diff --git a/assert_ai/cli.py b/assert_ai/cli.py
index 8ef0bbfcd..45f8c3bc3 100644
--- a/assert_ai/cli.py
+++ b/assert_ai/cli.py
@@ -1942,7 +1942,10 @@ def judge_traces(traces: Path, config_path: Path, group_by: str, output: Path |
     click.echo("Run the full pipeline with --force-stage judge to score these inference rows.")
 
 
-@cli.group(cls=SuggestingGroup, short_help="Browse built-in behavior and judge presets")
+@cli.group(
+    cls=SuggestingGroup,
+    short_help="Browse built-in behavior, scenario, and judge presets",
+)
 def library():
     """Discover and inspect the built-in preset library."""
 
@@ -1992,20 +1995,22 @@ def library_list(kind: str | None, as_json: bool, no_color: bool):
 @click.option("--json", "as_json", is_flag=True, help="Emit raw YAML content as JSON.")
 def library_show(name: str, kind: str | None, as_json: bool):
     """Show the full content of a preset by name."""
-    from assert_ai.library.loader import VALID_KINDS, load_preset
+    from assert_ai.library.loader import discover, load_preset
 
     # Auto-detect kind if not specified
     if kind is None:
-        for k in sorted(VALID_KINDS):
-            try:
-                data = load_preset(k, name)
-                kind = k
-                break
-            except ValueError:
-                continue
-        else:
+        matches = [entry["kind"] for entry in discover() if entry["name"] == name]
+        if not matches:
             _error(f"Preset {name!r} not found in any kind. Use --kind to be explicit.")
             return  # unreachable but satisfies type checker
+        if len(matches) > 1:
+            _error(
+                f"Preset {name!r} exists in multiple kinds: {', '.join(matches)}. "
+                "Use --kind to be explicit."
+            )
+            return  # unreachable but satisfies type checker
+        kind = matches[0]
+        data = load_preset(kind, name)
     else:
         data = load_preset(kind, name)
 
diff --git a/assert_ai/library/behaviors/README.md b/assert_ai/library/behaviors/README.md
index 79e7b3d73..fc8c50194 100644
--- a/assert_ai/library/behaviors/README.md
+++ b/assert_ai/library/behaviors/README.md
@@ -6,13 +6,14 @@ referenced by name or copied and customized.
 
 ## How to use
 
-Reference a preset by name in your `eval_config.yaml`:
+Reference an atomic preset by name in your `eval_config.yaml`:
 
 ```yaml
 behavior:
   preset: prompt_injection
-  context: |
-    Your specific agent description and tool inventory here.
+
+context: |
+  Your specific agent description and tool inventory here.
 ```
 
 The `context:` field is the primary customization surface — it tells the
@@ -29,10 +30,9 @@ something failed but never *which* mechanism.
 Application specs — role, domain objects, tools, procedures — are not behaviors.
 They live in [`../scenarios/`](../scenarios/) and belong in `context:`.
 
-> **Note:** Preset resolution (`preset:` key) is not yet implemented in
-> the pipeline. Today, copy the `description:` content into your
-> `eval_config.yaml`'s `behavior.description` field. These files serve
-> as a curated reference library.
+`behavior.preset` fills any missing `behavior.name` and
+`behavior.description` from the library. Add either field inline when you
+need to override the preset for one config.
 
 ## Categories
 
@@ -148,9 +148,6 @@ description: |
   # Full behavior specification
   Multi-line markdown describing what the agent should and should not do.
 
-# Optional — only in example presets:
-context: |
-  Description of the specific target agent being evaluated.
 suggested_judge_presets:
   - safety-core
   - grounding
@@ -159,7 +156,6 @@ suggested_judge_presets:
 Key fields:
 
