feat: add suggest_resume_keywords for skills/domains/keywords gap analysis

Replaces NotImplementedError stub with full LLM-backed implementation.
Builds a prompt from the last 3 resume positions plus already-selected
skills/domains/keywords, calls LLMRouter, and returns de-duped suggestions
in all three categories.

scripts/suggest_helpers.py

@@ -124,4 +124,37 @@ def suggest_resume_keywords(
 
     Returns: {"skills": [...], "domains": [...], "keywords": [...]}
     """
-    raise NotImplementedError
+    resume_context = _load_resume_context(resume_path)
+
+    already_skills   = ", ".join(current_kw.get("skills", []))   or "none"
+    already_domains  = ", ".join(current_kw.get("domains", []))  or "none"
+    already_keywords = ", ".join(current_kw.get("keywords", [])) or "none"
+
+    prompt = f"""You are helping a job seeker build a keyword profile used to score job description matches.
+
+--- RESUME BACKGROUND ---
+{resume_context or "Not provided"}
+
+--- ALREADY SELECTED (do not repeat these) ---
+Skills:   {already_skills}
+Domains:  {already_domains}
+Keywords: {already_keywords}
+
+Suggest additional tags in each of the three categories below. Only suggest tags NOT already in the lists above.
+
+SKILLS — specific technical or soft skills (e.g. "Salesforce", "Executive Communication", "SQL", "Stakeholder Management")
+DOMAINS — industry verticals, company types, or functional areas (e.g. "B2B SaaS", "EdTech", "Non-profit", "Series A-C")
+KEYWORDS — specific terms, methodologies, metrics, or JD phrases (e.g. "NPS", "churn prevention", "QBR", "cross-functional")
+
+Return ONLY valid JSON in exactly this format (no extra text):
+{{"skills": ["Skill A", "Skill B"],
+  "domains": ["Domain A"],
+  "keywords": ["Keyword A", "Keyword B"]}}"""
+
+    raw = LLMRouter().complete(prompt).strip()
+    parsed = _parse_json(raw)
+    return {
+        "skills":   parsed.get("skills", []),
+        "domains":  parsed.get("domains", []),
+        "keywords": parsed.get("keywords", []),
+    }

tests/test_suggest_helpers.py

@@ -95,3 +95,54 @@ def test_suggest_search_terms_raises_on_llm_exhausted():
     with patch("scripts.suggest_helpers.LLMRouter", return_value=mock_router):
         with pytest.raises(RuntimeError, match="All LLM backends exhausted"):
             suggest_search_terms(["CSM"], RESUME_PATH, BLOCKLIST, USER_PROFILE)
+
+
+# ── suggest_resume_keywords ───────────────────────────────────────────────────
+
+CURRENT_KW = {
+    "skills": ["Customer Success", "SQL"],
+    "domains": ["B2B SaaS"],
+    "keywords": ["NPS"],
+}
+
+
+def test_suggest_resume_keywords_returns_all_three_categories():
+    from scripts.suggest_helpers import suggest_resume_keywords
+    payload = {
+        "skills": ["Project Management"],
+        "domains": ["EdTech"],
+        "keywords": ["churn prevention"],
+    }
+    with _mock_llm(payload):
+        result = suggest_resume_keywords(RESUME_PATH, CURRENT_KW)
+    assert "skills" in result
+    assert "domains" in result
+    assert "keywords" in result
+
+
+def test_suggest_resume_keywords_excludes_already_selected():
+    from scripts.suggest_helpers import suggest_resume_keywords
+    with _mock_llm({"skills": [], "domains": [], "keywords": []}) as mock_cls:
+        suggest_resume_keywords(RESUME_PATH, CURRENT_KW)
+    prompt_sent = mock_cls.return_value.complete.call_args[0][0]
+    # Already-selected tags should appear in the prompt so LLM knows to skip them
+    assert "Customer Success" in prompt_sent
+    assert "NPS" in prompt_sent
+
+
+def test_suggest_resume_keywords_returns_empty_on_bad_json():
+    from scripts.suggest_helpers import suggest_resume_keywords
+    mock_router = MagicMock()
+    mock_router.complete.return_value = "I cannot assist."
+    with patch("scripts.suggest_helpers.LLMRouter", return_value=mock_router):
+        result = suggest_resume_keywords(RESUME_PATH, CURRENT_KW)
+    assert result == {"skills": [], "domains": [], "keywords": []}
+
+
+def test_suggest_resume_keywords_raises_on_llm_exhausted():
+    from scripts.suggest_helpers import suggest_resume_keywords
+    mock_router = MagicMock()
+    mock_router.complete.side_effect = RuntimeError("All LLM backends exhausted")
+    with patch("scripts.suggest_helpers.LLMRouter", return_value=mock_router):
+        with pytest.raises(RuntimeError, match="All LLM backends exhausted"):
+            suggest_resume_keywords(RESUME_PATH, CURRENT_KW)