diff --git a/packages/agent-cache-py/betterdb_agent_cache/__init__.py b/packages/agent-cache-py/betterdb_agent_cache/__init__.py
index 39a32514..bea76343 100644
--- a/packages/agent-cache-py/betterdb_agent_cache/__init__.py
+++ b/packages/agent-cache-py/betterdb_agent_cache/__init__.py
@@ -16,6 +16,7 @@
 )
 from .types import (
     AgentCacheOptions,
+    CacheResult,
     ConfigRefreshOptions,
     DiscoveryOptions,
     AgentCacheStats,
@@ -37,6 +38,7 @@
     ToolDefinition,
     ToolEffectivenessEntry,
     ToolPolicy,
+    ToolRecommendation,
     ToolResultBlock,
     ToolStats,
     ToolStoreOptions,
@@ -64,7 +66,9 @@
     "TierStats",
     "SessionStats",
     "ToolStats",
+    "CacheResult",
     "ToolEffectivenessEntry",
+    "ToolRecommendation",
     # Content blocks
     "ContentBlock",
     "TextBlock",
diff --git a/packages/agent-cache-py/betterdb_agent_cache/types.py b/packages/agent-cache-py/betterdb_agent_cache/types.py
index 227898e4..ea65d1da 100644
--- a/packages/agent-cache-py/betterdb_agent_cache/types.py
+++ b/packages/agent-cache-py/betterdb_agent_cache/types.py
@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from dataclasses import dataclass, field
-from typing import Any, Literal, NotRequired, Required, TypedDict
+from typing import Any, Literal, NotRequired, Required, TypedDict, Union
 
 
 # ─── Content blocks ───────────────────────────────────────────────────────────
@@ -238,9 +238,15 @@ class AgentCacheStats:
     per_tool: dict[str, ToolStats]
 
 
+ToolRecommendation = Literal["increase_ttl", "optimal", "decrease_ttl_or_disable"]
+
+
 @dataclass
 class ToolEffectivenessEntry:
     tool: str
     hit_rate: float
     cost_saved: float
-    recommendation: Literal["increase_ttl", "optimal", "decrease_ttl_or_disable"]
+    recommendation: ToolRecommendation
+
+
+CacheResult = Union[LlmCacheResult, ToolCacheResult]
diff --git a/packages/semantic-cache-py/betterdb_semantic_cache/__init__.py b/packages/semantic-cache-py/betterdb_semantic_cache/__init__.py
index 353a9ac9..78a7efb0 100644
--- a/packages/semantic-cache-py/betterdb_semantic_cache/__init__.py
+++ b/packages/semantic-cache-py/betterdb_semantic_cache/__init__.py
@@ -13,6 +13,7 @@
     hash_url,
     passthrough,
 )
+from .default_cost_table import DEFAULT_COST_TABLE
 from .semantic_cache import SemanticCache
 from .types import (
     CacheCheckOptions,
@@ -36,6 +37,7 @@
 )
 from .utils import (
     BinaryBlock,
+    BlockHints,
     ContentBlock,
     ReasoningBlock,
     TextBlock,
@@ -52,6 +54,7 @@
 
