Release 1.1.3 — long skills keep their later steps

Fix release for 1.1.2: the 14 longest skills keep their later phases
after a compaction, a question nobody answered is never taken as an
answer, settings read the same from a subfolder, the commit check works
for a project in a subfolder of a larger repository, every skill opens
with a title, and the shipped allow rules no longer approve deleting a
branch or writing files without asking. Details in CHANGELOG.md; upgrade
steps in UPGRADING.md (v1.1.2 → v1.1.3).

Refs #83
Refs #133

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0185en4t76fPn7315q4c3nko

.claude/skills/setup-engine/references/6-knowledge-gap.md

@@ -0,0 +1,38 @@
+# /setup-engine — Section 6: Determine Knowledge Gap
+
+> Part of `/setup-engine`. `SKILL.md` names when to read this file; the settings it
+> resolved and the rules under its later headings still apply here.
+
+## 6. Determine Knowledge Gap
+
+Check whether the engine version is likely beyond the LLM's training data.
+
+**Known approximate coverage** — the same figures the shipped
+`docs/engine-reference/*/VERSION.md` files record:
+- LLM knowledge cutoff: **May 2025**
+- Godot: training data likely covers up to ~4.3
+- Unity: training data likely covers up to ~2022 LTS (2022.3)
+- Unreal: training data likely covers up to ~5.3
+
+> **This table goes stale silently, and a stale table fails in the dangerous
+> direction only if it is too *new*.** A cutoff left unchanged for a year after
+> it stopped being true over-classifies risk — safe, but every project then pays
+> for full reference docs it may not have needed.
+> The opposite error is the harmful one: a cutoff claimed *later* than the model's
+> actual one marks post-cutoff versions LOW RISK and suppresses the reference
+> docs that exist to stop invented APIs.
+>
+> **If the model running this skill states an earlier training cutoff than the
+> one above, do not trust the table.** Say so, and treat the engine version as
+> `HIGH RISK` regardless of the comparison — a cutoff the model does not have is
+> not a cutoff that was met.
+
+Compare the user's chosen version against these baselines:
+
+- **Within training data** → `LOW RISK` — reference docs optional but recommended
+- **Near the edge** → `MEDIUM RISK` — reference docs recommended
+- **Beyond training data** → `HIGH RISK` — reference docs required
+
+Inform the user which category they're in and why.
+
+---