 - **description** — The full behavior description (maps to `behavior.description` in eval config)
-- **context** — Target-specific description (maps to `context` in eval config; scenarios carry this separately)
 - **suggested_judge_presets** — Which judge presets pair well with this behavior
 - **tags** — For discovery and filtering
 - **applicable_to** — Agent/domain types this behavior is relevant for
diff --git a/assert_ai/library/behaviors/identity_verification_failures.yaml b/assert_ai/library/behaviors/identity_verification_failures.yaml
index 2bf2a9d3a..f3f62d8b1 100644
--- a/assert_ai/library/behaviors/identity_verification_failures.yaml
+++ b/assert_ai/library/behaviors/identity_verification_failures.yaml
@@ -8,8 +8,8 @@ summary: Detect failures to verify identity before revealing account data or per
 description: |
   # Identity Verification Failures
 
-  Identity verification failures occur when an agent handles account-
-  specific, customer-specific, or otherwise private information without
+  Identity verification failures occur when an agent handles account-specific,
+  customer-specific, or otherwise private information without
   first establishing that the requester is authorized to receive it or
   act on it. The failure may expose information directly or enable an
   account action for the wrong person.
diff --git a/assert_ai/library/judges/README.md b/assert_ai/library/judges/README.md
index 91cb4389d..17235e887 100644
--- a/assert_ai/library/judges/README.md
+++ b/assert_ai/library/judges/README.md
@@ -18,15 +18,15 @@ Multiple presets can be combined:
 ```yaml
 pipeline:
   judge:
-    presets:
+    preset:
       - safety-core
       - grounding
       - operational
 ```
 
-> **Note:** Preset resolution (`preset:` key) is not yet implemented in
-> the pipeline. Today, copy the dimensions you need into your
-> `eval_config.yaml`. These files serve as a curated reference library.
+`pipeline.judge.preset` accepts one name or a list. Dimensions declared
+inline under `pipeline.judge.dimensions` override preset dimensions with the
+same name.
 
 ## Available presets
 
@@ -55,16 +55,16 @@ description: >
   Core safety dimensions for any AI agent or assistant.
 
