Primary Recommendations
2
Total Mentions
8
Win Rate
25%
Implementation Rate
100%
How well your documentation and SDK help AI assistants recommend and implement your tool
out of 100
How often AI writes code after recommending
How often selected as primary choice
% of prompt constraints addressed
Fewer gotchas = more AI-friendly
Consistency across assistants
Win Rate Trend
25% → 25%
Mention Volume
Weekly Activity
1 week of data
| Category | Recommended | Compared | Rejected | Total | Win Rate |
|---|---|---|---|---|---|
| ⚡ Edge Compute | 2 | - | - | 6 | 33% |
| unknown | - | - | - | 2 | 0% |
Constraints in prompts where this vendor was mentioned but a competitor was chosen
| Competitor | Wins Over You | Scenarios |
|---|---|---|
| Cloudflare Workers | 3 | Edge Caching and Rate Limiting with Global KV, edge-open-01 |
that `proxy.ts` runs **Node.js only**; for edge routing use `middleware.ts` with a compatible Next.js version. ([vercel.com](https://vercel.com/docs/routing-middleware?utm_source=openai))
this fits your latency goal (<10ms cold start)
Prioritized by estimated impact on AI recommendation ranking • Based on 8 benchmark responses
cloudflare-workers beats you in 3 head-to-head scenarios. Their advantage: addressing global kv store, custom cache keys, programmatic purge.
Only recommended on codex_cli (2×). claude_code and cursor are not recommending you — improve discoverability through documentation, npm package naming, and example code.