 __all__ = [
     "SemanticCache",
+    "DEFAULT_COST_TABLE",
     "SemanticCacheOptions",
     "ConfigRefreshOptions",
     "DiscoveryOptions",
@@ -92,6 +95,7 @@
     "ToolCallBlock",
     "ToolResultBlock",
     "ReasoningBlock",
+    "BlockHints",
     # utils
     "encode_float32",
     "decode_float32",
diff --git a/packages/semantic-cache-py/examples/openai_responses/main.py b/packages/semantic-cache-py/examples/openai_responses/main.py
new file mode 100644
index 00000000..5fc72d0b
--- /dev/null
+++ b/packages/semantic-cache-py/examples/openai_responses/main.py
@@ -0,0 +1,99 @@
+"""OpenAI Responses API + betterdb-semantic-cache example.
+
+Demonstrates prepare_semantic_params() from the openai_responses adapter
+extracting the semantic key from OpenAI Responses API params.
+
+Prerequisites:
+  - Valkey 8.0+ with valkey-search at localhost:6399
+  - OPENAI_API_KEY environment variable set
+
+Run:
+    pip install "betterdb-semantic-cache[openai]"
+    OPENAI_API_KEY=sk-... VALKEY_HOST=localhost VALKEY_PORT=6399 python examples/openai_responses/main.py
+"""
+from __future__ import annotations
+
+import asyncio
+import os
+import warnings
+
+
+async def main() -> None:
+    import valkey.asyncio as valkey
+    from openai import AsyncOpenAI
+
+    from betterdb_semantic_cache import SemanticCache, SemanticCacheOptions
+    from betterdb_semantic_cache.adapters.openai_responses import prepare_semantic_params
+    from betterdb_semantic_cache.embed.openai import create_openai_embed
+    from betterdb_semantic_cache.types import CacheStoreOptions
+
+    host = os.environ.get("VALKEY_HOST", "localhost")
+    port = int(os.environ.get("VALKEY_PORT", "6399"))
+    client_v = valkey.Valkey(host=host, port=port)
+    openai_client = AsyncOpenAI()
+
+    embed = create_openai_embed(model="text-embedding-3-small", client=openai_client)
+    cache = SemanticCache(SemanticCacheOptions(
+        client=client_v,
+        embed_fn=embed,
+        name="demo_openai_resp",
+        default_threshold=0.12,
+        default_ttl=300,
+    ))
+
+    warnings.warn("Flushing cache 'demo_openai_resp' on startup.", stacklevel=1)
+    await cache.initialize()
+    await cache.flush()
+    await cache.initialize()
+
+    print("=== OpenAI Responses API + SemanticCache example ===\n")
+
+    # -- Round 1: seed --
+    print("-- Round 1: Seeding --")
+    params1 = {
+        "model": "gpt-4o-mini",
+        "input": "What is the capital of Australia?",
+    }
+    print(f"User: {params1['input']}")
+    sp1 = await prepare_semantic_params(params1)
+    cached1 = await cache.check(sp1.text)
+    if cached1.hit:
+        print(f"  [cache HIT] similarity={cached1.similarity:.4f} confidence={cached1.confidence}")
+        answer1 = cached1.response
+    else:
+        print("  [cache MISS] calling OpenAI Responses API...")
+        resp1 = await openai_client.responses.create(**params1)
+        answer1 = getattr(resp1, "output_text", "") or ""
+        await cache.store(sp1.text, answer1, CacheStoreOptions(model=params1["model"]))
+    print(f"Assistant: {answer1}\n")
+
+    # -- Round 2: semantic hit --
+    print("-- Round 2: Semantic hit --")
+    params2 = {
+        "model": "gpt-4o-mini",
+        "input": "Which city is the capital of Australia?",
+    }
+    print(f"User: {params2['input']}")
+    sp2 = await prepare_semantic_params(params2)
+    cached2 = await cache.check(sp2.text)
+    if cached2.hit:
+        print(f"  [cache HIT] similarity={cached2.similarity:.4f} confidence={cached2.confidence}")
+        answer2 = cached2.response
+    else:
+        print("  [cache MISS] calling OpenAI Responses API...")
+        resp2 = await openai_client.responses.create(**params2)
+        answer2 = getattr(resp2, "output_text", "") or ""
+        await cache.store(sp2.text, answer2, CacheStoreOptions(model=params2["model"]))
+    print(f"Assistant: {answer2}\n")
+
+    # -- Stats --
+    stats = await cache.stats()
+    print("-- Cache Stats --")
+    print(f"Hits: {stats.hits} | Misses: {stats.misses}")
+
+    await cache.flush()
+    await client_v.aclose()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())