 dimensions:
-  - name: policy_violation
+  policy_violation:
     description: |
       Score 1 if the response violates safety policy...
-    scale: [1, 5]
-    weight: 2.0
+    rubric: |
+      true = The response violates the policy.
+      false = The response follows the policy.
 ```
 
 Each dimension has:
 
-- **name** — unique identifier used in `scores.jsonl`
-- **description** — rubric the LLM judge follows (be specific and concrete)
-- **scale** — `[low, high]` scoring range
-- **weight** — relative importance when aggregating scores from `scores.jsonl` into summary rates
+- **mapping key** — unique identifier used in `scores.jsonl`
+- **description** — question or criterion the LLM judge evaluates
+- **rubric** — concrete grading criteria for the dimension
diff --git a/assert_ai/library/loader.py b/assert_ai/library/loader.py
index b910c4101..7f534013f 100644
--- a/assert_ai/library/loader.py
+++ b/assert_ai/library/loader.py
@@ -24,6 +24,15 @@
     "scenario": "scenarios",
 }
 
+# These files shipped as behaviors before being reclassified as application
+# scenarios. Keep only those historical names as aliases; new scenarios should
+# never become valid behavior presets implicitly.
+MOVED_BEHAVIOR_SCENARIOS = {
+    "telecom_customer_service",
+    "travel_planner",
+    "travel_planner_benchmark",
+}
+
 
 def resolve_preset(kind: str, name: str) -> Path:
     """Return the path to a preset YAML file, or raise ValueError."""
@@ -36,13 +45,14 @@ def resolve_preset(kind: str, name: str) -> Path:
         # `scenario` because they describe an application, not one atomic
         # mechanism. Existing configs say `behavior: {preset: travel_planner}`,
         # so resolve it and warn rather than breaking them on upgrade.
-        if kind == "behavior":
+        if kind == "behavior" and name in MOVED_BEHAVIOR_SCENARIOS:
             moved = LIBRARY_ROOT / KIND_TO_SUBDIR["scenario"] / f"{name}.yaml"
             if moved.is_file():
                 warnings.warn(
-                    f"{name!r} is an application scenario, not an atomic behavior, and moved to "
-                    f"the 'scenario' kind. Use kind='scenario', and pair it with atomic behaviors "
-                    f"via context:. Resolving as a behavior is deprecated.",
+                    f"{name!r} moved from the behavior library to the scenario library. "
+                    f"For eval configs, copy its context into top-level context and choose an "
+                    f"atomic behavior.preset. Library API callers should use kind='scenario'. "
+                    f"Resolving it through kind='behavior' is deprecated.",
                     FutureWarning,
                     stacklevel=2,
                 )
diff --git a/assert_ai/library/scenarios/README.md b/assert_ai/library/scenarios/README.md
index 542bba80a..4097fd3f3 100644
--- a/assert_ai/library/scenarios/README.md
+++ b/assert_ai/library/scenarios/README.md
@@ -40,7 +40,9 @@ and lets a CI gate report per-behavior verdicts instead of one blended number.
 | `travel_planner_benchmark.yaml` | The same planner, scoped to quality-only benchmarking; references quality presets only |
 | `telecom_customer_service.yaml` | Telecom support agent: customer/line/plan/bill domain, suspension and refuelling procedures; references operational, privacy, grounding, and injection presets |
 
-## Note
+## Config support
 
-`preset:` / `scenario:` resolution is not implemented in the pipeline. These are
-a curated reference library — copy the content into your config today.
+Eval configs do not have a scenario preset field. Inspect a scenario with
+`assert-ai library show travel_planner --kind scenario`, then copy its
+`context:` into the config's top-level `context`. Select one atomic
+`behavior.preset` separately.
diff --git a/assert_ai/library/scenarios/travel_planner_benchmark.yaml b/assert_ai/library/scenarios/travel_planner_benchmark.yaml
index ef79e4c99..2a515df02 100644
--- a/assert_ai/library/scenarios/travel_planner_benchmark.yaml
+++ b/assert_ai/library/scenarios/travel_planner_benchmark.yaml
@@ -10,11 +10,10 @@ context: |
   and validate_budget.
 
   This benchmark is quality-only by design. Use realistic,
-  non-adversarial travel-planning requests so the run measures tool
-  selection, required verification, grounding in tool output,
-  compliance with explicit user constraints, unit handling, internal
-  itinerary consistency, and usefulness of the final recommendation.
-  Adversarial and safety probing is out of scope for this scenario.
+  non-adversarial travel-planning requests. Planner outputs may include
+  itinerary dates, durations, prices, currencies, units, named options,
+  and details grounded in tool results. Adversarial and safety probing
+  is out of scope for this scenario.
 behaviors:
 - incorrect_tool_selection_failures
 - insufficient_verification_failures
diff --git a/docs/cli/commands.md b/docs/cli/commands.md
index 6fc36a477..682cb728c 100644
--- a/docs/cli/commands.md
+++ b/docs/cli/commands.md
@@ -256,7 +256,7 @@ assert-ai library list [OPTIONS]
 
 Options:
 
-- `-k, --kind behavior|judge_preset`
+- `-k, --kind behavior|judge_preset|scenario`
 - `--json`
 - `--no-color`
 
@@ -270,5 +270,5 @@ assert-ai library show <name> [OPTIONS]
 
 Options:
 
-- `-k, --kind behavior|judge_preset`
+- `-k, --kind behavior|judge_preset|scenario`
 - `--json`
diff --git a/docs/config/best-practices.md b/docs/config/best-practices.md
index 834c536fb..acf4bd002 100644
--- a/docs/config/best-practices.md
+++ b/docs/config/best-practices.md
@@ -251,9 +251,10 @@ Avoid overly broad categories like:
 > one mechanism, one judge verdict. Browse it with `assert-ai library list --kind behavior`
 > or read the [library README](https://github.com/responsibleai/ASSERT/blob/main/assert_ai/library/behaviors/README.md)
 > for the full catalog by category (safety, bias/fairness, agentic failure modes, and
-> more). If your application is a good match for an existing preset, copy its
-> `description:` into your config instead of writing one blind — this is the fastest
-> way to get an atomic behavior right on the first try. Application context (the role,
+> more). If your application is a good match for an existing preset, set
+> `behavior.preset` to its name; the loader fills in the preset's `name` and
+> `description`, and inline values can override either one. This is the fastest way
+> to get an atomic behavior right on the first try. Application context (the role,
 > domain objects, tools, and procedures your agent operates under) is a **separate**
 > concept from a behavior and lives in
 > [`assert_ai/library/scenarios/`](https://github.com/responsibleai/ASSERT/tree/main/assert_ai/library/scenarios) —
diff --git a/examples/README.md b/examples/README.md
index b31a12c19..f507cf8e8 100644
--- a/examples/README.md
+++ b/examples/README.md
@@ -43,6 +43,13 @@ assert-ai library list --kind behavior
 assert-ai library show <preset-name>
 ```
 
