Refactor scoring hygiene and profile constants

src/analyzers/activity.py

@@ -17,7 +17,6 @@
 
 class ActivityAnalyzer(BaseAnalyzer):
     name = "activity"
-    weight = 0.15
 
     def analyze(
         self,

src/analyzers/base.py

@@ -14,7 +14,6 @@ class BaseAnalyzer(ABC):
     """Abstract base for all repo analyzers."""
 
     name: str
-    weight: float
 
     @abstractmethod
     def analyze(

src/analyzers/cicd.py

@@ -22,7 +22,6 @@
 
 class CicdAnalyzer(BaseAnalyzer):
     name = "cicd"
-    weight = 0.10
 
     def analyze(
         self,

src/analyzers/code_quality.py

@@ -50,7 +50,6 @@
 
 class CodeQualityAnalyzer(BaseAnalyzer):
     name = "code_quality"
-    weight = 0.15
 
     def analyze(
         self,

src/analyzers/community_profile.py

@@ -32,7 +32,6 @@ class CommunityProfileAnalyzer(BaseAnalyzer):
     """
 
     name = "community_profile"
-    weight = 0.03
 
     def analyze(
         self,

src/analyzers/completeness.py

@@ -52,7 +52,6 @@
 
 class DocumentationAnalyzer(BaseAnalyzer):
     name = "documentation"
-    weight = 0.05
 
     def analyze(
         self,
@@ -108,7 +107,6 @@ def analyze(
 
 class BuildReadinessAnalyzer(BaseAnalyzer):
     name = "build_readiness"
-    weight = 0.05
 
     def analyze(
         self,

src/analyzers/dependencies.py

@@ -41,7 +41,6 @@
 
 class DependenciesAnalyzer(BaseAnalyzer):
     name = "dependencies"
-    weight = 0.10
 
     def cache_inputs_hash(
         self,

src/analyzers/interest.py

@@ -35,7 +35,6 @@ class InterestAnalyzer(BaseAnalyzer):
     """
 
     name = "interest"
-    weight = 0.0  # Not part of completeness score — separate axis
 
     def analyze(
         self,

src/analyzers/readme.py

@@ -36,7 +36,6 @@
 
 class ReadmeAnalyzer(BaseAnalyzer):
     name = "readme"
-    weight = 0.15
 
     def cache_inputs_hash(
         self,

src/analyzers/security.py

@@ -112,7 +112,6 @@ class SecurityAnalyzer(BaseAnalyzer):
     """Scans for security surface issues — exposed secrets, dangerous files, missing config."""
 
     name = "security"
-    weight = 0.0  # Advisory dimension, not part of completeness score
 
     def analyze(
         self,

src/analyzers/structure.py

@@ -42,7 +42,6 @@
 
 class StructureAnalyzer(BaseAnalyzer):
     name = "structure"
-    weight = 0.10
 
     def cache_inputs_hash(
         self,

src/analyzers/testing.py

@@ -21,7 +21,6 @@
 
 class TestingAnalyzer(BaseAnalyzer):
     name = "testing"
-    weight = 0.15
 
     def analyze(
         self,

src/app/run_audit.py

@@ -53,6 +53,17 @@
 DEFAULT_ANALYSIS_WORKERS = 1
 MAX_ANALYSIS_WORKERS = 8
 DEFAULT_PORTFOLIO_WORKSPACE = Path.home() / "Projects"
+_SCORING_PROFILE_RESERVED_KEYS = frozenset(
+    {"stale_threshold_days", "grade_thresholds", "completeness_tiers"}
+)
+
+
+class ScoringProfile(dict[str, float]):
+    """Flat profile weights plus optional scoring-constant overrides."""
+
+    def __init__(self, weights: dict[str, float], *, overrides: dict[str, object]) -> None:
+        super().__init__(weights)
+        self.overrides = overrides
 CLI_MODE_GUIDE = """GitHub portfolio operating system with four product modes:
   First Run     setup, baseline creation, first workbook, first control-center read
   Weekly Review normal workbook-first operator loop
@@ -545,6 +556,7 @@ def _analyze_one(repo_meta: RepoMetadata, repo_path: Path) -> RepoAudit:
             repo_path=repo_path,
             portfolio_lang_freq=portfolio_lang_freq,
             custom_weights=custom_weights,
+            scoring_profile=getattr(custom_weights, "overrides", None),
             github_client=worker_client,
             scorecard_enabled=args.scorecard,
             security_offline=args.security_offline,
@@ -1646,7 +1658,13 @@ def _load_scoring_profile(profile_name: str | None) -> tuple[dict[str, float] |
     profile_path = Path(f"config/scoring-profiles/{profile_name}.json")
     if profile_path.is_file():
         print_info(f"Using scoring profile: {profile_name}")
-        return json.loads(profile_path.read_text()), normalized
+        profile = json.loads(profile_path.read_text())
+        overrides = {
+            key: profile.pop(key)
+            for key in _SCORING_PROFILE_RESERVED_KEYS
+            if key in profile
+        }
+        return ScoringProfile(profile, overrides=overrides), normalized
 
