[unCited]
ProductCitation IndexAI InfluenceBlogBook
[unCited]/AutoGen
ProductCitation IndexAI InfluenceBlogBook
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AEO Score

86

Authoritative Source

Avg Prompt Score

71

across 274 prompts

AI Share of Voice

71%

across 274 prompts

Critical Issues

7

critical + high

Shortlist Position

69/80

Leader · Agent Frameworks Discovery

Per-stage performance

🔍Discovery
160 category
Cited89%143/160
Share of voice66%avg
Engine consensus58%of engines
Competitors23.9avg/cited
Sentiment—no data
⚖️Evaluation
4 brand-level
Cited100%4/4
Share of voice100%avg
Engine consensus100%of engines
Competitors5.0avg/cited
Sentiment—no data
🛡️Trust
4 brand-level
Cited100%4/4
Share of voice100%avg
Engine consensus100%of engines
Competitors5.0avg/cited
Sentiment—no data
💰Conversion
4 brand-level
Cited100%4/4
Share of voice100%avg
Engine consensus100%of engines
Competitors5.0avg/cited
Sentiment—no data

Cited rate · share of voice · engine consensus · sentiment, broken out by buyer-journey stage. Sentiment is the net positive−negative skew across engines that cited the brand at this stage.

Categories AutoGen is visible in

1
  • Agent Frameworks2 of 55→

Your visibility gap

AutoGen surfaces in 69/80 Agent Frameworks discovery prompts. Claim this profile to see which 11 prompts you're missing and how to win them.

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Executive summary

microsoft.github.io is strongly cited for agent-framework discovery queries (e.g., customer experience/marketing/QA/testing and system integration) because it hosts first-party, developer-facing agent framework documentation. The biggest citation risk is evaluation-stage “what do [role] actually use” and conversion-stage “pricing/plans” style queries—these require crawlable, role-specific evaluation content and structured product/pricing surfaces that this domain does not consistently provide.

Based on audit of microsoft.github.io · Jun 12, 2026

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