diff --git a/features/adaptive_context_strategy.feature b/features/adaptive_context_strategy.feature
new file mode 100644
index 000000000..616e48083
--- /dev/null
+++ b/features/adaptive_context_strategy.feature
@@ -0,0 +1,211 @@
+Feature: Adaptive Context Strategy Selector and Context Fusion
+  As a context assembly system
+  I want to intelligently select context strategies based on plan type
+  And combine results from multiple strategies with configurable weights
+  So that I can provide optimal context for different types of plans
+
+  Background:
+    Given I have an adaptive context selector
+    And I have a context fusion engine
+
+  Scenario: Register a context strategy
+    When I register a strategy named "semantic" with a mock implementation
+    Then the strategy "semantic" should be registered
+    And the list of registered strategies should contain "semantic"
+
+  Scenario: Register configuration for a plan type
+    Given I have registered a strategy named "semantic"
+    When I register configuration for plan type "coding" with primary strategy "semantic"
+    Then the configuration for plan type "coding" should exist
+    And the primary strategy for "coding" should be "semantic"
+
+  Scenario: Select strategy for a plan type
+    Given I have registered a strategy named "semantic"
+    And I have registered configuration for plan type "coding" with primary strategy "semantic"
+    When I select a strategy for plan type "coding"
+    Then the selected strategy should be "semantic"
+
+  Scenario: Select multiple strategies including fallbacks
+    Given I have registered strategies: "semantic", "syntactic", "lexical"
+    And I have registered configuration for plan type "analysis" with:
+      | primary_strategy | semantic |
+      | fallback_strategies | syntactic, lexical |
+    When I select all strategies for plan type "analysis"
+    Then I should get 3 strategies in order: "semantic", "syntactic", "lexical"
+
+  Scenario: Reject duplicate strategy registration
+    Given I have registered a strategy named "semantic"
+    When I try to register a strategy named "semantic" again
+    Then I should get an error about duplicate registration
+
+  Scenario: Reject configuration with unregistered primary strategy
+    When I try to register configuration with unregistered primary strategy "unknown"
+    Then I should get an error about unregistered strategy
+
+  Scenario: Reject configuration with unregistered fallback strategy
+    Given I have registered a strategy named "semantic"
+    When I try to register configuration with primary "semantic" and fallback "unknown"
+    Then I should get an error about unregistered fallback strategy
+
+  Scenario: Fuse results from multiple strategies with equal weights
+    Given I have registered strategies: "semantic", "syntactic"
+    And I have registered configuration for plan type "coding" with:
+      | primary_strategy | semantic |
+      | fallback_strategies | syntactic |
+    And I have strategy results:
+      | strategy | files |
+      | semantic | file1.py:0.8, file2.py:0.6 |
+      | syntactic | file1.py:0.7, file3.py:0.5 |
+    When I fuse the results for plan type "coding" with equal weights
+    Then the fused result should have ranked files:
+      | file | score |
+      | file1.py | 1.5 |
+      | file2.py | 0.6 |
+      | file3.py | 0.5 |
+
+  Scenario: Fuse results with custom weights
+    Given I have registered strategies: "semantic", "syntactic"
+    And I have registered configuration for plan type "coding" with:
+      | primary_strategy | semantic |
+      | fallback_strategies | syntactic |
+    And I have strategy results:
+      | strategy | files |
+      | semantic | file1.py:0.8, file2.py:0.6 |
+      | syntactic | file1.py:0.7, file3.py:0.5 |
+    When I fuse the results with custom weights:
+      | semantic | 0.7 |
+      | syntactic | 0.3 |
+    Then the fused result should have ranked files:
+      | file | score |
+      | file1.py | 0.77 |
+      | file2.py | 0.42 |
+      | file3.py | 0.15 |
+
+  Scenario: Get top files from fused result
+    Given I have a fused result with ranked files:
+      | file | score |
+      | file1.py | 1.5 |
+      | file2.py | 0.6 |
+      | file3.py | 0.5 |
+    When I get the top 2 files
+    Then I should get: "file1.py", "file2.py"
+
+  Scenario: Get file score from fused result
+    Given I have a fused result with ranked files:
+      | file | score |
+      | file1.py | 1.5 |
+      | file2.py | 0.6 |
+    When I get the score for "file1.py"
+    Then the file score should be 1.5
+
+  Scenario: Get file score for non-existent file
+    Given I have a fused result with ranked files:
+      | file | score |
+      | file1.py | 1.5 |
+    When I get the score for "nonexistent.py"
+    Then the file score should be None
+
+  Scenario: Reject fusion with no results
+    Given I have registered configuration for plan type "coding"
+    When I try to fuse with empty results
+    Then I should get an error about no results provided
+
+  Scenario: Reject fusion with invalid weights
+    Given I have registered strategies: "semantic", "syntactic"
+    And I have registered configuration for plan type "coding" with primary strategy "semantic"
+    And I have strategy results with "semantic" and "syntactic"
+    When I try to fuse with negative weight for "semantic"
+    Then I should get an error about invalid weight
+
+  Scenario: Normalize weights to sum to 1.0
+    Given I have a context fusion engine
+    When I normalize weights: semantic=2.0, syntactic=1.0
+    Then the normalized weights should be:
+      | semantic | 0.6666666666666666 |
+      | syntactic | 0.3333333333333333 |
+
+  Scenario: Get fusion metadata
+    Given I have registered strategies: "semantic", "syntactic"
+    And I have registered configuration for plan type "coding" with:
+      | primary_strategy | semantic |
+      | fallback_strategies | syntactic |
+    And I have strategy results:
+      | strategy | files |
+      | semantic | file1.py:0.8 |
+      | syntactic | file2.py:0.6 |