     print_warning(f"Scoring profile not found: {profile_path}")
     return None, normalized

src/excel_action_items_helpers.py

@@ -4,6 +4,8 @@
 
 from typing import Any
 
+from src.scoring_dimensions import display_dimension
+
 ACTION_ITEMS_HEADERS = ["#", "Repo", "Action", "Impact", "Effort", "Dimension"]
 EFFORT_MAP = {
     "readme": "Low",
@@ -42,11 +44,13 @@ def collect_action_items(data: dict[str, Any]) -> list[dict[str, Any]]:
             for result in audit.get("analyzer_results", [])
             if result["dimension"] != "interest"
         }
-        for dimension, score in sorted(dimension_scores.items(), key=lambda item: item[1])[:2]:
+        for dimension, score in sorted(
+            dimension_scores.items(), key=lambda item: item[1]
+        )[:2]:
             actions.append(
                 {
                     "repo": audit["metadata"]["name"],
-                    "action": f"Improve {dimension} (currently {score:.1f})",
+                    "action": f"Improve {display_dimension(dimension)} (currently {score:.1f})",
                     "impact": f"Close {gap:.3f} gap to {next_tier}",
                     "effort": EFFORT_MAP.get(dimension, "Med"),
                     "dimension": dimension,
@@ -69,7 +73,9 @@ def collect_action_items(data: dict[str, Any]) -> list[dict[str, Any]]:
             )
 
     effort_order = {"Low": 0, "Med": 1, "High": 2}
-    actions.sort(key=lambda action: (effort_order.get(action["effort"], 1), action["gap"]))
+    actions.sort(
+        key=lambda action: (effort_order.get(action["effort"], 1), action["gap"])
+    )
 
     seen: set[tuple[str, str]] = set()
     unique: list[dict[str, Any]] = []
@@ -102,7 +108,9 @@ def write_action_items_sections(
     ws.freeze_panes = "A5"
 
     if content["sprint_rows"]:
-        ws.cell(row=3, column=1, value="Weekly Sprint (Top 5 Low-Effort)").font = section_font
+        ws.cell(
+            row=3, column=1, value="Weekly Sprint (Top 5 Low-Effort)"
+        ).font = section_font
         for col, header in enumerate(ACTION_ITEMS_HEADERS, 1):
             ws.cell(row=4, column=col, value=header)
         style_header_row(ws, 4, len(ACTION_ITEMS_HEADERS))
@@ -111,7 +119,9 @@ def write_action_items_sections(
                 style_data_cell(ws.cell(row=row_number, column=col, value=value))
 
     full_start = len(content["sprint_rows"]) + 7
-    ws.cell(row=full_start, column=1, value="All Actions (Prioritized)").font = section_font
+    ws.cell(
+        row=full_start, column=1, value="All Actions (Prioritized)"
+    ).font = section_font
     full_start += 1
     for col, header in enumerate(ACTION_ITEMS_HEADERS, 1):
         ws.cell(row=full_start, column=col, value=header)
@@ -136,7 +146,7 @@ def _build_action_rows(actions: list[dict[str, Any]]) -> list[list[Any]]:
             action["action"],
             action["impact"],
             action["effort"],
-            action["dimension"],
+            display_dimension(action["dimension"]),
         ]
         for index, action in enumerate(actions, start=1)
     ]

src/excel_all_repos_helpers.py

@@ -9,6 +9,7 @@
 from openpyxl.styles import Alignment, Font
 from openpyxl.utils import get_column_letter
 from openpyxl.worksheet.datavalidation import DataValidation
+from src.scoring_dimensions import display_dimension
 
 ALL_REPOS_HEADERS = [
     "Repo",
@@ -158,7 +159,7 @@ def _build_biggest_drag(audit: dict[str, Any]) -> str:
     if not dimension_scores:
         return "—"
     worst_dimension = min(dimension_scores, key=dimension_scores.get)
-    return f"{worst_dimension} ({dimension_scores[worst_dimension]:.1f})"
+    return f"{display_dimension(worst_dimension)} ({dimension_scores[worst_dimension]:.1f})"
 
 
 def _build_grade_reason(audit: dict[str, Any]) -> str:
@@ -174,8 +175,8 @@ def _build_grade_reason(audit: dict[str, Any]) -> str:
     if len(weakest_dimensions) < 2:
         return grade
     return (
-        f"{grade}: {weakest_dimensions[0][0]}={weakest_dimensions[0][1]:.1f}, "
-        f"{weakest_dimensions[1][0]}={weakest_dimensions[1][1]:.1f}"
+        f"{grade}: {display_dimension(weakest_dimensions[0][0])}={weakest_dimensions[0][1]:.1f}, "
+        f"{display_dimension(weakest_dimensions[1][0])}={weakest_dimensions[1][1]:.1f}"
     )
 
