| name | featbit-evaluation-insights-api |
| description | Expert guidance for using FeatBit's Flag Evaluation REST API and Track Insights REST API to build custom SDKs for platforms without an official FeatBit SDK. Use when user asks about "evaluation API", "flag evaluation endpoint", "evaluate feature flags via HTTP", "track insights", "insight tracking API", "build custom SDK", "Kotlin SDK", "Android SDK", "iOS SDK", "Swift SDK", "Unity SDK", "embedded SDK", "mobile feature flags", "sendToExperiment", or needs to call FeatBit evaluation server directly. Do not use for management API operations (projects, environments, flag CRUD) — use featbit-rest-api for those. Do not use when an official SDK exists for the target language. |
| license | MIT |
| metadata | {"author":"FeatBit","version":"1.0.0","category":"api-reference"} |
FeatBit Flag Evaluation & Insights API
Direct HTTP access to FeatBit's evaluation server — the foundation for building custom SDKs on any platform (Kotlin, Swift, Android, iOS, Unity, embedded, etc.).
Official documentation:
When to Use This Skill
Activate when users:
- Build custom FeatBit SDK for Android, iOS/Swift, Kotlin, Unity, or any platform without an official SDK
- Call the evaluation server directly via HTTP without using a client library
- Need to implement flag evaluation + A/B experiment tracking from scratch
- Ask about
sendToExperiment, variation insights, custom metric events, or batch insight payloads
Prerequisites
Before writing any code:
- Evaluation server URL —
{evaluation-server-url} (e.g., https://eval.your-featbit.com). Found in your FeatBit dashboard under environment settings.
- Environment secret key — client-side or server-side key. Include in every request header:
Authorization: your-environment-secret-key
See How to get the environment secret
Core Workflow
This is the recommended pattern for a custom mobile/frontend SDK:
Step 1 ─ App launch → Evaluate ALL flags (or filtered by tags/keys)
Step 2 ─ Store locally → Cache results in memory for fast synchronous reads
Step 3 ─ Track insights → Fire-and-forget: send evaluation records to FeatBit
Step 4 ─ Poll for updates → Repeat Step 1 periodically using `filter.timestamp`
Step 5 ─ Track metrics → Send custom events (conversion, click, purchase) as they occur
Step 1: Evaluate Feature Flags
POST {evaluation-server-url}/api/public/featureflag/evaluate
Authorization: your-environment-secret-key
Content-Type: application/json
Minimal request body:
{
"user": {
"keyId": "user-123",
"name": "John Doe",
"customizedProperties": [
{ "name": "country", "value": "US" },
{ "name": "plan", "value": "premium" }
]
}
}
Response — array of flag evaluation results:
[
{
"key": "new-checkout-flow",
"variation": {
"id": "08aceef3-5513-4b38-80ad-4b27bebe8871",
"type": "boolean",
"value": "true",
"matchReason": "premium user rule",
"sendToExperiment": true
}
}
]
Key fields:
variation.value — always a string, cast to the needed type ("true" → boolean, "104857600" → number)
variation.sendToExperiment — save this; pass it unchanged when tracking insights
variation.matchReason — "flag disabled" | "targeted" | "{rule name}" | "default"
Narrow the response with filters (essential for reducing payload on mobile):
{
"user": { "keyId": "user-123" },
"filter": {
"keys": ["checkout-flow", "theme-color"],
"tags": ["mobile"],
"tagFilterMode": "and",
"timestamp": 1704067200000
}
}
filter.timestamp — Unix ms. Returns only flags modified after this timestamp. Pass the timestamp from the previous call to implement efficient polling.
Read references/flag-evaluation-api.md for the complete schema, all filter options, and error responses.
Step 2: Cache Locally
Store the response array in memory keyed by flag.key. Serve flag values synchronously from cache — never block UI on a network call.
Step 3: Track Flag Evaluation Insights (fire-and-forget)
After evaluating flags, send evaluation records asynchronously.
POST {evaluation-server-url}/api/public/insight/track
Authorization: your-environment-secret-key
Content-Type: application/json
Request body — array of insight objects:
[
{
"user": {
"keyId": "user-123",
"name": "John Doe",
"customizedProperties": [
{ "name": "plan", "value": "premium" }
]
},
"variations": [
{
"featureFlagKey": "new-checkout-flow",
"variation": {
"id": "08aceef3-5513-4b38-80ad-4b27bebe8871",
"value": "true"
},
"sendToExperiment": true,
"timestamp": 1704067200000
}
],
"metrics": []
}
]
Response: 200 OK with empty body on success. Do not await this in the main UI thread.
Critical:
- Copy
variation.id, variation.value, and sendToExperiment exactly from the evaluation response. Do not derive or guess these values.
- At least one of
variations or metrics must be non-empty in each insight object. A payload where both are empty arrays is a no-op.
Step 4: Poll for Flag Updates
On a background timer, re-evaluate using filter.timestamp set to the time of the last successful poll. Only changed flags are returned — update your cache with the diff.
Step 5: Track Custom Metric Events
When a user performs a meaningful action (purchase, conversion, click):
[
{
"user": { "keyId": "user-123" },
"variations": [],
"metrics": [
{
"route": "/checkout/complete",
"type": "CustomEvent",
"eventName": "purchase-completed",
"numericValue": 99.99,
"appType": "Mobile",
"timestamp": 1704067350000
}
]
}
]
appType — use "Mobile" for Android/iOS apps, "Web" for browser-based apps.
Read references/track-insights-api.md for the complete schema, batch examples, and best practices.
Decision Map
| Scenario | Action |
|---|
| Evaluate all flags on launch | POST evaluate with user, no filter |
| Evaluate only mobile-tagged flags | POST evaluate with filter.tags: ["mobile"] |
| Evaluate one specific flag | POST evaluate with filter.keys: ["flag-key"] |
| Detect flag changes since last poll | POST evaluate with filter.timestamp: {lastPollMs} |
| Record which variation user saw | POST track with variations array |
| Record A/B test conversion | POST track with metrics array |
| Record both at once | POST track with both variations and metrics in one payload |
Mobile SDK Implementation Checklist
Copy and track progress:
Reference Files
| File | Read when |
|---|
references/flag-evaluation-api.md | User asks about exact request/response schema, filter parameters, error codes, or single-flag evaluation |
references/track-insights-api.md | User asks about insights schema, batching multiple users, MetricInsight fields, or best practices |