pkg(tools): Expose raw search results in MemoryPromptData for prompt templates (#787)

Expose raw search results in `MemoryPromptData` so prompt templates can traverse, filter, and selectively include results based on metadata (e.g. score, source).

##### Usage example

```typescript
const promptTemplate = (data: MemoryPromptData) => {
  const relevant = data.searchResults.filter(
    (r) => (r.metadata?.score as number) > 0.7
  )
  return `${data.userMemories}\n${relevant.map(r => r.memory).join('\n')}`
}
```

apps/docs/ai-sdk/user-profiles.mdx

@@ -154,6 +154,7 @@ The `MemoryPromptData` object passed to your template function provides:
 
 - `userMemories`: Pre-formatted markdown combining static profile facts (name, preferences, goals) and dynamic context (current projects, recent interests)
 - `generalSearchMemories`: Pre-formatted search results based on semantic similarity to the current query (empty string if mode is "profile")
+- `searchResults`: Raw search results array (`Array<{ memory: string; metadata?: Record<string, unknown> }>`) for traversing, filtering, or selectively including results based on metadata
 
 ### XML-Based Prompting for Claude
 
@@ -179,6 +180,31 @@ const model = withSupermemory(anthropic("claude-3-sonnet"), "user-123", {
 })
 ```
 
+### Filtering Search Results
+
+Use `searchResults` to traverse the raw data and pick what's important:
+
+```typescript
+const selectivePrompt = (data: MemoryPromptData) => {
+  const relevant = data.searchResults.filter(
+    (r) => (r.metadata?.score as number) > 0.7
+  )
+  return `
+<user_memories>
+${data.userMemories}
+</user_memories>
+<relevant_context>
+${relevant.map((r) => `- ${r.memory}`).join("\n")}
+</relevant_context>
+`.trim()
+}
+
+const model = withSupermemory(openai("gpt-4"), "user-123", {
+  mode: "full",
+  promptTemplate: selectivePrompt
+})
+```
+
 ### Custom Branding
 
 Remove "supermemories" references and use your own branding:

apps/docs/integrations/ai-sdk.mdx

@@ -75,7 +75,7 @@ const model = withSupermemory(openai("gpt-4"), "user-123", { mode: "full" })
 
 ### Custom Prompt Templates
 
-Customize how memories are formatted:
+Customize how memories are formatted. The template receives `userMemories`, `generalSearchMemories`, and `searchResults` (raw array for filtering by metadata):
 
 ```typescript
 import { withSupermemory, type MemoryPromptData } from "@supermemory/tools/ai-sdk"

apps/docs/integrations/mastra.mdx

@@ -162,7 +162,7 @@ await agent.generate("My favorite framework is Next.js")
 
 ## Custom Prompt Templates
 
-Customize how memories are formatted and injected:
+Customize how memories are formatted and injected. The template receives `userMemories`, `generalSearchMemories`, and `searchResults` (raw array for filtering by metadata):
 
 ```typescript
 import { Agent } from "@mastra/core/agent"