools
- Regularly audit and revoke permissions for skills that are no longer in active use, treating them like outdated employee access badges
Network isolation
- Route agent requests through a controlled gateway that logs and validates all skill executions before they connect to external design tools
- Restrict skill files from directly accessing internal company databases, customer records, or sensitive design repositories—require explicit approval workflows for elevated access
- Use separate, sandboxed environments (isolated copies of systems) when testing new or community-contributed skills before deploying them to production
Monitoring
- Enable logging of all skill activations and outputs to detect when an agent unexpectedly returns customer data, API keys, or confidential design information
- Set up alerts that trigger whenever a skill attempts to access resources outside its declared purpose (for example, a design skill suddenly querying employee records)
- Review community contribution history and security reports for each skill file quarterly, flagging any authored by inactive or untrusted contributors
Red flags to watch for
- Skills with vague or overly broad descriptions that don't clearly explain what data they access or what the agent will do with it
- Design skill files that request permissions to multiple unrelated services or APIs (for example, a design tool that also asks for payment system access)
- Skills that generate prompts or instructions dynamically at runtime rather than using fixed, reviewed templates—this is a common injection attack vector
- Absence of version history or recent maintenance on community-contributed skills, indicating they may contain unpatched vulnerabilities
Alternatives
- Anthropic's official prompt library – documented, first-party agent patterns curated by Claude creators.
- OpenAI Cookbook – community examples and best practices for agentic workflows with GPT models.
- LangChain Agent Templates – maintained templates and tool integrations for building agentic applications.
- Hugging Face Agent Hub – community-driven agent skill registry with versioning and metadata.