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Absolutely makes sense. Alongside our MCP, skill, public API, .md files for all pages, llms.txt and https://fless.io/ai-agents https://fless.io/ai-agents info
by flessio 11d ago
Absolutely makes sense.
Alongside our MCP, skill, public API, .md files for all pages, llms.txt and https://fless.io/ai-agents https://fless.io/ai-agents info page we also wired up detailed analytics at every stage and for every request isolated by channel, both human and AI agent.
We track all agent calls at a pretty granular level to understand the agent funnel, by channel and provider (ex. Perplexity User, OpenAI User etc..).
We can't see what the agent did after calling us but we can see a funnel clearly which is useful to see where engagement and drop-off are.
Our first goal is for users to start a new apartment search - moving from 'landing page' - one of the surfaces mentioned above - to search created (ie. we're hunting for apartments on their behalf).
This has been helpful to understand agent behavior and where we need to improve skill / MCP etc..
- sohaibtariq 11d agoThanks for sharing! In your case, since the skill terminates in an MCP/API call, you have a closed feedback loop. I was wondering about skills that don't have that feedback loop, where the output the agent produced doesn't touch an external server. For instance, the frontend-design skill from Anthropic. How would someone get insights into the user's experience of using that kind of skill?