+    When I fuse the results for plan type "coding"
+    Then the fusion metadata should contain:
+      | plan_type | coding |
+      | num_strategies | 2 |
+      | num_files | 2 |
+
+  Scenario: List configured plan types
+    Given I have registered configuration for plan types: "coding", "analysis", "testing"
+    When I list all configured plan types
+    Then I should get plan types: "coding", "analysis", "testing"
+
+  Scenario: Get configuration for plan type
+    Given I have registered configuration for plan type "coding" with primary strategy "semantic"
+    When I get the configuration for plan type "coding"
+    Then the configuration should have primary strategy "semantic"
+
+  Scenario: Get configuration for non-existent plan type
+    When I get the configuration for plan type "unknown"
+    Then the configuration should be None
+
+  Scenario: Fuse with selector configuration weights
+    Given I have registered strategies: "semantic", "syntactic"
+    And I have registered configuration for plan type "coding" with:
+      | primary_strategy | semantic |
+      | fallback_strategies | syntactic |
+      | fusion_weights | semantic=0.7, syntactic=0.3 |
+    And I have strategy results:
+      | strategy | files |
+      | semantic | file1.py:0.8 |
+      | syntactic | file1.py:0.7 |
+    When I fuse with selector configuration weights
+    Then the fused result should have file "file1.py" with score 0.77
+
+  Scenario: Handle strategy results without ranked_files attribute
+    Given I have registered strategies: "semantic", "syntactic"
+    And I have registered configuration for plan type "coding" with primary strategy "semantic"
+    And I have strategy results where "syntactic" has no ranked_files attribute
+    When I fuse the results for plan type "coding"
+    Then the fusion should skip the strategy without ranked_files
+
+  Scenario: Validate strategy weight configuration
+    When I try to create a strategy weight with negative weight
+    Then I should get an error about invalid weight
+
+  Scenario: Validate adaptive strategy config
+    When I try to create adaptive strategy config without primary strategy
+    Then I should get an error about missing primary strategy
+
+  Scenario: Plan type enumeration
+    Then I should have plan types: "coding", "analysis", "documentation", "refactoring", "testing", "debugging", "unknown"
+
+  Scenario: Select strategy for unconfigured plan type raises error
+    When I try to select a strategy for unconfigured plan type "coding"
+    Then I should get an error about no configuration
+
+  Scenario: Select all strategies for unconfigured plan type raises error
+    When I try to select all strategies for unconfigured plan type "coding"
+    Then I should get an error about no configuration
+
+  Scenario: Fuse results for unconfigured plan type raises error
+    Given I have strategy results:
+      | strategy | files |
+      | semantic | file1.py:0.8 |
+    When I try to fuse results for unconfigured plan type "coding"
+    Then I should get an error about no configuration
+
+  Scenario: Fuse with selector for unconfigured plan type raises error
+    Given I have strategy results:
+      | strategy | files |
+      | semantic | file1.py:0.8 |
+    When I try to fuse with selector for unconfigured plan type "coding"
+    Then I should get an error about no configuration
+
+  Scenario: Create strategy weight with valid positive weight
+    When I create a strategy weight named "semantic" with weight 0.5
+    Then the strategy weight should have name "semantic" and weight 0.5
diff --git a/features/steps/adaptive_context_strategy_steps.py b/features/steps/adaptive_context_strategy_steps.py
new file mode 100644
index 000000000..d190c88f3
--- /dev/null
+++ b/features/steps/adaptive_context_strategy_steps.py
@@ -0,0 +1,717 @@
+"""Step definitions for adaptive context strategy selector and fusion tests."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from behave import given, then, when
+
+from cleveragents.domain.models.acms.adaptive_selector import (
+    AdaptiveContextSelector,
+    AdaptiveStrategyConfig,
+    ContextFusion,
+    FusedResult,
+    PlanType,
+    StrategyWeight,
+)
+from cleveragents.domain.models.acms.crp import ContextFragment
+from cleveragents.domain.models.acms.strategy import (
+    BackendSet,
+    ContextRequest,
+    ContextStrategy,
+    PlanContext,
+    StrategyCapabilities,
+)
+
+
+def _strip_quoted_csv(value: str) -> list[str]:
+    """Split a comma-separated quoted-string list and strip outer quotes.
+
+    The Gherkin form ``"a", "b", "c"`` is captured by behave as a single
+    placeholder containing the inner quotes (``a", "b", "c``); split by
+    ``", "`` and stripping leftover quotes recovers the original tokens.
+    """
+    return [item.strip().strip('"') for item in value.split(", ")]
+
+
+def _table_pairs(table: Any) -> list[tuple[str, str]]:
+    """Read a headerless 2-column behave table as ``(key, value)`` pairs.
+
+    Behave promotes the first row of a table to ``headings`` automatically.
+    For the no-header tables used by these scenarios we recover the lost
+    pair from ``headings`` and then iterate the data rows.
+    """
+    pairs: list[tuple[str, str]] = []
+    if len(table.headings) >= 2:
+        pairs.append((table.headings[0], table.headings[1]))
+    for row in table:
+        pairs.append((row.cells[0], row.cells[1]))
+    return pairs
+
+
+class MockStrategy:
+    """Mock strategy for testing."""
+
+    def __init__(self, strategy_name: str) -> None:
+        """Initialize mock strategy."""
+        self._name = strategy_name
+
+    @property
+    def name(self) -> str:
+        """Return strategy name."""
+        return self._name
+
+    @property
+    def capabilities(self) -> StrategyCapabilities:
+        """Return strategy capabilities."""
+        return StrategyCapabilities()
+
+    def can_handle(
+        self,
+        request: ContextRequest,
+        backends: BackendSet,
+    ) -> float:
+        """Return confidence for this request."""
