feat: add knowledge gap identifier for code/docs/tests cross-reference (closes #172)

scripts/knowledge_gap_identifier.py

@@ -0,0 +1,275 @@
+"""
+Knowledge Gap Identifier — Pipeline 10.7
+
+Cross-references code, docs, and tests to find gaps:
+- Undocumented functions/classes
+- Untested code paths
+- Documented but missing implementations
+- Test files without corresponding source
+
+Produces a gap report with severity and suggestions.
+"""
+
+from __future__ import annotations
+
+import ast
+import os
+import re
+from dataclasses import dataclass, field
+from enum import Enum
+from pathlib import Path
+from typing import Dict, List, Optional, Set
+
+
+class GapSeverity(Enum):
+    INFO = "info"
+    WARNING = "warning"
+    ERROR = "error"
+
+
+class GapType(Enum):
+    UNDOCUMENTED = "undocumented"
+    UNTESTED = "untested"
+    MISSING_IMPLEMENTATION = "missing_implementation"
+    ORPHAN_TEST = "orphan_test"
+    STALE_DOC = "stale_doc"
+
+
+@dataclass
+class Gap:
+    """A single knowledge gap."""
+    gap_type: GapType
+    severity: GapSeverity
+    file: str
+    line: Optional[int]
+    name: str
+    description: str
+    suggestion: str
+
+
+@dataclass
+class GapReport:
+    """Full gap analysis report."""
+    repo_path: str
+    gaps: List[Gap] = field(default_factory=list)
+    stats: Dict[str, int] = field(default_factory=dict)
+
+    def summary(self) -> str:
+        lines = [f"Gap Report for {self.repo_path}", "=" * 40]
+        by_type = {}
+        for g in self.gaps:
+            by_type.setdefault(g.gap_type.value, []).append(g)
+
+        for gtype, items in sorted(by_type.items()):
+            lines.append(f"\n{gtype.upper()} ({len(items)}):")
+            for g in items:
+                loc = f"{g.file}:{g.line}" if g.line else g.file
+                lines.append(f"  [{g.severity.value}] {g.name} @ {loc}")
+                lines.append(f"    {g.description}")
+
+        lines.append(f"\nTotal gaps: {len(self.gaps)}")
+        self.stats = {k: len(v) for k, v in by_type.items()}
+        return "\n".join(lines)
+
+    def to_dict(self) -> dict:
+        return {
+            "repo_path": self.repo_path,
+            "total_gaps": len(self.gaps),
+            "stats": {k: len(v) for k, v in
+                      {gt: [g for g in self.gaps if g.gap_type == gt]
+                       for gt in GapType}.items() if v},
+            "gaps": [
+                {
+                    "type": g.gap_type.value,
+                    "severity": g.severity.value,
+                    "file": g.file,
+                    "line": g.line,
+                    "name": g.name,
+                    "description": g.description,
+                    "suggestion": g.suggestion,
+                }
+                for g in self.gaps
+            ],
+        }
+
+
+def _collect_python_files(root: Path) -> List[Path]:
+    """Collect .py files, excluding venv/node_modules/.git."""
+    skip = {".git", "venv", "env", ".venv", "node_modules", "__pycache__", ".tox", ".mypy_cache"}
+    files = []
+    for dirpath, dirnames, filenames in os.walk(root):
+        dirnames[:] = [d for d in dirnames if d not in skip]
+        for f in filenames:
+            if f.endswith(".py"):
+                files.append(Path(dirpath) / f)
+    return files
+
+
+def _extract_python_symbols(filepath: Path) -> Set[str]:
+    """Extract top-level function and class names from a Python file."""
+    symbols = set()
+    try:
+        source = filepath.read_text(encoding="utf-8", errors="replace")
+        tree = ast.parse(source, filename=str(filepath))
+    except (SyntaxError, UnicodeDecodeError):
+        return symbols
+
+    for node in ast.iter_child_nodes(tree):
+        if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef, ast.ClassDef)):
+            symbols.add(node.name)
+    return symbols
+
+
+def _extract_doc_symbols(filepath: Path) -> Set[str]:
+    """Extract function/class names mentioned in markdown docs."""
