Harden Calm Filters surface before Track 3

- Add API test layer (TestClient): bad prefs -> 200, mute affects feed,
  avoid-term filters, brief filters down, counts match filtered feed.
- Render article cards via the DOM API (textContent) instead of HTML string
  interpolation, and only allow http(s) hrefs — defense-in-depth XSS guard for
  when the feed faces untrusted sources publicly.
- Refresh the stale README Next Steps to reflect what's done vs ahead.

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

README.md

@@ -178,11 +178,21 @@ run missed while the machine was off is caught up on the next boot.
 
 ## Next Steps
 
-1. Run the poller for a few days and inspect which sources produce useful candidates.
-2. Add source-level quality notes and deactivate noisy feeds.
-3. Replace or supplement `heuristic-v0` with a local model classifier.
-4. Add a daily brief builder that selects 5 items using scores and source diversity.
-5. Add a small web/API layer once the ingest data looks trustworthy.
+Done so far: RSS/Atom ingestion with exact + semantic dedup, heuristic + local-LLM
+classification with topic/flavor tagging, the daily brief, the FastAPI web/API layer
+and site, scheduled `cycle` via systemd, a pytest suite, and device-local Calm Filters.
+
+Still ahead:
+
+1. **Supervised source pipeline** — paste a feed URL, preview a scored sample
+   (freshness, acceptance rate, topic/flavor mix, cortisol/ragebait/PR averages,
+   example items), then add to quarantine before it can reach the main feed.
+2. **Learned "Less like this" weighting** — replace the interim flavor-pause with
+   real preference down-ranking.
+3. **Corpus rebalancing** — add calm/feelgood sources (currently science-heavy).
+4. **Retention/pruning** — soft-delete + time-window indexes as the corpus grows
+   toward ~10k articles (don't rush; not yet needed).
+5. **Go-public hardening** — TLS via a reverse proxy, then a domain.
 
 ## Local Model Configuration