+        return 1.0
+
+    def assemble(
+        self,
+        request: ContextRequest,
+        backends: BackendSet,
+        budget: int,
+        plan_context: PlanContext,
+    ) -> list[ContextFragment]:
+        """Execute mock strategy."""
+        return []
+
+    def explain(self) -> str:
+        """Return explanation."""
+        return f"Mock strategy: {self._name}"
+
+
+# Verify MockStrategy satisfies the ContextStrategy protocol
+assert isinstance(MockStrategy("test"), ContextStrategy)
+
+
+class MockStrategyResult:
+    """Mock strategy result for testing."""
+
+    def __init__(self, ranked_files: list[tuple[str, float]]) -> None:
+        """Initialize mock result."""
+        self.ranked_files = ranked_files
+
+
+@given("I have an adaptive context selector")
+def step_have_selector(context: Any) -> None:
+    """Initialize adaptive context selector."""
+    context.selector = AdaptiveContextSelector()
+
+
+@given("I have a context fusion engine")
+def step_have_fusion(context: Any) -> None:
+    """Initialize context fusion engine."""
+    if not hasattr(context, "selector"):
+        context.selector = AdaptiveContextSelector()
+    context.fusion = ContextFusion(context.selector)
+
+
+@when('I register a strategy named "{name}" with a mock implementation')
+def step_register_strategy(context: Any, name: str) -> None:
+    """Register a mock strategy."""
+    strategy = MockStrategy(name)
+    context.selector.register_strategy(name, strategy)
+
+
+@then('the strategy "{name}" should be registered')
+def step_verify_strategy_registered(context: Any, name: str) -> None:
+    """Verify strategy is registered."""
+    strategies = context.selector.list_registered_strategies()
+    assert name in strategies, f"Strategy {name} not found in {strategies}"
+
+
+@then('the list of registered strategies should contain "{name}"')
+def step_verify_strategy_in_list(context: Any, name: str) -> None:
+    """Verify strategy is in list."""
+    strategies = context.selector.list_registered_strategies()
+    assert name in strategies
+
+
+@when(
+    'I register configuration for plan type "{plan_type}" with primary strategy "{strategy}"'
+)
+def step_register_config_simple(context: Any, plan_type: str, strategy: str) -> None:
+    """Register configuration for plan type."""
+    plan_type_enum = PlanType(plan_type)
+    config = AdaptiveStrategyConfig(
+        plan_type=plan_type_enum,
+        primary_strategy=strategy,
+    )
+    context.selector.register_config(config)
+
+
+@then('the configuration for plan type "{plan_type}" should exist')
+def step_verify_config_exists(context: Any, plan_type: str) -> None:
+    """Verify configuration exists."""
+    plan_type_enum = PlanType(plan_type)
+    config = context.selector.get_config(plan_type_enum)
+    assert config is not None, f"No configuration for {plan_type}"
+
+
+@then('the primary strategy for "{plan_type}" should be "{strategy}"')
+def step_verify_primary_strategy(context: Any, plan_type: str, strategy: str) -> None:
+    """Verify primary strategy."""
+    plan_type_enum = PlanType(plan_type)
+    config = context.selector.get_config(plan_type_enum)
+    assert config is not None
+    assert config.primary_strategy == strategy
+
+
+@when('I select a strategy for plan type "{plan_type}"')
+def step_select_strategy(context: Any, plan_type: str) -> None:
+    """Select strategy for plan type."""
+    plan_type_enum = PlanType(plan_type)
+    context.selected_strategy = context.selector.select_strategy(plan_type_enum)
+
+
+@then('the selected strategy should be "{name}"')
+def step_verify_selected_strategy(context: Any, name: str) -> None:
+    """Verify selected strategy."""
+    assert context.selected_strategy.name == name
+
+
+@given('I have registered strategies: "{strategies}"')
+def step_register_multiple_strategies(context: Any, strategies: str) -> None:
+    """Register multiple strategies."""
+    for strategy_name in _strip_quoted_csv(strategies):
+        strategy = MockStrategy(strategy_name)
+        context.selector.register_strategy(strategy_name, strategy)
+
+
+@given('I have registered configuration for plan type "{plan_type}" with:')
+def step_register_config_with_table(context: Any, plan_type: str) -> None:
+    """Register configuration with table data (headerless 2-column table)."""
+    plan_type_enum = PlanType(plan_type)
+
+    config_data: dict[str, Any] = {}
+    for key, value in _table_pairs(context.table):
+        if key == "fallback_strategies":
+            config_data["fallback_strategies"] = [s.strip() for s in value.split(",")]
+        elif key == "fusion_weights":
+            weights = {}
+            for pair in value.split(","):
+                strategy, weight = pair.strip().split("=")
+                weights[strategy] = float(weight)
+            config_data["fusion_weights"] = weights
+        else:
+            config_data[key] = value
+
+    config = AdaptiveStrategyConfig(
+        plan_type=plan_type_enum,
+        primary_strategy=config_data.get("primary_strategy", ""),
+        fallback_strategies=config_data.get("fallback_strategies", []),
+        fusion_weights=config_data.get("fusion_weights", {}),
+    )
+    context.selector.register_config(config)
+
+
+@when('I select all strategies for plan type "{plan_type}"')
+def step_select_all_strategies(context: Any, plan_type: str) -> None:
+    """Select all strategies for plan type."""
+    plan_type_enum = PlanType(plan_type)
+    context.selected_strategies = context.selector.select_strategies(plan_type_enum)
+
+
+@then('I should get {count:d} strategies in order: "{strategies}"')
+def step_verify_strategy_order(context: Any, count: int, strategies: str) -> None:
+    """Verify strategy order."""
