Radical Transparency: We're Publishing Our API's Real Hit Rate (11% and growing)

The Uncomfortable Truth About AI Agent Data

When an AI agent tells you "the best price for Jetson Nano is $249", how do you know it's telling the truth? How does the agent know?

It doesn't. It guesses. It trusts the API it called.

I run

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Anyone – human or agent – can check our real performance at any time.

Here's Our Real Data (No Filtering)

*"Yes, our current hit rate is only 11% and the sample is insufficient. We're publishing this to hold ourselves accountable."*

What this honest data tells you:

• We are in the building phase – only 9 signals in 7 days


• Early overall hit rate: 11%
  


• 
  /api/v1/search is leading at 25%
  


• We don't have enough data to make firm claims yet

But Here's Where It Gets Interesting

While our measured traffic is still small, our system is configured to cover specific categories well.

The Road Ahead

Phase 1 (now – done): data_status, trust_*, public data quality endpoint

Phase 2 (this month – in progress): MCP tools with trust signals, category breakdown from real traffic

Phase 3 (next): Per-category hit rates, historical freshness charts, agent-facing dashboard

Phase 4 (future): Agent data exchange – where agents can buy/sell data with trust scores

But none of this matters without real usage.

Call to Action

If you're building agents that shop, compare prices, or make purchase decisions:

• 👏 Leave a like/favorite – helps more builders see this


• 💬 Comment – what trust signals would you want?


• 🔁 Share – tag @devcommunity and @AgentShare


• 🚀 Use the API – help us turn insufficient_sample into high_confidence
  

Let's build the most trustworthy data layer for AI agents. Together.

Tags

#aio #aiagents #mcp #priceapi #transparency #radicaltransparency #buildinginpublic #agentshare #devto