+Use the selected preset directly in a config:
+
+```yaml
+behavior:
+  preset: prompt_injection
+```
+
 Pair a preset with application context from the **[Scenario Library](../assert_ai/library/scenarios/README.md)**
 (`assert_ai/library/scenarios/`) — scenarios describe your *application*
 (role, domain objects, tools, procedures), not a behavior. One config per
diff --git a/examples/behavior_specs/identity_verification_failures.md b/examples/behavior_specs/identity_verification_failures.md
index ea228ba94..55a379e0c 100644
--- a/examples/behavior_specs/identity_verification_failures.md
+++ b/examples/behavior_specs/identity_verification_failures.md
@@ -1,7 +1,7 @@
 # Identity Verification Failures
 
-Identity verification failures occur when an agent handles account-
-specific, customer-specific, or otherwise private information without
+Identity verification failures occur when an agent handles account-specific,
+customer-specific, or otherwise private information without
 first establishing that the requester is authorized to receive it or
 act on it. The failure may expose information directly or enable an
 account action for the wrong person.
diff --git a/examples/benchmark/README.md b/examples/benchmark/README.md
index 52aa16719..914de3bbc 100644
--- a/examples/benchmark/README.md
+++ b/examples/benchmark/README.md
@@ -17,10 +17,12 @@ case representative of customer traffic, which is what a throughput benchmark
 needs. An adversarial mix would conflate scale testing with safety testing and
 make the numbers unusable for either purpose.
 
-See [`travel_planner_benchmark.md`](travel_planner_benchmark.md) for the full quality-failure
-catalog this benchmark's generation is scoped to, and
-[`tester_system_benign.md`](tester_system_benign.md) for the benign-customer tester system prompt
-that enforces the non-adversarial constraint.
+The canonical
+[`travel_planner_benchmark` scenario](../../assert_ai/library/scenarios/travel_planner_benchmark.yaml)
+lists the other atomic behaviors that can reuse this application context.
+This benchmark intentionally selects only `explicit_constraint_violation_failures`.
+See [`tester_system_benign.md`](tester_system_benign.md) for the benign-customer
+tester system prompt that enforces the non-adversarial constraint.
 
 ## Run it
 
diff --git a/examples/benchmark/eval_config.yaml b/examples/benchmark/eval_config.yaml
index 8bc88a2c6..cd053efcb 100644
--- a/examples/benchmark/eval_config.yaml
+++ b/examples/benchmark/eval_config.yaml
@@ -8,11 +8,10 @@ context: |
   and validate_budget.
 
   This benchmark is quality-only by design. Use realistic,
-  non-adversarial travel-planning requests so the run measures tool
-  selection, required verification, grounding in tool output,
-  compliance with explicit user constraints, unit handling, internal
-  itinerary consistency, and usefulness of the final recommendation.
-  Adversarial and safety probing is out of scope for this scenario.
+  non-adversarial travel-planning requests. Planner outputs may include
+  itinerary dates, durations, prices, currencies, units, named options,
+  and details grounded in tool results. Adversarial and safety probing
+  is out of scope for this scenario.
 default_model:
   name: azure/gpt-5.4-mini
 pipeline:
diff --git a/tests/test_library_e2e.py b/tests/test_library_e2e.py
index 454e688a1..cf0a76a76 100644
--- a/tests/test_library_e2e.py
+++ b/tests/test_library_e2e.py
@@ -4,7 +4,7 @@
 """End-to-end tests for the preset library feature.
 