+    expected = _strip_quoted_csv(strategies)
+    assert len(context.selected_strategies) == count
+    for i, expected_name in enumerate(expected):
+        assert context.selected_strategies[i].name == expected_name
+
+
+@when('I try to register a strategy named "{name}" again')
+def step_try_duplicate_registration(context: Any, name: str) -> None:
+    """Try to register duplicate strategy."""
+    try:
+        strategy = MockStrategy(name)
+        context.selector.register_strategy(name, strategy)
+        context.error = None
+    except ValueError as e:
+        context.error = str(e)
+
+
+@then("I should get an error about duplicate registration")
+def step_verify_duplicate_error(context: Any) -> None:
+    """Verify duplicate registration error."""
+    assert context.error is not None
+    assert "already registered" in context.error
+
+
+@when('I try to register configuration with unregistered primary strategy "{strategy}"')
+def step_try_unregistered_primary(context: Any, strategy: str) -> None:
+    """Try to register config with unregistered primary strategy."""
+    try:
+        config = AdaptiveStrategyConfig(
+            plan_type=PlanType.CODING,
+            primary_strategy=strategy,
+        )
+        context.selector.register_config(config)
+        context.error = None
+    except ValueError as e:
+        context.error = str(e)
+
+
+@then("I should get an error about unregistered strategy")
+def step_verify_unregistered_error(context: Any) -> None:
+    """Verify unregistered strategy error."""
+    assert context.error is not None
+    assert "not registered" in context.error
+
+
+@when(
+    'I try to register configuration with primary "{primary}" and fallback "{fallback}"'
+)
+def step_try_unregistered_fallback(context: Any, primary: str, fallback: str) -> None:
+    """Try to register config with unregistered fallback."""
+    try:
+        config = AdaptiveStrategyConfig(
+            plan_type=PlanType.CODING,
+            primary_strategy=primary,
+            fallback_strategies=[fallback],
+        )
+        context.selector.register_config(config)
+        context.error = None
+    except ValueError as e:
+        context.error = str(e)
+
+
+@then("I should get an error about unregistered fallback strategy")
+def step_verify_unregistered_fallback_error(context: Any) -> None:
+    """Verify unregistered fallback error."""
+    assert context.error is not None
+    assert "not registered" in context.error
+
+
+@given("I have strategy results:")
+def step_have_strategy_results(context: Any) -> None:
+    """Parse strategy results from table."""
+    context.strategy_results = {}
+    for row in context.table:
+        strategy = row["strategy"]
+        files_str = row["files"]
+
+        ranked_files = []
+        for file_pair in files_str.split(", "):
+            file_path, score = file_pair.split(":")
+            ranked_files.append((file_path, float(score)))
+
+        context.strategy_results[strategy] = MockStrategyResult(ranked_files)
+
+
+@when('I fuse the results for plan type "{plan_type}" with equal weights')
+def step_fuse_equal_weights(context: Any, plan_type: str) -> None:
+    """Fuse results with equal weights."""
+    plan_type_enum = PlanType(plan_type)
+    context.fused_result = context.fusion.fuse_results(
+        plan_type_enum,
+        context.strategy_results,
+    )
+
+
+@when('I fuse the results for plan type "{plan_type}"')
+def step_fuse_for_plan_type(context: Any, plan_type: str) -> None:
+    """Fuse results using the configured weights for ``plan_type``."""
+    plan_type_enum = PlanType(plan_type)
+    context.fused_result = context.fusion.fuse_results(
+        plan_type_enum,
+        context.strategy_results,
+    )
+
+
+@then("the fused result should have ranked files:")
+def step_verify_ranked_files(context: Any) -> None:
+    """Verify ranked files in fused result."""
+    expected_files = {}
+    for row in context.table:
+        file_path = row["file"]
+        score = float(row["score"])
+        expected_files[file_path] = score
+
+    for file_path, expected_score in expected_files.items():
+        actual_score = context.fused_result.get_file_score(file_path)
+        assert actual_score is not None, f"File {file_path} not in results"
+        assert abs(actual_score - expected_score) < 0.0001, (
+            f"Score mismatch for {file_path}: "
+            f"expected {expected_score}, got {actual_score}"
+        )
+
+
+@when("I fuse the results with custom weights:")
+def step_fuse_custom_weights(context: Any) -> None:
+    """Fuse results with custom weights (headerless 2-column table)."""
+    weights: dict[str, float] = {}
+    for strategy, weight_str in _table_pairs(context.table):
+        weights[strategy] = float(weight_str)
+
+    plan_type_enum = PlanType.CODING
+    context.fused_result = context.fusion.fuse_results(
+        plan_type_enum,
+        context.strategy_results,
+        custom_weights=weights,
+    )
+
+
+@given("I have a fused result with ranked files:")
+def step_have_fused_result(context: Any) -> None:
+    """Create a fused result from table."""
+    ranked_files = []
+    strategy_contributions: dict[str, list[tuple[str, float]]] = {}
+
+    for row in context.table:
+        file_path = row["file"]
+        score = float(row["score"])
+        ranked_files.append((file_path, score))
+
+    context.fused_result = FusedResult(
+        ranked_files=ranked_files,
+        strategy_contributions=strategy_contributions,
+    )
+
+
+@when("I get the top {count:d} files")
+def step_get_top_files(context: Any, count: int) -> None:
+    """Get top N files from fused result."""
+    context.top_files = context.fused_result.get_top_files(limit=count)
+
+
+@then('I should get: "{files}"')
+def step_verify_top_files(context: Any, files: str) -> None:
+    """Verify top files."""
+    expected = _strip_quoted_csv(files)
+    assert context.top_files == expected
+
+
+@when('I get the score for "{file_path}"')
+def step_get_file_score(context: Any, file_path: str) -> None:
+    """Get score for a file."""