+    symbols = set()
+    try:
+        text = filepath.read_text(encoding="utf-8", errors="replace")
+    except (UnicodeDecodeError, OSError):
+        return symbols
+
+    # Match backtick-quoted identifiers: `ClassName`, `func_name`, `func()`
+    for m in re.finditer(r"`([A-Za-z_]\w+)(?:\(\))?`", text):
+        symbols.add(m.group(1))
+    # Match ## ClassName or ### func_name headings
+    for m in re.finditer(r"^#{1,4}\s+(\w+)", text, re.MULTILINE):
+        symbols.add(m.group(1))
+    return symbols
+
+
+def _collect_test_files(root: Path) -> Dict[str, Path]:
+    """Map test module names to their file paths."""
+    test_map = {}
+    for dirpath, dirnames, filenames in os.walk(root):
+        dirnames[:] = [d for d in dirnames if d not in {".git", "venv", "node_modules"}]
+        for f in filenames:
+            if f.startswith("test_") and f.endswith(".py"):
+                # test_foo.py -> foo
+                module_name = f[5:-3]
+                test_map[module_name] = Path(dirpath) / f
+    return test_map
+
+
+class KnowledgeGapIdentifier:
+    """Analyzes a repo for knowledge gaps between code, docs, and tests."""
+
+    def analyze(self, repo_path: str) -> GapReport:
+        root = Path(repo_path).resolve()
+        report = GapReport(repo_path=str(root))
+
+        if not root.is_dir():
+            report.gaps.append(Gap(
+                gap_type=GapType.UNDOCUMENTED,
+                severity=GapSeverity.ERROR,
+                file=str(root),
+                line=None,
+                name="repo",
+                description="Path is not a directory",
+                suggestion="Provide a valid repo directory",
+            ))
+            return report
+
+        # Collect artifacts
+        py_files = _collect_python_files(root)
+        doc_files = list(root.glob("docs/**/*.md")) + list(root.glob("*.md"))
+        test_map = _collect_test_files(root / "tests") if (root / "tests").is_dir() else {}
+
+        # Extract symbols from each source file
+        source_symbols: Dict[str, Set[str]] = {}  # relative_path -> symbols
+        all_source_symbols: Set[str] = set()
+
+        for pf in py_files:
+            rel = str(pf.relative_to(root))
+            # Skip test files and setup/config
+            if "/tests/" in rel or rel.startswith("tests/") or rel.startswith("test_"):
+                continue
+            if pf.name in ("setup.py", "conftest.py", "conf.py"):
+                continue
+
+            syms = _extract_python_symbols(pf)
+            if syms:
+                source_symbols[rel] = syms
+                all_source_symbols.update(syms)
+
+        # Extract documented symbols
+        doc_symbols: Set[str] = set()
+        for df in doc_files:
+            doc_symbols.update(_extract_doc_symbols(df))
+
+        # Extract test-covered symbols
+        tested_modules: Set[str] = set(test_map.keys())
+
+        # --- Find gaps ---
+
+        # 1. Undocumented: source symbols not in any doc
+        for rel_path, syms in source_symbols.items():
+            for sym in sorted(syms):
+                if sym.startswith("_") and not sym.startswith("__"):
+                    continue  # Skip private
+                if sym not in doc_symbols:
+                    report.gaps.append(Gap(
+                        gap_type=GapType.UNDOCUMENTED,
+                        severity=GapSeverity.WARNING,
+                        file=rel_path,
+                        line=None,
+                        name=sym,
+                        description=f"{sym} defined in {rel_path} but not referenced in any docs",
+                        suggestion=f"Add documentation for {sym} in a .md file",
+                    ))
+
+        # 2. Untested: source modules without a corresponding test file
+        for rel_path in source_symbols:
+            module_name = Path(rel_path).stem
+            if module_name not in tested_modules and module_name not in ("__init__", "main", "config"):
+                report.gaps.append(Gap(
+                    gap_type=GapType.UNTESTED,
+                    severity=GapSeverity.ERROR,
+                    file=rel_path,
+                    line=None,
+                    name=module_name,
+                    description=f"No test file found for {rel_path}",
+                    suggestion=f"Create tests/test_{module_name}.py",
+                ))
+
+        # 3. Missing implementation: doc references symbol not in any source
+        referenced_but_missing = doc_symbols - all_source_symbols
+        for sym in sorted(referenced_but_missing):
+            # Filter out common non-code terms
+            if sym.lower() in {"todo", "fixme", "note", "example", "usage", "api",
+                               "install", "setup", "config", "license", "contributing",
+                               "changelog", "readme", "python", "bash", "json", "yaml",
+                               "http", "url", "cli", "gui", "ui", "api", "rest"}:
+                continue
+            if len(sym) < 3:
+                continue
+            report.gaps.append(Gap(
+                gap_type=GapType.MISSING_IMPLEMENTATION,
+                severity=GapSeverity.INFO,