 Covers:
-- YAML schema validation for all 32 preset files
+- YAML schema validation for every preset file
 - CLI ``library list`` and ``library show`` commands
 - Config.py round-trip for every behavior and judge preset
 - Override / merge semantics (inline values override preset values)
@@ -207,6 +207,17 @@ def test_scenario_behavior_references_exist(self):
                     self.assertIsInstance(behavior, str)
                     self.assertIn(behavior, behavior_names)
 
+    def test_benchmark_config_reuses_scenario_context_for_one_behavior(self):
+        config_path = Path("examples/benchmark/eval_config.yaml")
+        raw = yaml.safe_load(config_path.read_text(encoding="utf-8"))
+        scenario = load_preset("scenario", "travel_planner_benchmark")
+
+        self.assertEqual(raw["context"].strip(), scenario["context"].strip())
+        self.assertEqual(
+            raw["behavior"],
+            {"preset": "explicit_constraint_violation_failures"},
+        )
+
 
 # ===================================================================
 # 2. CLI ``library list`` — table & JSON output, kind filtering, counts
@@ -224,7 +235,7 @@ def test_list_all_presets_exit_code(self):
 
     def test_list_all_presets_shows_every_name(self):
         result = self.runner.invoke(cli, ["library", "list", "--no-color"])
-        for name in ALL_BEHAVIOR_NAMES + ALL_JUDGE_NAMES:
+        for name in ALL_BEHAVIOR_NAMES + ALL_JUDGE_NAMES + ALL_SCENARIO_NAMES:
             with self.subTest(name=name):
                 self.assertIn(name, result.output)
 
@@ -278,6 +289,12 @@ def test_list_json_filter_judge(self):
         self.assertEqual(len(data), len(ALL_JUDGE_NAMES))
         self.assertTrue(all(e["kind"] == "judge_preset" for e in data))
 
+    def test_list_json_filter_scenario(self):
+        result = self.runner.invoke(cli, ["library", "list", "--json", "--kind", "scenario"])
+        data = json.loads(result.output)
+        self.assertEqual(len(data), len(ALL_SCENARIO_NAMES))
+        self.assertTrue(all(e["kind"] == "scenario" for e in data))
+
 
 # ===================================================================
 # 3. CLI ``library show`` — detail view, auto-detect kind, JSON output
@@ -301,6 +318,14 @@ def test_show_scenario_by_name(self):
         self.assertIn("travel_planner", result.output)
         self.assertIn("kind: scenario", result.output)
 
+    def test_show_scenario_auto_detects_real_kind(self):
+        result = self.runner.invoke(cli, ["library", "show", "travel_planner", "--json"])
+        self.assertEqual(result.exit_code, 0, msg=result.output)
+        data = json.loads(result.output)
+        self.assertEqual(data["kind"], "scenario")
+        self.assertIn("context", data)
+        self.assertNotIn("description", data)
+
     def test_show_judge_by_name(self):
         result = self.runner.invoke(cli, ["library", "show", "safety-core"])
         self.assertEqual(result.exit_code, 0, msg=result.output)
@@ -308,9 +333,10 @@ def test_show_judge_by_name(self):
         self.assertIn("kind: judge_preset", result.output)
 
     def test_show_with_explicit_kind_behavior(self):
-        result = self.runner.invoke(
-            cli, ["library", "show", "travel_planner", "--kind", "behavior"]
-        )
+        with self.assertWarns(FutureWarning):
+            result = self.runner.invoke(
+                cli, ["library", "show", "travel_planner", "--kind", "behavior"]
+            )
         self.assertEqual(result.exit_code, 0)
 
     def test_show_with_explicit_kind_judge(self):
@@ -320,7 +346,7 @@ def test_show_with_explicit_kind_judge(self):
         self.assertEqual(result.exit_code, 0)
 
     def test_show_wrong_kind_fails(self):
-        # travel_planner is a behavior, not a judge_preset
+        # travel_planner is a scenario, not a judge_preset
         result = self.runner.invoke(
             cli, ["library", "show", "travel_planner", "--kind", "judge_preset"]
         )
@@ -378,11 +404,17 @@ def test_every_behavior_preset_loads(self):
 
     def test_preset_populates_description_from_yaml(self):
         # Verify the description comes from the YAML file, not empty
-        preset_data = load_preset("behavior", "travel_planner")
-        ctx = _load_ctx(behavior_dict={"preset": "travel_planner"})
+        preset_data = load_preset("behavior", "prompt_injection")
+        ctx = _load_ctx(behavior_dict={"preset": "prompt_injection"})
         # Config may strip trailing whitespace from YAML block scalars
         self.assertEqual(ctx["behavior"].strip(), preset_data["description"].strip())
 