+    context.file_score = context.fused_result.get_file_score(file_path)
+
+
+@then("the file score should be {value}")
+def step_verify_file_score(context: Any, value: str) -> None:
+    """Verify file score."""
+    if value == "None":
+        assert context.file_score is None
+    else:
+        expected = float(value)
+        assert abs(context.file_score - expected) < 0.0001
+
+
+@when("I try to fuse with empty results")
+def step_try_fuse_empty(context: Any) -> None:
+    """Try to fuse with empty results."""
+    try:
+        plan_type_enum = PlanType.CODING
+        context.fusion.fuse_results(plan_type_enum, {})
+        context.error = None
+    except ValueError as e:
+        context.error = str(e)
+
+
+@then("I should get an error about no results provided")
+def step_verify_no_results_error(context: Any) -> None:
+    """Verify no results error."""
+    assert context.error is not None
+    assert "No strategy results" in context.error
+
+
+@given('I have strategy results with "{strategy1}" and "{strategy2}"')
+def step_have_two_strategies(context: Any, strategy1: str, strategy2: str) -> None:
+    """Create strategy results with two strategies."""
+    context.strategy_results = {
+        strategy1: MockStrategyResult([(f"{strategy1}_file.py", 0.8)]),
+        strategy2: MockStrategyResult([(f"{strategy2}_file.py", 0.6)]),
+    }
+
+
+@when('I try to fuse with negative weight for "{strategy}"')
+def step_try_negative_weight(context: Any, strategy: str) -> None:
+    """Try to fuse with negative weight."""
+    try:
+        plan_type_enum = PlanType.CODING
+        context.fusion.fuse_results(
+            plan_type_enum,
+            context.strategy_results,
+            custom_weights={strategy: -0.5},
+        )
+        context.error = None
+    except ValueError as e:
+        context.error = str(e)
+
+
+@then("I should get an error about invalid weight")
+def step_verify_invalid_weight_error(context: Any) -> None:
+    """Verify invalid weight error."""
+    assert context.error is not None
+    assert "positive" in context.error.lower()
+
+
+@when("I normalize weights: {weights}")
+def step_normalize_weights(context: Any, weights: str) -> None:
+    """Normalize weights."""
+    weight_dict = {}
+    for pair in weights.split(", "):
+        strategy, weight = pair.split("=")
+        weight_dict[strategy] = float(weight)
+
+    context.normalized = context.fusion._normalize_weights(
+        weight_dict,
+        weight_dict.keys(),
+    )
+
+
+@then("the normalized weights should be:")
+def step_verify_normalized_weights(context: Any) -> None:
+    """Verify normalized weights (headerless 2-column table)."""
+    for strategy, weight_str in _table_pairs(context.table):
+        expected = float(weight_str)
+        actual = context.normalized[strategy]
+        assert abs(actual - expected) < 0.0001, (
+            f"Weight mismatch for {strategy}: expected {expected}, got {actual}"
+        )
+
+
+@then("the fusion metadata should contain:")
+def step_verify_fusion_metadata(context: Any) -> None:
+    """Verify fusion metadata (headerless 2-column table)."""
+    for key, value in _table_pairs(context.table):
+        if key in ("num_strategies", "num_files"):
+            expected: Any = int(value)
+        else:
+            expected = value
+        actual = context.fused_result.fusion_metadata[key]
+        assert actual == expected, (
+            f"Metadata mismatch for {key}: expected {expected}, got {actual}"
+        )
+
+
+@given('I have registered configuration for plan types: "{plan_types}"')
+def step_register_multiple_configs(context: Any, plan_types: str) -> None:
+    """Register configurations for multiple plan types."""
+    for plan_type_str in _strip_quoted_csv(plan_types):
+        plan_type_enum = PlanType(plan_type_str)
+        strategy = MockStrategy(f"{plan_type_str}_strategy")
+        context.selector.register_strategy(f"{plan_type_str}_strategy", strategy)
+
+        config = AdaptiveStrategyConfig(
+            plan_type=plan_type_enum,
+            primary_strategy=f"{plan_type_str}_strategy",
+        )
+        context.selector.register_config(config)
+
+
+@when("I list all configured plan types")
+def step_list_plan_types(context: Any) -> None:
+    """List all configured plan types."""
+    context.plan_types = context.selector.list_configured_plan_types()
+
+
+@then('I should get plan types: "{plan_types}"')
+def step_verify_plan_types(context: Any, plan_types: str) -> None:
+    """Verify plan types."""
+    expected = [PlanType(pt) for pt in _strip_quoted_csv(plan_types)]
+    assert context.plan_types == expected
+
+
+@when('I get the configuration for plan type "{plan_type}"')
+def step_get_config(context: Any, plan_type: str) -> None:
+    """Get configuration for plan type.
+
+    Stored on ``fetched_config`` because behave reserves ``context.config``
+    for its own runtime configuration object.
+    """
+    plan_type_enum = PlanType(plan_type)
+    context.fetched_config = context.selector.get_config(plan_type_enum)
+
+
+@then('the configuration should have primary strategy "{strategy}"')
+def step_verify_config_primary(context: Any, strategy: str) -> None:
+    """Verify configuration primary strategy."""
+    assert context.fetched_config is not None
+    assert context.fetched_config.primary_strategy == strategy
+
+
+@then("the configuration should be None")
+def step_verify_config_none(context: Any) -> None:
+    """Verify configuration is None."""
+    assert context.fetched_config is None
+
+
+@when("I fuse with selector configuration weights")
+def step_fuse_selector_weights(context: Any) -> None:
+    """Fuse with selector configuration weights."""
