feat(ui): batch risk column + bulk vault controls; isolate test vaults

- Batch table: add Risk Level (LOW/MEDIUM/HIGH) + Review Terms count; rename to
Internal/Independent; caption explains HIGH = needs confirmation.
- Bulk vault controls: confirm "I have these" (→ safe in all future resumes) or
block "never use these". Only user confirmation upgrades a term to safe — the
system never auto-promotes (vault source labels enforce this).
- Tests: isolate verify_anticheat / verify_90_pipeline to temp vault paths so
runs are deterministic and never pollute the real per-user vault.

All 3 regression suites pass.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

scripts/verify_90_pipeline.py

@@ -11,6 +11,10 @@ sys.path.insert(0, os.path.abspath("."))
 
 from src.resume_customizer import ResumeCustomizer
 from src.llm_client import LLMClient
+import src.candidate_vault as _cv
+_cv._VAULT_PATH = "data/_test_vault_90.json"
+if os.path.exists(_cv._VAULT_PATH):
+    os.remove(_cv._VAULT_PATH)
 
 src_pdf = r"C:\Users\Nxtwave\Desktop\resume\Saiteja_Tirunagari_Resume A 26 - Copy.pdf"
 dst = "data/resume/resume.pdf"

scripts/verify_anticheat.py

@@ -22,6 +22,11 @@ from src.resume_customizer import ResumeCustomizer, _read_docx_text
 from src.llm_client import LLMClient
 from src.ats_validator import validate_resume
 from src.resume_parser_v2 import parse_resume_pdf
+# Isolate the vault so prior user confirmations don't change anti-cheat results.
+import src.candidate_vault as _cv
+_cv._VAULT_PATH = "data/_test_vault_anticheat.json"
+if os.path.exists(_cv._VAULT_PATH):
+    os.remove(_cv._VAULT_PATH)
 
 src_pdf = r"C:\Users\Nxtwave\Desktop\resume\Saiteja_Tirunagari_Resume A 26 - Copy.pdf"
 dst = "data/resume/resume.pdf"

ui.py

@@ -2086,31 +2086,76 @@ if not st.session_state.running and st.session_state.results:
         _ORDER = {"READY_90_PLUS": 0, "READY_90_PLUS_REVIEW_RECOMMENDED": 1,
                   "NEEDS_USER_INPUT": 2, "NEEDS_REPAIR": 3,
                   "NOT_ELIGIBLE_LOW_FIT": 4, "PARSE_FAILED": 5}
+        def _risk_level(j):
+            q = j.get("quality_flag", "")
+            if j.get("status") == "NEEDS_USER_INPUT":
+                return "HIGH"
+            if q == "REVIEW_REQUIRED_90_PLUS" or j.get("review_terms"):
+                return "MEDIUM"
+            if q in ("WEAK_90_INTERNAL_ONLY",):
+                return "HIGH"
+            return "LOW"
         _rows = []
         for j in sorted(st.session_state.results,
                         key=lambda x: _ORDER.get(x.get("status", ""), 3)):
+            _nrev = len(j.get("review_terms", []) or []) + \
+                    len(j.get("_v2_report", {}).get("high_risk_terms_for_confirmation", []) or []) \
+                    if isinstance(j.get("_v2_report"), dict) else len(j.get("review_terms", []) or [])
             _rows.append({
                 "Job Title": (j.get("title", "") or "")[:40],
                 "Company": (j.get("company", "") or "")[:24],
                 "Platform": j.get("platform", j.get("source", "")),
                 "Status": j.get("status", ""),
                 "Quality": j.get("quality_flag", ""),
-                "JD Match": j.get("jd_match", j.get("ats_score_after", "")),
+                "Internal": j.get("jd_match", j.get("ats_score_after", "")),
                 "Independent": j.get("independent_jd_match", ""),
                 "Readability": j.get("ats_readability", ""),
-                "Risk": "review" if j.get("review_terms") else "low",
+                "Risk": _risk_level(j),
+                "Review Terms": _nrev,
                 "Download": "✅" if j.get("download_allowed") else "—",
             })
         with st.expander(f"📋 Batch summary — {len(_rows)} jobs (ranked by readiness)", expanded=True):
             _ready = sum(1 for r in _rows if r["Download"] == "✅")
             st.caption(f"{_ready}/{len(_rows)} ready to apply (both internal & "
-                       f"independent ≥ 90). Independent = anti-circular evidence-based score.")
+                       f"independent ≥ 90). Independent = anti-circular evidence-based score. "
+                       f"Risk HIGH = needs your confirmation before applying.")
             try:
                 import pandas as _pd
                 st.dataframe(_pd.DataFrame(_rows), use_container_width=True, hide_index=True)
             except Exception:
                 st.table(_rows)
 
+        # ── Bulk vault controls (confirm/block terms across all future jobs) ──
+        with st.expander("🔐 Manage skills vault (confirm or block terms)", expanded=False):
+            st.caption("Confirmed terms are treated as fully safe in every future "
+                       "resume; blocked terms are never used. Only YOUR confirmation "
+                       "upgrades a term to safe — the system never auto-promotes.")
+            vc1, vc2 = st.columns(2)
+            with vc1:
+                _confirm_in = st.text_input(
+                    "✅ Confirm I have these (comma-separated)",
+                    key="vault_confirm_in",
+                    placeholder="e.g. SIEM, SOAR, Tableau")
+                if st.button("Confirm to vault", key="vault_confirm_btn") and _confirm_in.strip():
+                    try:
+                        from src.candidate_vault import confirm_terms
+                        confirm_terms([t.strip() for t in _confirm_in.split(",") if t.strip()], confirmed=True)
+                        st.success("Confirmed — these are now safe for future resumes.")
+                    except Exception as _e:
+                        st.error(f"Could not update vault: {_e}")
+            with vc2:
+                _block_in = st.text_input(
+                    "🚫 Never use these (comma-separated)",
+                    key="vault_block_in",
+                    placeholder="e.g. Kubernetes, CISSP")
+                if st.button("Block in vault", key="vault_block_btn") and _block_in.strip():
+                    try:
+                        from src.candidate_vault import confirm_terms
+                        confirm_terms([t.strip() for t in _block_in.split(",") if t.strip()], confirmed=False)
+                        st.success("Blocked — these will never be added to resumes.")
+                    except Exception as _e:
+                        st.error(f"Could not update vault: {_e}")
+
 if st.session_state.running:
     time.sleep(0.8)
     st.rerun()