Primary Recommendations
2
Total Mentions
20
Win Rate
10%
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
10% → 10%
Mention Volume
Weekly Activity
1 week of data
| Category | Recommended | Compared | Rejected | Total | Win Rate |
|---|---|---|---|---|---|
| 🚩 Feature Flags | 2 | - | 2 | 12 | 17% |
| 🔀 Cross-Category | - | 1 | - | 3 | 0% |
| unknown | - | - | - | 5 | 0% |
Constraints in prompts where this vendor was mentioned but a competitor was chosen
| Competitor | Wins Over You | Scenarios |
|---|---|---|
| Statsig | 2 | Migrate from LaunchDarkly to Server-Side Evaluation, ff-targeted-02 |
| Sentry | 1 | err-targeted-02 |
vs. alternatives:
vs. alternatives:
Prioritized by estimated impact on AI recommendation ranking • Based on 20 benchmark responses
You're mentioned in 12 feature flags scenarios but only win 2. Analyze the constraints in losing scenarios for targeted improvements.
You're mentioned in 3 cross-category scenarios but only win 0. Analyze the constraints in losing scenarios for targeted improvements.
Only recommended on claude_code (2×). codex_cli and cursor are not recommending you — improve discoverability through documentation, npm package naming, and example code.
statsig beats you in 2 head-to-head scenarios.
sentry beats you in 1 head-to-head scenario.