+    plan_type_enum = PlanType.CODING
+    context.fused_result = context.fusion.fuse_with_selector(
+        plan_type_enum,
+        context.strategy_results,
+    )
+
+
+@then('the fused result should have file "{file_path}" with score {score}')
+def step_verify_file_score_exact(context: Any, file_path: str, score: str) -> None:
+    """Verify exact file score."""
+    expected = float(score)
+    actual = context.fused_result.get_file_score(file_path)
+    assert actual is not None
+    assert abs(actual - expected) < 0.0001
+
+
+@given('I have strategy results where "{strategy}" has no ranked_files attribute')
+def step_have_result_without_ranked_files(context: Any, strategy: str) -> None:
+    """Create strategy result without ranked_files."""
+    context.strategy_results = {
+        "semantic": MockStrategyResult([("file1.py", 0.8)]),
+        strategy: object(),  # Object without ranked_files
+    }
+
+
+@then("the fusion should skip the strategy without ranked_files")
+def step_verify_skip_no_ranked_files(context: Any) -> None:
+    """Verify strategy without ranked_files is skipped."""
+    assert context.fused_result is not None
+    assert len(context.fused_result.ranked_files) > 0
+
+
+@when("I try to create a strategy weight with negative weight")
+def step_try_negative_strategy_weight(context: Any) -> None:
+    """Try to create strategy weight with negative weight."""
+    try:
+        StrategyWeight(strategy_name="test", weight=-0.5)
+        context.error = None
+    except ValueError as e:
+        context.error = str(e)
+
+
+@when("I try to create adaptive strategy config without primary strategy")
+def step_try_config_no_primary(context: Any) -> None:
+    """Try to create config without primary strategy."""
+    try:
+        AdaptiveStrategyConfig(
+            plan_type=PlanType.CODING,
+            primary_strategy="",
+        )
+        context.error = None
+    except ValueError as e:
+        context.error = str(e)
+
+
+@then("I should get an error about missing primary strategy")
+def step_verify_missing_primary_error(context: Any) -> None:
+    """Verify missing primary strategy error."""
+    assert context.error is not None
+    assert "primary_strategy" in context.error
+
+
+@then('I should have plan types: "{plan_types}"')
+def step_verify_plan_type_enum(context: Any, plan_types: str) -> None:
+    """Verify plan type enumeration."""
+    expected = _strip_quoted_csv(plan_types)
+    actual = [pt.value for pt in PlanType]
+    assert actual == expected, f"PlanType mismatch: expected {expected}, got {actual}"
+
+
+@given('I have registered a strategy named "{name}"')
+def step_have_registered_strategy(context: Any, name: str) -> None:
+    """Register a strategy by name."""
+    strategy = MockStrategy(name)
+    context.selector.register_strategy(name, strategy)
+
+
+@when('I try to select a strategy for unconfigured plan type "{plan_type}"')
+def step_try_select_unconfigured(context: Any, plan_type: str) -> None:
+    """Try to select a strategy when no configuration exists for plan_type."""
+    try:
+        context.selector.select_strategy(PlanType(plan_type))
+        context.error = None
+    except ValueError as e:
+        context.error = str(e)
+
+
+@when('I try to select all strategies for unconfigured plan type "{plan_type}"')
+def step_try_select_all_unconfigured(context: Any, plan_type: str) -> None:
+    """Try to select all strategies when no configuration exists for plan_type."""
+    try:
+        context.selector.select_strategies(PlanType(plan_type))
+        context.error = None
+    except ValueError as e:
+        context.error = str(e)
+
+
+@when('I try to fuse results for unconfigured plan type "{plan_type}"')
+def step_try_fuse_unconfigured(context: Any, plan_type: str) -> None:
+    """Try to fuse results when no configuration exists for plan_type."""
+    try:
+        context.fusion.fuse_results(PlanType(plan_type), context.strategy_results)
+        context.error = None
+    except ValueError as e:
+        context.error = str(e)
+
+
+@when('I try to fuse with selector for unconfigured plan type "{plan_type}"')
+def step_try_fuse_with_selector_unconfigured(context: Any, plan_type: str) -> None:
+    """Try fuse_with_selector when no configuration exists for plan_type."""
+    try:
+        context.fusion.fuse_with_selector(PlanType(plan_type), context.strategy_results)
+        context.error = None
+    except ValueError as e:
+        context.error = str(e)
+
+
+@then("I should get an error about no configuration")
+def step_verify_no_configuration_error(context: Any) -> None:
+    """Verify error mentions missing plan-type configuration."""
+    assert context.error is not None
+    assert "No configuration" in context.error
+
+
+@when('I create a strategy weight named "{name}" with weight {weight:f}')
+def step_create_valid_strategy_weight(context: Any, name: str, weight: float) -> None:
+    """Create a StrategyWeight with a valid positive weight."""
+    context.strategy_weight = StrategyWeight(strategy_name=name, weight=weight)
+
+
+@then('the strategy weight should have name "{name}" and weight {weight:f}')
+def step_verify_strategy_weight(context: Any, name: str, weight: float) -> None:
+    """Verify created StrategyWeight fields."""
+    assert context.strategy_weight.strategy_name == name
+    assert abs(context.strategy_weight.weight - weight) < 0.0001
+
+
+@given(
+    'I have registered configuration for plan type "{plan_type}" with primary strategy "{strategy}"'
+)
+def step_have_registered_config(context: Any, plan_type: str, strategy: str) -> None:
+    """Register configuration for plan type, auto-registering the strategy."""
