fix(review): extract shared filter_pruning_false_positives helper

Author: Trecek

src/autoskillit/recipe/_api.py

@@ -63,6 +63,7 @@
 from autoskillit.recipe._rule_helpers import (
     _is_failure_sentinel_value,
     extract_sentinel_json_blocks,
+    filter_pruning_false_positives,
 )
 from autoskillit.recipe.contracts import (
     check_contract_staleness,
@@ -430,14 +431,9 @@ def load_and_validate(
             t0 = _t("semantic_rules", t0, name)
 
             if _skip_resolutions and any(v is False for v in _skip_resolutions.values()):
-                _pre_prune_finding_keys: frozenset[tuple[str, str, str]] = frozenset(
-                    (f.rule, f.step_name, f.message) for f in _pre_prune_findings
+                semantic_findings = filter_pruning_false_positives(
+                    semantic_findings, _pre_prune_findings
                 )
-                semantic_findings = [
-                    f
-                    for f in semantic_findings
-                    if (f.rule, f.step_name, f.message) in _pre_prune_finding_keys
-                ]
                 semantic_suggestions = findings_to_dicts(semantic_findings)
 
             _suppressed = suppressed or []

src/autoskillit/recipe/_api_listing.py

@@ -9,6 +9,7 @@
 from autoskillit.recipe._analysis import make_validation_context
 from autoskillit.recipe._recipe_composition import _prune_skipped_steps
 from autoskillit.recipe._recipe_ingredients import RecipeListItem
+from autoskillit.recipe._rule_helpers import filter_pruning_false_positives
 from autoskillit.recipe.contracts import load_recipe_card, validate_recipe_cards
 from autoskillit.recipe.io import (
     RecipeInfo,
@@ -146,14 +147,7 @@ def validate_from_path(
     report = ctx.dataflow
     semantic_findings = run_semantic_rules(ctx)
     if _skip_resolutions and any(v is False for v in _skip_resolutions.values()):
-        _pre_prune_finding_keys: frozenset[tuple[str, str, str]] = frozenset(
-            (f.rule, f.step_name, f.message) for f in _pre_prune_findings
-        )
-        semantic_findings = [
-            f
-            for f in semantic_findings
-            if (f.rule, f.step_name, f.message) in _pre_prune_finding_keys
-        ]
+        semantic_findings = filter_pruning_false_positives(semantic_findings, _pre_prune_findings)
 
     quality = build_quality_dict(report)
     semantic = findings_to_dicts(semantic_findings)

src/autoskillit/recipe/_rule_helpers.py

@@ -15,6 +15,7 @@
 
 if TYPE_CHECKING:
     from autoskillit.recipe._contracts_types import SkillContract
+    from autoskillit.recipe.registry import RuleFinding
     from autoskillit.recipe.schema import CampaignDispatch, Recipe, RecipeStep
 
 logger = get_logger(__name__)
@@ -268,3 +269,19 @@ def _identify_optional_output_fields(contract: SkillContract) -> set[str]:
         if m and m.group(1) in output_names:
             optional.add(m.group(1))
     return optional
+
+
+def filter_pruning_false_positives(
+    post_prune_findings: list[RuleFinding],
+    pre_prune_findings: list[RuleFinding],
+) -> list[RuleFinding]:
+    """Keep only post-prune findings that also appeared pre-prune.
+
+    Graph-aware rules (dead-output, capture-inversion) produce false positives
+    when pruning changes step-graph reachability. Intersecting with the
+    pre-prune baseline suppresses findings introduced by pruning.
+    """
+    pre_prune_keys: frozenset[tuple[str, str, str]] = frozenset(
+        (f.rule, f.step_name, f.message) for f in pre_prune_findings
+    )
+    return [f for f in post_prune_findings if (f.rule, f.step_name, f.message) in pre_prune_keys]