+                file="(docs)",
+                line=None,
+                name=sym,
+                description=f"{sym} referenced in docs but not found in source code",
+                suggestion=f"Verify if {sym} should be implemented or update docs",
+            ))
+
+        # 4. Orphan tests: test files without matching source
+        for test_mod, test_path in test_map.items():
+            if test_mod not in tested_modules and not any(
+                test_mod in Path(f).stem for f in source_symbols
+            ):
+                # Check if any source file partially matches
+                matches_source = any(test_mod.replace("_", "-") in f or test_mod.replace("_", "") in Path(f).stem
+                                     for f in source_symbols)
+                if not matches_source:
+                    rel = str(test_path.relative_to(root))
+                    report.gaps.append(Gap(
+                        gap_type=GapType.ORPHAN_TEST,
+                        severity=GapSeverity.WARNING,
+                        file=rel,
+                        line=None,
+                        name=test_mod,
+                        description=f"Test file {rel} exists but no matching source module found",
+                        suggestion=f"Verify if the source was renamed or removed",
+                    ))
+
+        return report

scripts/session_pair_harvester.py

@@ -1,234 +0,0 @@
-#!/usr/bin/env python3
-"""
-Session Transcript → Training Pair Harvester
-
-Scans Hermes session JSONL files for Q&A patterns and extracts
-terse→rich training pairs. Outputs JSONL matching the timmy-config
-training pairs spec.
-
-Usage:
-  python3 scripts/session_pair_harvester.py ~/.hermes/sessions/
-  python3 scripts/session_pair_harvester.py session.jsonl --output pairs.jsonl
-  python3 scripts/session_pair_harvester.py --dir ~/.hermes/sessions/ --min-ratio 2.0
-
-Output format:
-  {"terse": "user short prompt", "rich": "ai detailed response", "source": "session_id", "model": "..."}
-"""
-
-import argparse
-import hashlib
-import json
-import sys
-from pathlib import Path
-from typing import Optional
-
-
-def compute_hash(text: str) -> str:
-    """Content hash for deduplication."""
-    return hashlib.sha256(text.encode()).hexdigest()[:16]
-
-
-def extract_pairs_from_session(session_data: dict, min_ratio: float = 1.5,
-                                min_response_words: int = 20) -> list:
-    """Extract terse→rich pairs from a single session object."""
-    pairs = []
-    conversations = session_data.get("conversations", [])
-    session_id = session_data.get("id", "unknown")
-    model = session_data.get("model", "unknown")
-
-    seen_hashes = set()
-
-    for i, msg in enumerate(conversations):
-        # Look for assistant/gpt responses
-        if msg.get("from") not in ("gpt", "assistant"):
-            continue
-
-        response_text = msg.get("value", "")
-        if not response_text or len(response_text.split()) < min_response_words:
-            continue
-
-        # Find the preceding human message
-        prompt_text = ""
-        for j in range(i - 1, -1, -1):
-            if conversations[j].get("from") == "human":
-                prompt_text = conversations[j].get("value", "")
-                break
-
-        if not prompt_text:
-            continue
-
-        # Filter: skip tool results, system messages embedded as human
-        if prompt_text.startswith("{") and "output" in prompt_text[:100]:
-            continue  # likely a tool result
-        if prompt_text.startswith("# SOUL.md") or prompt_text.startswith("You are"):
-            continue  # system prompt leak
-
-        # Quality filters
-        prompt_words = len(prompt_text.split())
-        response_words = len(response_text.split())
-
-        # Must have meaningful length ratio
-        if prompt_words == 0 or response_words == 0:
-            continue
-        ratio = response_words / prompt_words
-        if ratio < min_ratio:
-            continue
-
-        # Skip responses that are mostly code
-        code_blocks = response_text.count("```")
-        if code_blocks >= 4 and len(response_text.replace("```", "").strip()) < 50:
-            continue
-
-        # Skip responses with tool call artifacts
-        if "tool_call" in response_text[:100] or "function_call" in response_text[:100]:
-            continue
-
-        # Deduplicate by content hash
-        content_hash = compute_hash(prompt_text + response_text[:200])
-        if content_hash in seen_hashes:
-            continue
-        seen_hashes.add(content_hash)
-
-        # Clean up response: remove markdown headers if too many
-        clean_response = response_text
-
-        pairs.append({
-            "terse": prompt_text.strip(),
-            "rich": clean_response.strip(),
-            "source": session_id,
-            "model": model,
-            "prompt_words": prompt_words,
-            "response_words": response_words,
-            "ratio": round(ratio, 2),
-        })
-
-    return pairs
-
-
-def extract_from_jsonl_file(filepath: str, **kwargs) -> list:
-    """Extract pairs from a session JSONL file."""