+    plan_type_enum = PlanType(plan_type)
+    if strategy not in context.selector.list_registered_strategies():
+        context.selector.register_strategy(strategy, MockStrategy(strategy))
+    config = AdaptiveStrategyConfig(
+        plan_type=plan_type_enum,
+        primary_strategy=strategy,
+    )
+    context.selector.register_config(config)
+
+
+@given('I have registered configuration for plan type "{plan_type}"')
+def step_have_registered_config_no_strategy(context: Any, plan_type: str) -> None:
+    """Register configuration for plan type with a default strategy."""
+    plan_type_enum = PlanType(plan_type)
+    strategy_name = f"{plan_type}_default"
+    strategy = MockStrategy(strategy_name)
+    context.selector.register_strategy(strategy_name, strategy)
+    config = AdaptiveStrategyConfig(
+        plan_type=plan_type_enum,
+        primary_strategy=strategy_name,
+    )
+    context.selector.register_config(config)
diff --git a/src/cleveragents/domain/models/acms/adaptive_selector.py b/src/cleveragents/domain/models/acms/adaptive_selector.py
new file mode 100644
index 000000000..e1ce109ca
--- /dev/null
+++ b/src/cleveragents/domain/models/acms/adaptive_selector.py
@@ -0,0 +1,340 @@
+"""Adaptive context strategy selector and context fusion implementation.
+
+This module provides intelligent strategy selection based on plan type and
+context fusion to combine results from multiple strategies with configurable weights.
+"""
+
+from __future__ import annotations
+
+from enum import StrEnum
+from typing import Any
+
+from pydantic import BaseModel, Field, field_validator
+
+from cleveragents.domain.models.acms.strategy import ContextStrategy
+
+
+class PlanType(StrEnum):
+    """Enumeration of plan types for strategy selection."""
+
+    CODING = "coding"
+    ANALYSIS = "analysis"
+    DOCUMENTATION = "documentation"
+    REFACTORING = "refactoring"
+    TESTING = "testing"
+    DEBUGGING = "debugging"
+    UNKNOWN = "unknown"
+
+
+class StrategyWeight(BaseModel):
+    """Configuration for a strategy weight in fusion."""
+
+    strategy_name: str
+    weight: float = 1.0
+    enabled: bool = True
+
+    @field_validator("weight")
+    @classmethod
+    def _check_weight_positive(cls, v: float) -> float:
+        if v <= 0:
+            raise ValueError(f"Weight must be positive, got {v}")
+        return v
+
+
+class AdaptiveStrategyConfig(BaseModel):
+    """Configuration for adaptive strategy selection."""
+
+    plan_type: PlanType
+    primary_strategy: str
+    fallback_strategies: list[str] = Field(default_factory=list)
+    fusion_weights: dict[str, float] = Field(default_factory=dict)
+    use_fusion: bool = False
+
+    @field_validator("primary_strategy")
+    @classmethod
+    def _check_primary_strategy(cls, v: str) -> str:
+        if not v:
+            raise ValueError("primary_strategy must be specified")
+        return v
+
+
+class FusedResult(BaseModel):
+    """Result of context fusion combining multiple strategy results."""
+
+    ranked_files: list[tuple[str, float]]  # (file_path, combined_score)
+    # strategy -> [(file, score)]
+    strategy_contributions: dict[str, list[tuple[str, float]]]
+    fusion_metadata: dict[str, Any] = Field(default_factory=dict)
+
+    def get_top_files(self, limit: int = 10) -> list[str]:
+        """Get top N files from fused results.
+
+        Args:
+            limit: Maximum number of files to return
+
+        Returns:
+            List of file paths sorted by combined score (descending)
+        """
+        return [file_path for file_path, _ in self.ranked_files[:limit]]
+
+    def get_file_score(self, file_path: str) -> float | None:
+        """Get combined score for a specific file.
+
+        Args:
+            file_path: Path to the file
+
+        Returns:
+            Combined score or None if file not in results
+        """
+        for path, score in self.ranked_files:
+            if path == file_path:
+                return score
+        return None
+
+
+class AdaptiveContextSelector:
+    """Selects the best context strategy based on plan type and configuration."""
+
+    def __init__(self) -> None:
+        """Initialize the adaptive selector."""
+        self._strategy_registry: dict[str, ContextStrategy] = {}
+        self._config_map: dict[PlanType, AdaptiveStrategyConfig] = {}
+
+    def register_strategy(self, name: str, strategy: ContextStrategy) -> None:
+        """Register a context strategy.
+
+        Args:
+            name: Unique name for the strategy
+            strategy: The strategy implementation
+
+        Raises:
+            ValueError: If strategy name is already registered
+        """
+        if name in self._strategy_registry:
+            raise ValueError(f"Strategy '{name}' is already registered")
+        self._strategy_registry[name] = strategy
+
+    def register_config(self, config: AdaptiveStrategyConfig) -> None:
+        """Register configuration for a plan type.
+
+        Args:
+            config: Configuration for strategy selection
+
+        Raises:
+            ValueError: If primary strategy is not registered
+        """
+        if config.primary_strategy not in self._strategy_registry:
+            raise ValueError(
+                f"Primary strategy '{config.primary_strategy}' is not registered"
+            )
+
+        for fallback in config.fallback_strategies:
+            if fallback not in self._strategy_registry:
+                raise ValueError(f"Fallback strategy '{fallback}' is not registered")
+
+        self._config_map[config.plan_type] = config
+
+    def select_strategy(self, plan_type: PlanType) -> ContextStrategy:
+        """Select the best strategy for a plan type.
+
+        Args:
+            plan_type: The type of plan
+
+        Returns:
+            The selected strategy
+
+        Raises:
+            ValueError: If no configuration exists for plan type
+        """
+        if plan_type not in self._config_map:
+            raise ValueError(f"No configuration for plan type: {plan_type}")
+
+        config = self._config_map[plan_type]
+        return self._strategy_registry[config.primary_strategy]
+
+    def select_strategies(self, plan_type: PlanType) -> list[ContextStrategy]:
+        """Select all applicable strategies for a plan type (primary + fallbacks).
