Score breakdown0 Version history1 Source
Category Weight Category score Contribution
Security prompt, exec, net, exfil, eval
35%
100
35.0 pts
Supply chain hash, typosquat, maintainer, lockfile
20%
100
20.0 pts
Maintenance staleness, pinning, CI
15%
100
15.0 pts
Transparency SKILL.md, perms, README
15%
100
15.0 pts
Community installs, verify, response
15%
100
15.0 pts
Findings & checks · 0 flagged
Security score 100 · 0 findings
✓ — All security checks passedNo findings in this category for the latest scan. pass
Supply chain score 100 · 0 findings
✓ — All supply chain checks passedNo findings in this category for the latest scan. pass
Maintenance score 100 · 0 findings
✓ — All maintenance checks passedNo findings in this category for the latest scan. pass
Transparency score 100 · 0 findings
✓ — All transparency checks passedNo findings in this category for the latest scan. pass
Community score 100 · 0 findings
✓ — All community checks passedNo findings in this category for the latest scan. pass
Every scanned point with the score it earned and what moved between them.
1 scans · 90 days d97a2e4 latest
Jun 23, 2026 100 d97a2e4
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
library/specializations/ai-agents-conversational/skills/autogen-setup/SKILL.md · 1 file library/specializations/ai-agents-conversational/skills/autogen-setup/SKILL.md 1.2 KB · Markdown Rendered Raw ⧉ Copy
name : autogen-setup
description : Microsoft AutoGen multi-agent configuration for conversational AI systems
allowed-tools :
- Read
- Write
- Edit
- Bash
- Glob
- Grep
AutoGen Setup Skill Capabilities Configure AutoGen agents (AssistantAgent, UserProxyAgent) Set up agent conversations and group chats Implement code execution capabilities Design human-in-the-loop patterns Configure nested agent architectures Implement custom reply functions Target Processes multi-agent-system autonomous-task-planning Implementation Details Agent Types AssistantAgent : LLM-powered assistantUserProxyAgent : Human proxy with code executionGroupChatManager : Multi-agent orchestrationConversableAgent : Base class for custom agentsConfiguration Options LLM configuration (models, temperatures) Code execution settings Human input mode Max consecutive auto-replies Function calling configuration Patterns Two-agent conversations Group chats with selection Nested conversations Teachable agents Best Practices Proper termination conditions Safe code execution sandboxing Clear agent system messages Monitor conversation flow Dependencies