feat(rag): fb-41 PR-9c-2 — pipeline integration + mock test + SKILL.md (★ NLI 실 활성화)

PR-9c-1 의 wire surface 위에 behavior 활성화 — `ask_multi_hop` 의 step 8.5 hook 가 `[rag] nli_threshold > 0` 일 때 NLI 검증 실 수행. **첫 user-visible behavior change** in PR-9.

- crates/kebab-rag/src/pipeline.rs:
  - ask_multi_hop step 8.5 NLI hook (empty answer 가드 + truncate_for_nli + verifier.score + verification field + refusal 분기).
  - refuse_nli_verification helper (verification: Some(...) + RefusalReason::NliVerificationFailed).
  - refuse_nli_model_unavailable helper (verification: None + RefusalReason::NliModelUnavailable).
  - truncate_for_nli helper (module-level pub fn, MAX_NLI_PREMISE_CHARS = 4 * 400 = 1600 chars 의 chars-based budget, _hypothesis 미사용 placeholder — v0.18.1 token-budget 갱신 candidate).
  - PR-9c-1 의 #[allow(dead_code)] 두 곳 제거 (verifier field + with_verifier builder; doc 의 transitional sentence 도 정리). round-1 PR-9c-1 review N1 carry-forward closure.
- crates/kebab-app/src/app.rs:
  - App::open_with_config 의 NliVerifier construction — config.rag.nli_threshold > 0 → OnnxNliVerifier::new + Arc::new wrap + 후속 RagPipeline 초기화 시 with_verifier 호출. 실패 시 ? 전파 (시그니처 Result<Self> 그대로 — caller cascading 0).
  - kebab-app/Cargo.toml 에 kebab-nli path 의존 추가.
- crates/kebab-rag/tests/multi_hop.rs + tests/common/mod.rs:
  - MockNliVerifier (pass / fail / err 생성자 + score call_count instrumented).
  - multi_hop_nli_pass_keeps_grounded — entailment 0.9 → grounded=true, verification.nli_passed=true.
  - multi_hop_nli_fail_refuses — entailment 0.1 → refusal=NliVerificationFailed.
  - multi_hop_nli_disabled_skip_verify — threshold 0.0 → verify skip, verification=None.
  - multi_hop_nli_model_unavailable_refuses — verifier Err → refusal=NliModelUnavailable.
  - multi_hop_truncate_for_nli_preserves_hypothesis — long premise truncation + hypothesis 보전.
- integrations/claude-code/kebab/SKILL.md: mcp__kebab__ask 절에 NLI 안내 한 단락 (verification.nli_passed 의미 + threshold tuning + nli_verification_failed/nli_model_unavailable refusal handling).

검증: cargo test --workspace -j 1 — 5 신규 multi-hop pass + 회귀 0 (pre-existing kebab-mcp::tools_call_ask_multi_hop 동일 flaky). cargo clippy --workspace --all-targets -j 1 -- -D warnings clean.
Wire 영향: PR-9c-1 의 schema 변경에 *behavior wiring* — answer.v1.verification field 가 multi-hop happy path + refuse path 양쪽에서 채움.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

integrations/claude-code/kebab/SKILL.md

@@ -88,6 +88,7 @@ Input:
 - For follow-up turns on the same topic, pass `session_id` (e.g. `"team-onboarding-2026-05"`) and reuse it across the conversation. Sessions persist until `kebab reset --data-only`.
 - p9-fb-40: 기본 `prompt_template_version = "rag-v2"`. 답변이 더 strict — fact 인용 시 verbatim span, 학습 지식 동원 금지, 근거 모호 시 "확실하지 않다" 출현 가능. user 가 `[rag] prompt_template_version = "rag-v1"` 명시 시 legacy 동작.
 - **p9-fb-41 `multi_hop: true`** — opt the ask into the multi-hop pipeline. The query is decomposed into sub-questions, each retrieved independently (LLM-driven decide loop, up to `rag.multi_hop_max_depth` iters), then synthesized over the merged chunk pool. Cost trade-off: 2–5× LLM calls vs. single-pass. **Use** for compound questions ("X 와 Y 의 차이는?", prereq chains, cross-doc reasoning where one chunk alone is insufficient). **Don't** for simple fact-finding (single-pass is faster + cheaper). When set, `answer.v1.hops[]` carries the per-hop trace (`{iter, kind, sub_queries[], context_chunks_added, forced_stop, llm_call_ms}`) — surface a brief "Searched in N hops" note when the trace is non-trivial. Decompose-failure (model emitted non-JSON) → `refusal_reason = "multi_hop_decompose_failed"`; treat like any other refusal.
+- **v0.18+ multi-hop NLI verification** — multi-hop ask (`mcp__kebab__ask` with `multi_hop: true`) runs a post-synthesize NLI groundedness gate when `[rag] nli_threshold > 0` is set in the user's config. `answer.v1.verification.nli_passed == true` means the generated answer is entailed by the retrieved chunks (grounded); `false` means the answer is refused with `refusal_reason = "nli_verification_failed"` and the `verification` block still ships so the agent can show what entailment score was rejected. Threshold tuning: 0.5 is the production default, 0.9 is strict mode. If the NLI model download / inference fails the pipeline emits `refusal_reason = "nli_model_unavailable"` — user-side workaround is `[rag] nli_threshold = 0` then retry multi-hop. Single-pass `ask` (multi_hop: false / unset) is unaffected — it keeps the LLM self-judge gate as the only verification.
 
 ### `mcp__kebab__fetch` — when you need raw text