feat: recursive self-improvement — operational learning + full skill wiring (v0.13.8.0) (#647)

* refactor: remove dead contributor mode, replace with operational self-improvement slot

Contributor mode never fired in 18 days of heavy use (required manual opt-in
via gstack-config, gated behind _CONTRIB=true, wrote disconnected markdown).

Removes: generateContributorMode(), _CONTRIB bash var, 2 E2E tests, touchfile
entry, doc references. Cleans up skip-lists in plan-ceo-review, autoplan,
review resolver, and document-release templates.

The operational self-improvement system (next commit) replaces this slot with
automatic learning capture that requires no opt-in.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat: operational self-improvement — every skill learns from failures

Adds universal operational learning capture to the preamble completion protocol.
At the end of every skill session, the agent reflects on CLI failures, wrong
approaches, and project quirks, logging them as type "operational" to the
learnings JSONL. Future sessions surface these automatically.

- generateCompletionStatus(ctx) now includes operational capture section
- Preamble bash shows top 3 learnings inline when count > 5
- New "operational" type in generateLearningsLog alongside pattern/pitfall/etc
- Updated unit tests + operational seed entry in learnings E2E

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat: wire learnings into all insight-producing skills

Adds LEARNINGS_SEARCH and/or LEARNINGS_LOG to 10 skill templates that
produce reusable insights but were previously disconnected from the
learning system:

- office-hours, plan-ceo-review, plan-eng-review: add LOG (had SEARCH)
- plan-design-review: add both SEARCH + LOG (had neither)
- design-review, design-consultation, cso, qa, qa-only: add both
- retro: add SEARCH (had LOG)

13 skills now fully participate in the learning loop (read + write).
Every review, QA, investigation, and design session both consults prior
learnings and contributes new ones.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* test: add operational-learning E2E test (gate-tier)

Validates the write path: agent encounters a CLI failure, logs an
operational learning to JSONL via gstack-learnings-log. Replaces the
removed contributor-mode E2E test.

Setup: temp git repo, copy bin scripts, set GSTACK_HOME.
Prompt: simulated npm test failure needing --experimental-vm-modules.
Assert: learnings.jsonl exists with type=operational entry.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix: learnings-show E2E slug mismatch — seed at computed slug, not hardcoded

The test seeded learnings at projects/test-project/ but gstack-slug computes
the slug from basename(workDir) when no git remote exists. The agent's search
looked at the wrong path and found nothing.

Fix: compute slug the same way gstack-slug does (basename + sanitize) and
seed the learnings there.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* chore: bump version and changelog (v0.13.8.0)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

ARCHITECTURE.md

@@ -217,7 +217,7 @@ Every skill starts with a `{{PREAMBLE}}` block that runs before the skill's own
 
 1. **Update check** — calls `gstack-update-check`, reports if an upgrade is available.
 2. **Session tracking** — touches `~/.gstack/sessions/$PPID` and counts active sessions (files modified in the last 2 hours). When 3+ sessions are running, all skills enter "ELI16 mode" — every question re-grounds the user on context because they're juggling windows.
-3. **Contributor mode** — reads `gstack_contributor` from config. When true, the agent files casual field reports to `~/.gstack/contributor-logs/` when gstack itself misbehaves.
+3. **Operational self-improvement** — at the end of every skill session, the agent reflects on failures (CLI errors, wrong approaches, project quirks) and logs operational learnings to the project's JSONL file for future sessions.
 4. **AskUserQuestion format** — universal format: context, question, `RECOMMENDATION: Choose X because ___`, lettered options. Consistent across all skills.
 5. **Search Before Building** — before building infrastructure or unfamiliar patterns, search first. Three layers of knowledge: tried-and-true (Layer 1), new-and-popular (Layer 2), first-principles (Layer 3). When first-principles reasoning reveals conventional wisdom is wrong, the agent names the "eureka moment" and logs it. See `ETHOS.md` for the full builder philosophy.