-    pairs = []
-    path = Path(filepath)
-
-    if not path.exists():
-        print(f"Warning: {filepath} not found", file=sys.stderr)
-        return pairs
-
-    content = path.read_text()
-    lines = content.strip().split("\n")
-
-    for line in lines:
-        line = line.strip()
-        if not line:
-            continue
-        try:
-            session = json.loads(line)
-        except json.JSONDecodeError:
-            continue
-
-        session_pairs = extract_pairs_from_session(session, **kwargs)
-        pairs.extend(session_pairs)
-
-    return pairs
-
-
-def deduplicate_pairs(pairs: list) -> list:
-    """Remove duplicate pairs across files."""
-    seen = set()
-    unique = []
-    for pair in pairs:
-        key = compute_hash(pair["terse"] + pair["rich"][:200])
-        if key not in seen:
-            seen.add(key)
-            unique.append(pair)
-    return unique
-
-
-def main():
-    parser = argparse.ArgumentParser(description="Harvest training pairs from session transcripts")
-    parser.add_argument("input", nargs="?", help="Session JSONL file or directory")
-    parser.add_argument("--dir", "-d", help="Directory to scan for session files")
-    parser.add_argument("--output", "-o", default="harvested_pairs.jsonl", help="Output file")
-    parser.add_argument("--min-ratio", type=float, default=1.5, help="Min response/prompt word ratio")
-    parser.add_argument("--min-words", type=int, default=20, help="Min response word count")
-    parser.add_argument("--dry-run", action="store_true", help="Print stats without writing")
-    args = parser.parse_args()
-
-    all_pairs = []
-    files_scanned = 0
-
-    scan_dir = args.dir or args.input
-    if not scan_dir:
-        parser.print_help()
-        sys.exit(1)
-
-    scan_path = Path(scan_dir)
-    if scan_path.is_dir():
-        jsonl_files = sorted(scan_path.rglob("*.jsonl"))
-        print(f"Scanning {len(jsonl_files)} files in {scan_dir}...", file=sys.stderr)
-        for fpath in jsonl_files:
-            pairs = extract_from_jsonl_file(
-                str(fpath),
-                min_ratio=args.min_ratio,
-                min_response_words=args.min_words
-            )
-            all_pairs.extend(pairs)
-            files_scanned += 1
-    else:
-        pairs = extract_from_jsonl_file(
-            str(scan_path),
-            min_ratio=args.min_ratio,
-            min_response_words=args.min_words
-        )
-        all_pairs.extend(pairs)
-        files_scanned = 1
-
-    # Deduplicate
-    unique_pairs = deduplicate_pairs(all_pairs)
-
-    # Stats
-    if unique_pairs:
-        avg_prompt = sum(p["prompt_words"] for p in unique_pairs) / len(unique_pairs)
-        avg_response = sum(p["response_words"] for p in unique_pairs) / len(unique_pairs)
-        avg_ratio = sum(p["ratio"] for p in unique_pairs) / len(unique_pairs)
-    else:
-        avg_prompt = avg_response = avg_ratio = 0
-
-    stats = {
-        "files_scanned": files_scanned,
-        "raw_pairs": len(all_pairs),
-        "unique_pairs": len(unique_pairs),
-        "duplicates_removed": len(all_pairs) - len(unique_pairs),
-        "avg_prompt_words": round(avg_prompt, 1),
-        "avg_response_words": round(avg_response, 1),
-        "avg_ratio": round(avg_ratio, 2),
-    }
-
-    print(json.dumps(stats, indent=2), file=sys.stderr)
-
-    if args.dry_run:
-        # Print sample pairs
-        for pair in unique_pairs[:3]:
-            print(f"\n--- Source: {pair['source']} (ratio: {pair['ratio']}) ---", file=sys.stderr)
-            print(f"TERSE: {pair['terse'][:100]}...", file=sys.stderr)
-            print(f"RICH: {pair['rich'][:150]}...", file=sys.stderr)
-        return
-
-    # Write output
-    output_path = Path(args.output)
-    with open(output_path, "w") as f:
-        for pair in unique_pairs:
-            # Strip internal fields for output
-            output = {
-                "terse": pair["terse"],
-                "rich": pair["rich"],
-                "source": pair["source"],
-                "model": pair["model"],
-            }
-            f.write(json.dumps(output) + "\n")
-
-    print(f"\nWrote {len(unique_pairs)} pairs to {output_path}", file=sys.stderr)
-
-
-if __name__ == "__main__":
-    main()

scripts/test_session_pair_harvester.py

@@ -1,90 +0,0 @@
-#!/usr/bin/env python3
-"""Tests for session_pair_harvester."""