 

src/excel_repo_data_helpers.py

@@ -12,6 +12,7 @@
     build_score_explanation,
 )
 from src.sparkline import sparkline as render_sparkline
+from src.scoring_dimensions import display_dimension
 
 
 def score_explanation_for_audit(audit: dict) -> dict:
@@ -300,7 +301,9 @@ def repo_detail_rows(
         )
         for rank, (dimension, score, summary) in enumerate(ranked_dimensions, 1):
             lookup_key = f"{repo_name}::{rank}"
-            dimension_rows.append([lookup_key, repo_name, rank, dimension, score, summary])
+            dimension_rows.append(
+                [lookup_key, repo_name, rank, display_dimension(dimension), score, summary]
+            )
 
         for run_index, score in enumerate(scores, 1):
             history_rows.append([repo_name, run_index, score, render_sparkline(scores)])

src/excel_score_explainer_helpers.py

@@ -4,6 +4,8 @@
 
 from typing import Any
 
+from src.scoring_dimensions import UNSCORED_DIMENSIONS, display_dimension
+
 SCORE_EXPLAINER_HEADERS = ["Dimension", "Weight", "What It Measures", "How to Improve"]
 
 DIMENSION_INFO = {
@@ -41,6 +43,10 @@
         "docs/ dir, CHANGELOG, comment density",
         "Add docs/ folder or CHANGELOG.md",
     ),
+    "description": (
+        "Repository description confidence and consistency",
+        "Add a concise, accurate repository description",
+    ),
 }
 
 
@@ -53,12 +59,21 @@ def build_score_explainer_content(
     return {
         "dimension_rows": [
             [
-                dimension,
+                display_dimension(dimension),
                 f"{weight:.0%}",
                 DIMENSION_INFO.get(dimension, ("", ""))[0],
                 DIMENSION_INFO.get(dimension, ("", ""))[1],
             ]
             for dimension, weight in sorted(weights.items(), key=lambda item: item[1], reverse=True)
+        ] + [
+            [
+                display_dimension(dimension),
+                "Unscored",
+                DIMENSION_INFO.get(dimension, ("", ""))[0],
+                DIMENSION_INFO.get(dimension, ("", ""))[1],
+            ]
+            for dimension in sorted(UNSCORED_DIMENSIONS)
+            if dimension not in weights
         ],
         "grade_rows": [[grade, f">= {threshold:.0%}"] for threshold, grade in grade_thresholds],
         "tier_rows": [

src/portfolio_risk.py

@@ -56,7 +56,6 @@ def build_risk_entry(
     display_name: str,
     operating_path: str,
     path_override: str,
-    path_confidence: str,
     context_quality: str,
     activity_status: str,
     registry_status: str,

src/portfolio_truth_reconcile.py

@@ -653,7 +653,6 @@ def _build_truth_project(
         display_name=raw_project["name"],
         operating_path=path_entry.get("operating_path", ""),
         path_override=path_entry.get("path_override", ""),
-        path_confidence=path_entry.get("path_confidence", "legacy"),
         context_quality=context_quality,
         activity_status=activity_status,
         registry_status=registry_status,

src/report_enrichment.py

@@ -7,6 +7,7 @@
 
 from src.portfolio_truth_types import truth_latest_path
 from src.report_contracts import RiskLookupEntry, RiskPosture, TopElevatedEntry
+from src.scoring_dimensions import display_dimension
 from src.terminology import ACTION_SYNC_CANONICAL_LABELS
 from src.weekly_packaging import finalize_weekly_pack
 from src.weekly_scheduling_overlay import apply_weekly_scheduling_overlay
@@ -614,9 +615,10 @@ def _top_dimension_labels(scores: dict[str, float], *, reverse: bool) -> list[st
     for dimension, score in ordered:
         if dimension == "interest":
             continue
-        labels.append(
-            f"{DIMENSION_LABELS.get(dimension, dimension.replace('_', ' ').title())} ({score:.2f})"
-        )
+        label = DIMENSION_LABELS.get(dimension, dimension.replace("_", " ").title())
+        if display_dimension(dimension) != dimension:
+            label = f"{label} (unscored)"
+        labels.append(f"{label} ({score:.2f})")
         if len(labels) == 3:
             break
     return labels