hn-digest

Fetch top Hacker News stories, pause for human editorial approval, and publish a curated Markdown digest using examples/hn_digest/actions.py.

작성자를 위한 경고

"name" should match the name of the directory that holds SKILL.md
Not listed through the skills extension: the directory must be named after the skill.

Executes the 3-stage Hacker News curation workflow using the Python helper functions in examples/hn_digest/actions.py.

Stage 1 — Fetch Top Stories (fetch_top_stories):
- Call actions.fetch_top_stories(payload) with {"offline": True, "limit": 3} (or live API if offline=False).
- Returns (out_dict, msg) where out_dict contains {"stories": [...], "count": int, "top_title": str, "top_score": int, "source": str}.
- Persist out_dict under payload["outputs"]["fetch_top_stories"] so fetch_top_stories is not called again in Stage 3.
- Example invocation:
```
python3 -B -c "import json, sys; sys.path.insert(0, 'examples/hn_digest'); import actions; out, msg = actions.fetch_top_stories({'offline': True, 'limit': 3}); print(json.dumps({'outputs': {'fetch_top_stories': out}, 'message': msg}))"
```
Stage 2 — Human Editorial Gate (editorial_gate):
- MANDATORY GATE: Stop after Stage 1 and present top_title, top_score, and count to the human editor.
- Wait for their explicit approval and optional editor_note + output_path before executing Stage 3. Never auto-approve.
Stage 3 — Publish Digest (publish_digest):
- Condition: Run only if the editor approved Stage 2. Do not re-run fetch_top_stories.
- Call actions.publish_digest(payload) where payload contains:
  - "outputs": {"fetch_top_stories": <stage_1_out>, "editorial_gate": {"editor_note": "<note>", "output_path": "<path>"}}
- Writes the curated Markdown file atomically to output_path and returns ({"digest_path": str, "story_count": int, "simulated": bool}, msg).

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