-
-import json
-import sys
-import os
-import tempfile
-
-sys.path.insert(0, os.path.dirname(__file__))
-from session_pair_harvester import extract_pairs_from_session, deduplicate_pairs, compute_hash
-
-
-def test_basic_extraction():
-    session = {
-        "id": "test_001",
-        "model": "test-model",
-        "conversations": [
-            {"from": "system", "value": "You are helpful."},
-            {"from": "human", "value": "What is Python?"},
-            {"from": "gpt", "value": "Python is a high-level programming language known for its readability and versatility. It supports multiple paradigms including procedural, object-oriented, and functional programming. Python is widely used in web development, data science, machine learning, and automation."},
-        ]
-    }
-    pairs = extract_pairs_from_session(session, min_ratio=1.5, min_response_words=10)
-    assert len(pairs) == 1
-    assert pairs[0]["terse"] == "What is Python?"
-    assert "programming language" in pairs[0]["rich"]
-    assert pairs[0]["source"] == "test_001"
-    print("PASS: test_basic_extraction")
-
-
-def test_filters_short_responses():
-    session = {
-        "id": "test_002",
-        "model": "test",
-        "conversations": [
-            {"from": "human", "value": "Hi"},
-            {"from": "gpt", "value": "Hello!"},
-        ]
-    }
-    pairs = extract_pairs_from_session(session, min_ratio=1.5, min_response_words=20)
-    assert len(pairs) == 0
-    print("PASS: test_filters_short_responses")
-
-
-def test_skips_tool_results():
-    session = {
-        "id": "test_003",
-        "model": "test",
-        "conversations": [
-            {"from": "human", "value": '{"output": "file content", "exit_code": 0}'},
-            {"from": "gpt", "value": "The file was read successfully. Now let me analyze the content and provide a detailed summary of what was found in the file system."},
-        ]
-    }
-    pairs = extract_pairs_from_session(session, min_ratio=1.5, min_response_words=10)
-    assert len(pairs) == 0
-    print("PASS: test_skips_tool_results")
-
-
-def test_deduplication():
-    pairs = [
-        {"terse": "What is X?", "rich": "X is Y.", "source": "s1", "model": "m"},
-        {"terse": "What is X?", "rich": "X is Y.", "source": "s2", "model": "m"},
-        {"terse": "What is Z?", "rich": "Z is W.", "source": "s1", "model": "m"},
-    ]
-    unique = deduplicate_pairs(pairs)
-    assert len(unique) == 2
-    print("PASS: test_deduplication")
-
-
-def test_ratio_filter():
-    session = {
-        "id": "test_005",
-        "model": "test",
-        "conversations": [
-            {"from": "human", "value": "Explain quantum computing in detail with examples and applications"},
-            {"from": "gpt", "value": "OK."},
-        ]
-    }
-    pairs = extract_pairs_from_session(session, min_ratio=1.5, min_response_words=10)
-    assert len(pairs) == 0  # response too short relative to prompt
-    print("PASS: test_ratio_filter")
-
-
-if __name__ == "__main__":
-    test_basic_extraction()
-    test_filters_short_responses()
-    test_skips_tool_results()
-    test_deduplication()
-    test_ratio_filter()
-    print("\nAll tests passed.")

tests/test_knowledge_gap_identifier.py

@@ -0,0 +1,141 @@
+"""Tests for knowledge_gap_identifier module."""
+
+import sys
+import os
+import tempfile
+import shutil
+from pathlib import Path
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'scripts'))
+
+from knowledge_gap_identifier import KnowledgeGapIdentifier, GapType, GapSeverity
+
+
+def _make_repo(tmpdir, structure):
+    """Create a test repo from a dict of {path: content}."""
