agents: retro loop — "@pm retro" distills learnings into LEARNINGS.md

New learning step: ask @pm for a retrospective on any issue and the system
turns what happened into prompt-visible rules for future runs.

- run-agent.sh: @pm gains a RETRO marker (emit only when the maintainer asks);
  LEARNINGS.md (caller repo root, capped at 4KB) is injected into EVERY agent's
  prompt as "TEAM LEARNINGS" — the feedback loop that makes delegation more
  robust over time.
- publish.sh: on @pm's RETRO marker, open a "retro: issue #N" issue pointing at
  the issue + its PR (state=all resolve, works after merge) and trigger @senior
  on it (has gitea-api to read both threads). The retro produces a LEARNINGS.md
  PR through the NORMAL choreography (senior → pm → qa), so retros are reviewed
  like any change. Strip the RETRO marker from visible replies.
- publish.sh: bounce counter now counts only @qa-authored comments matching the
  exact trigger template — on PR #84 it jumped 1/3 → 3/3 because a qa review
  QUOTED our own "(fix attempt …)" template from the diff, halving the fix
  budget. Template + regex pinned together with a sync note.
- README: document the retro loop.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

README.md

@@ -35,6 +35,15 @@ deploy-host SSH skill, live in the consuming repo under `.gitea/agent-skills/`
 `@pm` is the only agent that ever merges, and only under the `autopilot` label (its kill switch:
 remove the label mid-flight and the next step reverts to human control).
 
+### Retros — the learning loop
+
+Ask `@pm` for a retrospective on any issue (e.g. **"@pm run a retro"**, typically when merging). The
+automation opens a `retro: issue #N` issue and assigns `@senior`, who reads the full issue + PR
+threads (via the `gitea-api` skill), distills what went wrong or slow, and appends one-line
+`symptom → rule` bullets to **`LEARNINGS.md`** at the repo root — through the normal PR choreography,
+so the retro itself gets reviewed. `LEARNINGS.md` is injected into **every agent's prompt** on every
+run, so the lessons actually change future behavior (better delegation, fewer repeated misses).
+
 ### Per-agent skill scoping
 
 Skills load **on-demand**: only a skill's one-line `description` ever appears in an agent's