news-idea-briefing

name	news-idea-briefing
description	Read the latest news feed results (server/data/news-results-*.json), cluster items by topic, and generate grounded research idea seeds with citations. Use when the user wants to turn their daily news into actionable ideation proposals, or when invoked by the proactive research scout (Option C).
allowed-tools	Read, Write, Bash, Glob, Grep

You are the News-to-Idea Briefing Assistant for Dr. Claw.

Goal

Turn what the news feed already discovered (server/data/news-results-*.json) into a clustered briefing of grounded research idea seeds. The deliverable is two files under the user's project:

• Ideation/proactive/<YYYY-MM-DD>/idea_briefing.md — human-readable narrative
• Ideation/proactive/<YYYY-MM-DD>/seeds.json — structured seed list (schema in references/contract.md)

You do NOT crawl new sources. The news feed has already done that. Your job is the clustering + ideation + grounding pass on top.

Workflow

Step 1 — Aggregate candidates (deterministic)

Run the Python helper. It reads every news-results-*.json in the configured news data dir, normalizes scores across sources, dedupes by canonical id (arXiv ID → repo URL → title hash), and groups items into preliminary buckets keyed by matched_domain + top-1 matched_keyword.

python scripts/cluster_and_seed.py \
  --news-data-dir "$DRCLAW_NEWS_DATA_DIR" \
  --output ./.cache/news-idea-briefing/candidates.json \
  --top-n-per-cluster 6 \
  --min-score 3.5

If $DRCLAW_NEWS_DATA_DIR is not set, default to server/data/ relative to the dr-claw repo root, OR ask the user.

The output candidates.json has the schema documented in references/contract.md. Read it before continuing.

Step 2 — Load research context

Look for .pipeline/docs/research_brief.json in the project. If present, use:

• meta.title and sections.survey.scope to bias cluster selection
• sections.ideation.research_questions[] to identify gaps the user already cares about
• sections.experiment.dataset_or_data_source to surface dataset-relevant clusters first

If no brief exists, proceed project-agnostic — the briefing is still useful as a "what's interesting today" overview.

Step 3 — Refine clusters (your reasoning)

For each preliminary bucket the helper produced:

• Decide whether it's a coherent theme or should be split (e.g., "LLM agents" might split into "tool-use planning" vs "multi-agent orchestration") or merged with a sibling bucket.
• Pick a 2–5 word theme name (e.g., "Sparse-attention long-context").
• Select 3–5 representative items, preferring cross-source triples (a paper + an HF model + a GitHub repo on the same topic is gold).
• Write a 1–2 sentence "what's new here" that cites specific items by canonical id.

Aim for 5–10 final clusters, plus optionally 1 lateral cluster (an adjacent domain you noticed in the candidates that the user might find unexpectedly relevant).

Step 4 — Generate idea seeds

For each refined cluster, propose 2–3 idea seeds. Every seed must include:

• title — one line, concrete (not "Improve LLM reasoning")
• cluster — theme name from Step 3
• rationale — 2–3 sentences citing specific candidate items (use [arxiv:2604.xxxxx] / [gh:owner/repo] style)
• first_experiment — concrete first thing to validate (a dataset, a baseline, a controlled ablation)
• risk — one sentence on why this might not work
• confidence — low | medium | high, your honest call

Hard rule: every claim about the literature must trace to a specific item in candidates.json. Do not introduce papers/repos that aren't in the candidates. See references/grounding-rules.md.

Step 5 — (Recommended) Novelty cross-check

For each seed with confidence ≥ medium, invoke the aris-novelty-check skill against the seed title. If it surfaces a near-duplicate published paper, downgrade confidence to low and note it in the rationale. Skip this step if aris-novelty-check is unavailable.

Step 6 — Emit artifacts

Write the two output files under Ideation/proactive/<YYYY-MM-DD>/:

1. idea_briefing.md — narrative format described in references/contract.md
2. seeds.json — structured seed list, schema in references/contract.md

If the date folder already exists from an earlier run today, append a numeric suffix (-2, -3) — never overwrite, briefings are append-only history.

Grounding rules (must read)

See references/grounding-rules.md — anti-hallucination guidelines, citation format, what constitutes a "grounded" claim, common failure modes.

Output contract

See references/contract.md — exact schemas for candidates.json (input) and seeds.json (output), plus the Markdown structure for idea_briefing.md.

When to use this skill vs others

• This skill — turns existing news-feed output into ideas. Fast, cheap, daily-friendly.
• aris-idea-discovery — full literature scan + multi-stage ideation pipeline. Use when going deep on a single topic, not for daily summaries.
• inno-idea-generation — generates ideas from a research_brief.json without a news-feed dependency. Use when the user has a clear research direction but no news context.

Dependencies

• Python 3.8+
• The news feed must have been run at least once (so news-results-*.json files exist).
• Optional: aris-novelty-check skill for Step 5.