feat: Add basic_criteria ADK eval sample

Add contributing/samples/evaluation/basic_criteria/, demonstrating the
deterministic built-in metrics tool_trajectory_avg_score and
response_match_score against the shared home-automation agent, run via
`adk eval`.

Co-authored-by: Haran Rajkumar <haranrk@google.com>
PiperOrigin-RevId: 952586163

Author: haranrk

contributing/samples/evaluation/README.md

@@ -37,8 +37,9 @@ answer.
 
 ## Samples
 
-| Sample | Concept | Criteria |
-| ------ | ------- | -------- |
+| Sample                                | Concept                                | Criteria                                            |
+| ------------------------------------- | -------------------------------------- | --------------------------------------------------- |
+| [`basic_criteria`](./basic_criteria/) | Deterministic, reference-based scoring | `tool_trajectory_avg_score`, `response_match_score` |
 
 ## Graph
 

contributing/samples/evaluation/basic_criteria/README.md

@@ -0,0 +1,78 @@
+# Basic evaluation criteria
+
+## Overview
+
+Evaluates the shared home-automation agent with the two deterministic,
+reference-based criteria:
+
+- `tool_trajectory_avg_score`: does the agent call the right tools with the
+  right args? Each expected tool call (name + args) is compared against what the
+  agent actually did.
+- `response_match_score`: ROUGE-1 word overlap between the agent's final
+  response and a reference answer.
+
+Both criteria are computed locally with no judge model, so this sample needs only
+a model credential for the agent's own inference (a Gemini API key or Vertex).
+
+## Sample Inputs
+
+The eval set (`home_automation.evalset.json`) contains two single-turn cases:
+
+- `Turn off device_2.`
+- `What is the temperature in the Living Room?`
+
+## How To
+
+Run the sample from the workspace root:
+
+```bash
+adk eval contributing/samples/evaluation/home_automation_agent \
+    contributing/samples/evaluation/basic_criteria/home_automation.evalset.json \
+    --config_file_path contributing/samples/evaluation/basic_criteria/eval_config.json \
+    --print_detailed_results
+```
+
+`adk eval` takes the agent folder and the eval-set file as two separate
+arguments, so this folder holds only eval data (`home_automation.evalset.json`),
+the criteria config (`eval_config.json`), and this README, with no agent code.
+
+### `match_type` for tool trajectory
+
+`tool_trajectory_avg_score` has a `match_type` (set to `EXACT` here in
+`eval_config.json`) that controls how the expected and actual tool calls are
+compared:
+
+- `EXACT`: the actual tool calls must match the expected calls one-for-one, in
+  the same order, with identical args. Use this when the trajectory is fully
+  deterministic (as in this sample).
+- `IN_ORDER`: the expected calls must appear in the given order, but extra
+  actual calls in between are tolerated. Useful when the agent may take
+  additional, harmless steps.
+- `ANY_ORDER`: the expected calls must all appear, but order does not matter.
+  Useful when the agent may reorder independent tool calls.
+
+The `threshold` is `1.0`, so every expected call must match for the case to pass.
+
+### Why `response_match_score` uses a `0.6` threshold
+
+`adk eval` runs live inference, so the exact wording of the agent's final
+response varies from run to run (for example, "I have turned off device_2." vs
+"device_2 has been switched off."). `response_match_score` is a ROUGE-1 score,
+which measures word overlap rather than exact-string equality, so it tolerates
+this phrasing variation. The `0.6` threshold requires the response to share most
+of its wording with the reference while still allowing some rewording. Raise it
+toward `1.0` for stricter wording, lower it to tolerate more paraphrasing.
+
+### Expectations captured from a real run
+
+The expected `tool_uses` (tool names and args) in `home_automation.evalset.json`
+were captured from an actual `adk eval` run of the agent: run with
+`--print_detailed_results`, read the printed Actual-vs-Expected, then set the
+expected values to match what the agent really produced. The reference
+`final_response` for each case is an independently written natural answer (not a
+copy of the model output), which is exactly what ROUGE-1 is designed to tolerate.
+
+## Related Guides
+
+- Evaluation overview: https://adk.dev/evaluate/
+- Evaluation criteria reference: https://adk.dev/evaluate/criteria/

contributing/samples/evaluation/basic_criteria/eval_config.json

@@ -0,0 +1,9 @@
+{
+  "criteria": {
+    "tool_trajectory_avg_score": {
+      "threshold": 1.0,
+      "match_type": "EXACT"
+    },
+    "response_match_score": 0.6
+  }
+}

contributing/samples/evaluation/basic_criteria/home_automation.evalset.json

@@ -0,0 +1,62 @@
+{
+  "eval_set_id": "basic_criteria",
+  "name": "Basic deterministic criteria",
+  "description": "Single-turn cases scored by tool trajectory and ROUGE-1.",
+  "eval_cases": [
+    {
+      "eval_id": "turn_off_bedroom_device",
+      "conversation": [
+        {
+          "invocation_id": "basic-1",
+          "user_content": {
+            "parts": [{"text": "Turn off device_2."}],
+            "role": "user"
+          },
+          "final_response": {
+            "parts": [{"text": "device_2 is now turned off."}],
+            "role": "model"
+          },
+          "intermediate_data": {
+            "tool_uses": [
+              {"name": "set_device_info",
+               "args": {"device_id": "device_2", "status": "OFF"}}
+            ],
+            "intermediate_responses": []
+          }
+        }
+      ],
+      "session_input": {
+        "app_name": "home_automation_agent",
+        "user_id": "user",
+        "state": {}
+      }
+    },
+    {
+      "eval_id": "get_living_room_temperature",
+      "conversation": [
+        {
+          "invocation_id": "basic-2",
+          "user_content": {
+            "parts": [{"text": "What is the temperature in the Living Room?"}],
+            "role": "user"
+          },
+          "final_response": {
+            "parts": [{"text": "The Living Room is 22 degrees Celsius."}],
+            "role": "model"
+          },
+          "intermediate_data": {
+            "tool_uses": [
+              {"name": "get_temperature", "args": {"location": "Living Room"}}
+            ],
+            "intermediate_responses": []
+          }
+        }
+      ],
+      "session_input": {
+        "app_name": "home_automation_agent",
+        "user_id": "user",
+        "state": {}
+      }
+    }
+  ]
+}