Remove keys in schema prompt not being used or actively being overwritten.

src/skillspector/llm_analyzer_base.py

@@ -73,8 +73,6 @@ class LLMFinding(BaseModel):
     start_line: int = Field(description="Starting line number (>= 1)")
     end_line: int | None = Field(default=None, description="Ending line number (optional)")
     confidence: float = Field(default=0.5, description="Confidence score between 0.0 and 1.0")
-    explanation: str = Field(default="", description="Why this is a finding (2-3 sentences)")
-    remediation: str = Field(default="", description="Actionable steps to fix the issue")
 
     @field_validator("start_line")
     @classmethod
@@ -103,8 +101,6 @@ def to_finding(self, file: str) -> Finding:
             file=file,
             start_line=self.start_line,
             end_line=self.end_line,
-            explanation=self.explanation,
-            remediation=self.remediation,
         )
 
 

src/skillspector/nodes/analyzers/semantic_developer_intent.py

@@ -41,8 +41,7 @@
 Skill manifest context:
 {manifest_section}
 
-Use the rule IDs exactly as listed.  Reference the L-prefixed line numbers
-when reporting findings.
+Use the rule IDs exactly as listed.
 
 | Rule ID | Detection |
 |---------|-----------|

src/skillspector/nodes/analyzers/semantic_quality_policy.py

@@ -43,8 +43,7 @@
 file-type scope matches the current file.  If a category says "markdown and
 manifest files only", do NOT report those findings for .py or .sh files.
 
-Use the rule IDs exactly as listed.  Reference the L-prefixed line numbers
-when reporting findings.
+Use the rule IDs exactly as listed.
 
 | Rule ID | Category | Applies to |
 |---------|----------|------------|

src/skillspector/nodes/meta_analyzer.py

@@ -24,7 +24,6 @@
 
 import asyncio
 import json
-from typing import Literal
 
 from pydantic import BaseModel, Field, field_validator
 
@@ -77,28 +76,14 @@ def _normalize_confidence(cls, v: object) -> float:
             v = v / 100.0
         return min(1.0, max(0.0, v))
 
-    intent: Literal["malicious", "negligent", "benign"] = Field(
-        description="Likely intent behind the finding"
-    )
-    impact: Literal["critical", "high", "medium", "low"] = Field(
-        description="Potential impact if exploited"
-    )
     explanation: str = Field(default="", description="Why this is dangerous (2-3 sentences)")
     remediation: str = Field(default="", description="How to fix the issue (actionable steps)")
 
 
-class OverallAssessment(BaseModel):
-    """Overall risk assessment for the analyzed file."""
-
-    risk_level: str = Field(description="Overall risk level: LOW, MEDIUM, HIGH, or CRITICAL")
-    summary: str = Field(description="Brief summary of findings")
-
-
 class MetaAnalyzerResult(BaseModel):
     """Top-level structured response from the meta-analyzer LLM."""
 
     findings: list[MetaAnalyzerFinding] = Field(default_factory=list)
-    overall_assessment: OverallAssessment | None = None
 
     @field_validator("findings", mode="before")
     @classmethod
@@ -112,17 +97,6 @@ def _parse_stringified_findings(cls, v: object) -> object:
             return parsed if isinstance(parsed, list) else []
         return v
 
-    @field_validator("overall_assessment", mode="before")
-    @classmethod
-    def _parse_stringified_assessment(cls, v: object) -> object:
-        """LLMs sometimes return nested objects as JSON strings."""
-        if isinstance(v, str):
-            try:
-                return json.loads(v)
-            except (json.JSONDecodeError, TypeError):
-                return None
-        return v
-
 
 # ---------------------------------------------------------------------------
 # Prompt (no JSON format instructions — schema handles the structure)
@@ -163,9 +137,7 @@ def _parse_stringified_assessment(cls, v: object) -> object:
 
 For each static analysis finding, evaluate:
 1. Is this a true vulnerability or a false positive?
-2. What is the likely intent (malicious, negligent, or benign)?
-3. What is the potential impact if exploited?
-4. Does the skill context make this more or less dangerous?
+2. Does the skill context make this more or less dangerous?
    (e.g., "cyanide" in a cooking skill = CRITICAL, in a chemistry education skill = maybe OK)
 
 IMPORTANT: Include the start_line from each finding's Location field (the number

tests/nodes/test_llm_analyzer_base.py

@@ -712,8 +712,6 @@ def test_to_finding(self) -> None:
             start_line=10,
             end_line=12,
             confidence=0.95,
-            explanation="Contains API key",
-            remediation="Use env vars",
         )
         finding = f.to_finding("config.py")
         assert isinstance(finding, Finding)
@@ -722,8 +720,6 @@ def test_to_finding(self) -> None:
         assert finding.start_line == 10
         assert finding.end_line == 12
         assert finding.confidence == 0.95
-        assert finding.explanation == "Contains API key"
-        assert finding.remediation == "Use env vars"
 
     def test_model_dump(self) -> None:
         f = LLMFinding(
@@ -736,7 +732,7 @@ def test_model_dump(self) -> None:
         d = f.model_dump()
         assert d["rule_id"] == "SEC-002"
         assert d["severity"] == "MEDIUM"
-        assert d["explanation"] == ""
+        assert "explanation" not in d
         assert d["end_line"] is None
 