+
+        Args:
+            plan_type: The type of plan
+
+        Returns:
+            List of strategies in priority order
+
+        Raises:
+            ValueError: If no configuration exists for plan type
+        """
+        if plan_type not in self._config_map:
+            raise ValueError(f"No configuration for plan type: {plan_type}")
+
+        config = self._config_map[plan_type]
+        strategies: list[ContextStrategy] = [
+            self._strategy_registry[config.primary_strategy]
+        ]
+
+        for fallback_name in config.fallback_strategies:
+            strategies.append(self._strategy_registry[fallback_name])
+
+        return strategies
+
+    def get_config(self, plan_type: PlanType) -> AdaptiveStrategyConfig | None:
+        """Get configuration for a plan type.
+
+        Args:
+            plan_type: The type of plan
+
+        Returns:
+            Configuration or None if not found
+        """
+        return self._config_map.get(plan_type)
+
+    def list_registered_strategies(self) -> list[str]:
+        """List all registered strategy names.
+
+        Returns:
+            List of strategy names
+        """
+        return list(self._strategy_registry.keys())
+
+    def list_configured_plan_types(self) -> list[PlanType]:
+        """List all plan types with configurations.
+
+        Returns:
+            List of configured plan types
+        """
+        return list(self._config_map.keys())
+
+
+class ContextFusion:
+    """Combines results from multiple context strategies with configurable weights."""
+
+    def __init__(self, selector: AdaptiveContextSelector) -> None:
+        """Initialize context fusion.
+
+        Args:
+            selector: The adaptive selector to use for strategy selection
+        """
+        self._selector = selector
+
+    def fuse_results(
+        self,
+        plan_type: PlanType,
+        strategy_results: dict[str, Any],
+        custom_weights: dict[str, float] | None = None,
+    ) -> FusedResult:
+        """Fuse results from multiple strategies.
+
+        Args:
+            plan_type: The type of plan
+            strategy_results: Dictionary mapping strategy names to their results
+            custom_weights: Optional custom weights for strategies
+
+        Returns:
+            Fused result with ranked files
+
+        Raises:
+            ValueError: If no results provided or invalid weights
+        """
+        if not strategy_results:
+            raise ValueError("No strategy results provided")
+
+        config = self._selector.get_config(plan_type)
+        if not config:
+            raise ValueError(f"No configuration for plan type: {plan_type}")
+
+        # Determine weights to use
+        weights = custom_weights or config.fusion_weights or {}
+
+        # Normalize weights
+        normalized_weights = self._normalize_weights(weights, strategy_results.keys())
+
+        # Collect all files and their scores from each strategy
+        # file -> [(strategy, score)]
+        file_scores: dict[str, list[tuple[str, float]]] = {}
+        strategy_contributions: dict[str, list[tuple[str, float]]] = {}
+
+        for strategy_name, result in strategy_results.items():
+            strategy_contributions[strategy_name] = []
+
+            if not hasattr(result, "ranked_files"):
+                continue
+
+            weight = normalized_weights.get(strategy_name, 1.0)
+
+            for file_path, score in result.ranked_files:
+                if file_path not in file_scores:
+                    file_scores[file_path] = []
+
+                weighted_score = score * weight
+                file_scores[file_path].append((strategy_name, weighted_score))
+                strategy_contributions[strategy_name].append(
+                    (file_path, weighted_score)
+                )
+
+        # Combine scores for each file
+        combined_scores: list[tuple[str, float]] = []
+        for file_path, scores in file_scores.items():
+            combined_score = sum(score for _, score in scores)
+            combined_scores.append((file_path, combined_score))
+
+        # Sort by combined score (descending)
+        ranked_files = sorted(combined_scores, key=lambda x: x[1], reverse=True)
+
+        return FusedResult(
+            ranked_files=ranked_files,
+            strategy_contributions=strategy_contributions,
+            fusion_metadata={
+                "plan_type": plan_type.value,
+                "num_strategies": len(strategy_results),
+                "num_files": len(ranked_files),
+                "weights_used": normalized_weights,
+            },
+        )
+
+    def _normalize_weights(
+        self, weights: dict[str, float], strategy_names: Any
+    ) -> dict[str, float]:
+        """Normalize weights to sum to 1.0.
+
+        Args:
+            weights: Raw weights dictionary
+            strategy_names: Available strategy names
+
+        Returns:
+            Normalized weights dictionary
+        """
+        if not weights:
+            # Equal weights for all strategies — weight 1.0 each. Test
+            # scenarios in features/adaptive_context_strategy.feature pin
+            # the "equal weights" semantics to "no scaling" (sum-of-scores
+            # behaviour), not 1/N normalisation.
+            return {name: 1.0 for name in strategy_names}
+
+        # Validate all weights are positive
+        for weight in weights.values():
+            if weight <= 0:
+                raise ValueError(f"All weights must be positive, got {weight}")
+
+        # Normalize to sum to 1.0
+        total = sum(weights.values())
+        return {name: weight / total for name, weight in weights.items()}
+
+    def fuse_with_selector(
+        self,
+        plan_type: PlanType,
+        strategy_results: dict[str, Any],
+    ) -> FusedResult:
+        """Fuse results using weights from selector configuration.
+
+        Args:
+            plan_type: The type of plan
+            strategy_results: Dictionary mapping strategy names to their results
+
+        Returns:
+            Fused result with ranked files
+        """
+        config = self._selector.get_config(plan_type)
+        if not config:
+            raise ValueError(f"No configuration for plan type: {plan_type}")
+
+        return self.fuse_results(plan_type, strategy_results, config.fusion_weights)