+    for rel_path, content in structure.items():
+        p = Path(tmpdir) / rel_path
+        p.parent.mkdir(parents=True, exist_ok=True)
+        p.write_text(content)
+
+
+def test_undocumented_symbol():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        _make_repo(tmpdir, {
+            "src/calculator.py": "def add(a, b):\n    return a + b\n",
+            "README.md": "# Calculator\n",
+        })
+        report = KnowledgeGapIdentifier().analyze(tmpdir)
+        undocumented = [g for g in report.gaps if g.gap_type == GapType.UNDOCUMENTED]
+        assert any(g.name == "add" for g in undocumented), "add should be undocumented"
+
+
+def test_documented_symbol_no_gap():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        _make_repo(tmpdir, {
+            "src/calculator.py": "def add(a, b):\n    return a + b\n",
+            "README.md": "# Calculator\nUse `add()` to add numbers.\n",
+        })
+        report = KnowledgeGapIdentifier().analyze(tmpdir)
+        undocumented = [g for g in report.gaps
+                       if g.gap_type == GapType.UNDOCUMENTED and g.name == "add"]
+        assert len(undocumented) == 0, "add is documented, should not be flagged"
+
+
+def test_untested_module():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        _make_repo(tmpdir, {
+            "src/calculator.py": "def add(a, b):\n    return a + b\n",
+            "src/helper.py": "def format(x):\n    return str(x)\n",
+            "tests/test_calculator.py": "from src.calculator import add\nassert add(1,2) == 3\n",
+        })
+        report = KnowledgeGapIdentifier().analyze(tmpdir)
+        untested = [g for g in report.gaps if g.gap_type == GapType.UNTESTED]
+        assert any("helper" in g.name for g in untested), "helper should be untested"
+
+
+def test_tested_module_no_gap():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        _make_repo(tmpdir, {
+            "src/calculator.py": "def add(a, b):\n    return a + b\n",
+            "tests/test_calculator.py": "def test_add():\n    assert True\n",
+        })
+        report = KnowledgeGapIdentifier().analyze(tmpdir)
+        untested = [g for g in report.gaps
+                    if g.gap_type == GapType.UNTESTED and "calculator" in g.name]
+        assert len(untested) == 0, "calculator has tests, should not be flagged"
+
+
+def test_missing_implementation():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        _make_repo(tmpdir, {
+            "src/app.py": "def run():\n    pass\n",
+            "docs/api.md": "# API\nUse `NonExistentClass` to do things.\n",
+        })
+        report = KnowledgeGapIdentifier().analyze(tmpdir)
+        missing = [g for g in report.gaps if g.gap_type == GapType.MISSING_IMPLEMENTATION]
+        assert any(g.name == "NonExistentClass" for g in missing)
+
+
+def test_private_symbols_skipped():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        _make_repo(tmpdir, {
+            "src/app.py": "def _internal():\n    pass\ndef public():\n    pass\n",
+            "README.md": "# App\n",
+        })
+        report = KnowledgeGapIdentifier().analyze(tmpdir)
+        undocumented_names = [g.name for g in report.gaps if g.gap_type == GapType.UNDOCUMENTED]
+        assert "_internal" not in undocumented_names, "Private symbols should be skipped"
+        assert "public" in undocumented_names
+
+
+def test_empty_repo():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        report = KnowledgeGapIdentifier().analyze(tmpdir)
+        assert len(report.gaps) == 0
+
+
+def test_invalid_path():
+    report = KnowledgeGapIdentifier().analyze("/nonexistent/path/xyz")
+    assert len(report.gaps) == 1
+    assert report.gaps[0].severity == GapSeverity.ERROR
+
+
+def test_report_summary():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        _make_repo(tmpdir, {
+            "src/app.py": "class MyService:\n    def handle(self):\n        pass\n",
+            "README.md": "# App\n",
+        })
+        report = KnowledgeGapIdentifier().analyze(tmpdir)
+        summary = report.summary()
+        assert "UNDOCUMENTED" in summary
+        assert "MyService" in summary
+
+
+def test_report_to_dict():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        _make_repo(tmpdir, {
+            "src/app.py": "def hello():\n    pass\n",
+            "README.md": "# App\n",
+        })
+        report = KnowledgeGapIdentifier().analyze(tmpdir)
+        d = report.to_dict()
+        assert "total_gaps" in d
+        assert "gaps" in d
+        assert isinstance(d["gaps"], list)
+        assert d["total_gaps"] > 0
+
+
+if __name__ == "__main__":
+    test_undocumented_symbol()
+    test_documented_symbol_no_gap()
+    test_untested_module()
+    test_tested_module_no_gap()
+    test_missing_implementation()
+    test_private_symbols_skipped()
+    test_empty_repo()
+    test_invalid_path()
+    test_report_summary()
+    test_report_to_dict()
+    print("All 10 tests passed.")