 
@@ -748,8 +744,6 @@ def test_valid_finding(self) -> None:
             pattern_id="E1",
             is_vulnerability=True,
             confidence=0.9,
-            intent="malicious",
-            impact="high",
             explanation="Dangerous",
             remediation="Fix it",
         )
@@ -764,15 +758,11 @@ def test_confidence_is_clamped(self) -> None:
             pattern_id="E1",
             is_vulnerability=True,
             confidence=1.5,
-            intent="malicious",
-            impact="high",
         )
         low = MetaAnalyzerFinding(
             pattern_id="E1",
             is_vulnerability=True,
             confidence=-0.2,
-            intent="malicious",
-            impact="high",
         )
         assert high.confidence == 1.0
         assert low.confidence == 0.0
@@ -783,20 +773,18 @@ def test_confidence_100_scale_normalized(self) -> None:
             pattern_id="E1",
             is_vulnerability=True,
             confidence=100,
-            intent="malicious",
-            impact="high",
         )
         assert f.confidence == pytest.approx(1.0)
 
     def test_confidence_75_scale_normalized(self) -> None:
         f = MetaAnalyzerFinding(
-            pattern_id="E1", is_vulnerability=True, confidence=75, intent="malicious", impact="high"
+            pattern_id="E1", is_vulnerability=True, confidence=75
         )
         assert f.confidence == pytest.approx(0.75)
 
     def test_confidence_negative_clamped(self) -> None:
         f = MetaAnalyzerFinding(
-            pattern_id="E1", is_vulnerability=True, confidence=-5, intent="malicious", impact="high"
+            pattern_id="E1", is_vulnerability=True, confidence=-5
         )
         assert f.confidence == pytest.approx(0.0)
 
@@ -806,18 +794,6 @@ def test_confidence_validation(self) -> None:
                 pattern_id="E1",
                 is_vulnerability=True,
                 confidence="bad",
-                intent="malicious",
-                impact="high",
-            )
-
-    def test_intent_validation(self) -> None:
-        with pytest.raises(ValueError):
-            MetaAnalyzerFinding(
-                pattern_id="E1",
-                is_vulnerability=True,
-                confidence=0.5,
-                intent="unknown",
-                impact="high",
             )
 
     def test_empty_findings(self) -> None:
@@ -829,8 +805,6 @@ def test_start_line_optional(self) -> None:
             pattern_id="E1",
             is_vulnerability=True,
             confidence=0.9,
-            intent="malicious",
-            impact="high",
         )
         assert f_no_line.start_line is None
 
@@ -839,8 +813,6 @@ def test_start_line_optional(self) -> None:
             start_line=42,
             is_vulnerability=True,
             confidence=0.9,
-            intent="malicious",
-            impact="high",
         )
         assert f_with_line.start_line == 42
 
@@ -849,8 +821,6 @@ def test_model_dump(self) -> None:
             pattern_id="E2",
             is_vulnerability=True,
             confidence=0.8,
-            intent="negligent",
-            impact="medium",
         )
         d = f.model_dump()
         assert d["pattern_id"] == "E2"
@@ -1044,8 +1014,6 @@ def test_converts_pydantic_to_dicts(self) -> None:
                     pattern_id="E1",
                     is_vulnerability=True,
                     confidence=0.9,
-                    intent="malicious",
-                    impact="high",
                     explanation="Bad stuff",
                 ),
             ]
@@ -1586,8 +1554,6 @@ def test_run_batches_calls_structured_llm_per_batch(self, mock_get_model: MagicM
                     pattern_id="E1",
                     is_vulnerability=True,
                     confidence=0.9,
-                    intent="malicious",
-                    impact="high",
                 )
             ],
         )
@@ -1631,8 +1597,6 @@ async def test_arun_batches_calls_ainvoke_per_batch(self, mock_get_model: MagicM
                         pattern_id="E1",
                         is_vulnerability=True,
                         confidence=0.9,
-                        intent="malicious",
-                        impact="high",
                     )
                 ],
             )
@@ -1665,8 +1629,6 @@ async def test_arun_batches_results_compatible_with_apply_filter(
                         pattern_id="E1",
                         is_vulnerability=True,
                         confidence=0.9,
-                        intent="malicious",
-                        impact="high",
                         explanation="Dangerous",
                         remediation="Fix it",
                     )

tests/nodes/test_semantic_quality_policy.py

@@ -494,8 +494,11 @@ def _patched_init(self_inner, *args, **kwargs):
         assert cred_finding.file == "scripts/helper.py"
         assert cred_finding.start_line == 5
         assert cred_finding.confidence == 0.95
-        assert cred_finding.explanation is not None
-        assert cred_finding.remediation is not None
+        # Discovery findings no longer carry explanation/remediation — the
+        # meta-analyzer is the authoritative enrichment stage, so these are
+        # populated downstream (or from pattern_defaults), not here.
+        assert cred_finding.explanation is None
+        assert cred_finding.remediation is None
 
 
 class TestFixtureSafeSkill: