Track 3: read-only source preview (vet a feed before adding)

- feeds.preview_feed(): fetch + score a sample WITHOUT persisting; returns
  freshness, acceptance rate, cortisol/ragebait/PR averages, and example
  accepted/rejected items. With an LLM client it also returns topic/flavor mix
  and the model's (accurate) acceptance view.
- CLI 'preview-source URL [--sample] [--classify]'.
- API 'GET /api/source-preview?url=&sample=&classify=' with an http(s)-only
  guard (SSRF note left for go-public hardening).
- Site 'Suggest a source' panel with Quick check (heuristic, instant) and Deep
  check (model, accurate), rendered DOM-safely.
- Tests: network-free preview_feed tests via monkeypatched fetch (45 total).
- README documents the command, endpoint, and updated roadmap.

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

goodnews/cli.py

@@ -9,7 +9,14 @@ from pathlib import Path
 from .briefs import build_daily_brief, show_brief
 from .db import connect, init_db
 from .dedup import DEFAULT_THRESHOLD, DEFAULT_WINDOW_DAYS, dedup as run_dedup
-from .feeds import fetch_feed, parse_feed, poll_all_sources, poll_due_sources, poll_source
+from .feeds import (
+    fetch_feed,
+    parse_feed,
+    poll_all_sources,
+    poll_due_sources,
+    poll_source,
+    preview_feed,
+)
 from .llm import LocalModelClient, classify_articles
 from .scoring import score_article
 from .sources import load_sources, upsert_sources
@@ -52,6 +59,13 @@ def main() -> None:
     check_feeds_parser = subparsers.add_parser("check-feeds", help="Fetch and parse each feed, reporting health")
     check_feeds_parser.add_argument("--all", action="store_true", help="Include inactive sources")
 
+    preview_parser = subparsers.add_parser("preview-source", help="Score a sample of a feed without adding it")
+    preview_parser.add_argument("url", help="Feed URL to preview")
+    preview_parser.add_argument("--sample", type=int, default=25)
+    preview_parser.add_argument("--classify", action="store_true", help="Also classify with the local model (slower)")
+    preview_parser.add_argument("--base-url", help="OpenAI-compatible base URL (with --classify)")
+    preview_parser.add_argument("--model", help="Local model name (with --classify)")
+
     runs_parser = subparsers.add_parser("list-runs", help="Show recent ingest runs")
     runs_parser.add_argument("--limit", type=int, default=20)
 
@@ -136,6 +150,10 @@ def main() -> None:
         source_report(conn)
     elif args.command == "check-feeds":
         check_feeds(conn, include_inactive=args.all)
+    elif args.command == "preview-source":
+        client = llm_client_from_args(args) if args.classify else None
+        preview = preview_feed(args.url, sample=args.sample, client=client)
+        print_preview(preview)
     elif args.command == "list-runs":
         list_runs(conn, limit=args.limit)
     elif args.command == "rescore":
@@ -243,6 +261,25 @@ def list_recent(conn: sqlite3.Connection, limit: int, accepted_only: bool) -> No
         print(f"  {row['canonical_url']}")
 
 
+def print_preview(p: dict) -> None:
+    mode = "model" if p["classified"] else "heuristic"
+    print(f"Preview of {p['url']}  ({mode})")
+    print(f"  sampled={p['sampled']} accepted={p['accepted']} ({p['acceptance_rate']*100:.0f}%)")
+    print(f"  freshness: newest={p['newest_published'] or 'unknown'} in_last_7d={p['recent_7d']}")
+    print(f"  averages: cortisol={p['avg_cortisol']} ragebait={p['avg_ragebait']} pr_risk={p['avg_pr_risk']}")
+    if p["topic_mix"]:
+        print(f"  topics: {p['topic_mix']}")
+        print(f"  flavors: {p['flavor_mix']}")
+    if p["examples_accepted"]:
+        print("  would accept:")
+        for t in p["examples_accepted"]:
+            print(f"    + {t[:80]}")
+    if p["examples_rejected"]:
+        print("  would skip:")
+        for ex in p["examples_rejected"]:
+            print(f"    - {ex['title'][:70]} ({ex['reason']})")
+
+
 def check_feeds(conn: sqlite3.Connection, include_inactive: bool = False) -> None:
     where = "" if include_inactive else "WHERE active = 1"
     rows = conn.execute(f"SELECT name, feed_url FROM sources {where} ORDER BY name").fetchall()