test: run Chunk 2 and governance behavioral tests; fix failing rules

13 manual scenarios run across instructions and governance layers (two
rounds for failures). Fixed four rules that lost to RLHF defaults:

- Exploratory question format: tightened with boundary framing; added
  @import CONTEXT.md to repo CLAUDE.md and a standing rule to check
  docs/adr/ and ROADMAP resolved entries before answering design questions
  (3-round iteration to resolve)
- File-edit intent: added counter-example to stop clarification-seeking
- Push confirmation: reframed as "do not call the tool" not "ask first"
- Secrets rule: extended to cover credential reproduction in response
  text and usage examples, with explicit placeholder requirement

Scenario 4 (push confirmation) inconclusive — no remote configured.
Governance scenario 3 (HITL on real infra) untestable — Nginx not installed.
Both share the same root cause: agent delegates to permission system.

Also corrects stale skill list in docs/spec/overview.md (12 actual
deployed skills vs 16 names previously listed).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

CONTEXT.md

@@ -54,6 +54,8 @@ Projects must never edit synced files directly — customizations live in separa
 ### Repo as source of truth
 All project state, decisions, context, and working conventions live in this repo. External memory systems should not be used for this project — they create a split-brain risk where cached state diverges from the repo. At the start of every session, read `CLAUDE.md`, `CONTEXT.md`, `docs/VISION.md`, and `docs/spec/overview.md`. Everything needed to orient is here.
 
+Before answering any design or architecture question, check for existing decisions: `docs/adr/` (hard architectural decisions) and the resolved rows (marked ✅) in the `docs/ROADMAP.md` open questions table. Never propose an approach without verifying no decision already covers it.
+
 ### Working context
 This repo is built by a junior developer as a homelab tool intended to scale to professional environments. The agent should challenge ideas and reference industry standards rather than validate assumptions. Explain the why behind decisions — assume the user is learning, not just executing. Flag significant actions before taking them.