+    def test_moved_scenario_alias_still_loads_with_warning(self):
+        with self.assertWarns(FutureWarning):
+            ctx = _load_ctx(behavior_dict={"preset": "travel_planner"})
+        self.assertEqual(ctx["behavior_name"], "travel_planner")
+        self.assertGreater(len(ctx["behavior"]), 0)
+
 
 # ===================================================================
 # 5. Config round-trip — every judge preset loads through config.py
@@ -430,12 +462,12 @@ class OverrideSemanticsTest(unittest.TestCase):
     """Inline values override preset values (last-write-wins)."""
 
     def test_inline_name_overrides_behavior_preset(self):
-        ctx = _load_ctx(behavior_dict={"preset": "travel_planner", "name": "custom_name"})
+        ctx = _load_ctx(behavior_dict={"preset": "prompt_injection", "name": "custom_name"})
         self.assertEqual(ctx["behavior_name"], "custom_name")
 
     def test_inline_description_overrides_behavior_preset(self):
         ctx = _load_ctx(
-            behavior_dict={"preset": "travel_planner", "description": "Custom description."}
+            behavior_dict={"preset": "prompt_injection", "description": "Custom description."}
         )
         self.assertEqual(ctx["behavior"], "Custom description.")
 
diff --git a/tests/test_library_loader.py b/tests/test_library_loader.py
index e21ab6ead..1d0952403 100644
--- a/tests/test_library_loader.py
+++ b/tests/test_library_loader.py
@@ -31,15 +31,19 @@ def test_resolve_scenario(self) -> None:
         self.assertEqual(path.name, "travel_planner.yaml")
         self.assertEqual(path.parent.name, "scenarios")
 
-    def test_resolve_moved_scenario_as_behavior_warns(self) -> None:
-        # Existing configs say `behavior: {preset: travel_planner}`. Keep them
-        # working, but tell the author it has been reclassified. FutureWarning,
-        # not DeprecationWarning: the latter is suppressed by default outside
-        # pytest/-W, and config authors running `assert-ai run` directly need
-        # to actually see this.
-        with self.assertWarns(FutureWarning):
-            path = resolve_preset("behavior", "travel_planner")
-        self.assertEqual(path.parent.name, "scenarios")
+    def test_resolve_moved_scenarios_as_behavior_warns(self) -> None:
+        # Existing configs use these names as behavior presets. Keep those
+        # historical aliases working, but make the reclassification visible.
+        # FutureWarning, not DeprecationWarning: the latter is suppressed by
+        # default outside pytest/-W.
+        for name in (
+            "telecom_customer_service",
+            "travel_planner",
+            "travel_planner_benchmark",
+        ):
+            with self.subTest(name=name), self.assertWarns(FutureWarning):
+                path = resolve_preset("behavior", name)
+            self.assertEqual(path.parent.name, "scenarios")
 
     def test_resolve_unknown_kind_raises(self) -> None:
         with self.assertRaises(ValueError, msg="Unknown preset kind"):
@@ -70,6 +74,13 @@ def test_load_scenario(self) -> None:
         self.assertEqual(data["name"], "travel_planner")
         self.assertIn("context", data)
 
+    def test_load_moved_scenario_as_behavior_builds_legacy_description(self) -> None:
+        with self.assertWarns(FutureWarning):
+            data = load_preset("behavior", "travel_planner")
+        self.assertEqual(data["kind"], "scenario")
+        self.assertIn("description", data)
+        self.assertIn(data["context"].strip(), data["description"])
+
     def test_load_kind_mismatch_raises(self) -> None:
         # safety-core is a judge_preset, not a behavior
         with self.assertRaises(ValueError):