--- name: p-news-briefing license: MIT description: Use when the user asks for news, wants a briefing, says "/news-briefing", or asks to aggregate recent information on any topic. Triggers on requests like "what's happening with AI", "get me news on crypto", "news briefing on climate". allowed-tools: WebSearch Task Bash Write argument-hint: " [--depth quick|deep]" compatibility: Requires access to the internet metadata: author: jackchuka scope: personal layer: workflow confirms: - save briefing to filesystem skillctx: version: "0.1.0" --- # News Briefing ## Setup Locate this skill's directory (the folder containing this SKILL.md), then run the resolver script from there: ```bash python /scripts/skillctx-resolve.py resolve p-news-briefing ``` The resolver outputs each binding as `key: value` (one per line). Substitute each `{binding_key}` placeholder below with the resolved value. If any values are missing or the user requests changes, use: ```bash python /scripts/skillctx-resolve.py set p-news-briefing ``` Aggregate recent news on any topic(s) into structured markdown files. ## Invocation - `/news-briefing ai, crypto` -- comma-separated topics - `/news-briefing ai --depth quick` -- with explicit depth - Conversational: "get me news on AI and crypto" ## Depth - **deep** (default): News + market/people reactions, sourced links, quotes, ~5 min read - **quick**: Headlines + brief context, 5-10 bullets with links, ~2 min read ## Flow 1. **Parse input**: Extract topic(s) and depth. Default depth is `deep`. 2. **Normalize topics**: Convert to URL-safe slugs for filenames (e.g., "artificial intelligence" -> `ai`, "open source" -> `open-source`). 3. **Create date directory**: `{notebook_daily_dir}YYYY-MM-DD/news/` 4. **Deduplicate against previous briefings** (parallelize if possible): Before researching, check for existing briefings on the same topic-slug in recent `daily/*/news/` directories (scan the last 14 days). Run dedup scans for all topics in parallel. Read any found files. Stories already covered in a previous briefing should be **skipped entirely** unless there is a meaningful follow-up (e.g., new data, reversal, sequel event). When a follow-up exists, write it as its own section and briefly note it builds on prior coverage — do not repeat the original story. 5. **Research directly** using WebSearch. Process all topics in parallel (parallelize if possible): after the dedup scan completes for all topics, dispatch all per-topic research tasks concurrently as a fan-out, then collect results and summarize. ### Per-Topic Research (parallelize if possible) IMPORTANT: Recency is critical. Follow these rules strictly: - **Always use today's exact date** (YYYY-MM-DD) to construct queries. Never use just a year or month alone. - **Prefer "today", "yesterday", "past 24 hours", "past 48 hours"** in queries — these terms signal freshness to search engines far better than month/year. - **Discard stale results**: After gathering search results, check publication dates. Only include stories from the **last 7 days** (for deep) or **last 3 days** (for quick). If a result has no visible date, deprioritize it. - **If initial results are stale**, run follow-up queries with stricter time language (e.g., "today", "yesterday", site:reuters.com OR site:bloomberg.com). **For deep depth:** Phase 1 - Breaking/recent news: Run 3 WebSearch queries in parallel: - "[TOPIC] news today [Full Month Day, Year]" (e.g., "AI news today February 6, 2026") - "[TOPIC] latest news this week [Month Year]" - "[TOPIC] breaking developments [Month Day Year]" Phase 2 - Reactions & analysis: Run 2-3 WebSearch queries in parallel: - "[TOPIC] market reaction today [Month Year]" - "[TOPIC] social reaction today [Month Year]" - "[TOPIC] analyst reaction [Month Day Year]" - "[TOPIC] expert opinion latest [Month Year]" Phase 3 - Fill gaps (only if needed): If Phase 1-2 returned fewer than 3 distinct stories, run 1-2 more targeted queries: - "[TOPIC] [specific subtopic from earlier results] [Month Day Year]" - site:reuters.com OR site:apnews.com "[TOPIC] [Month Year]" **Graceful failure**: If a WebSearch query fails or returns no results, note the gap and continue with available data. Include a footer note in the output listing any failed queries so the reader knows coverage may be incomplete. Phase 4 - Write output: Combine into structured markdown with: - YAML frontmatter: topic, date, depth - Major stories as H2 sections (each must include publication date) - Market data (stock moves, valuations) where relevant - Named quotes from analysts, CEOs, social media - Inline source links as markdown hyperlinks - A "Big Picture" H2 summary at the bottom **For quick depth:** Run 3 WebSearch queries in parallel: - "[TOPIC] news today [Full Month Day, Year]" - "[TOPIC] headlines this week [Month Year]" - "[TOPIC] latest [Month Day Year]" Then write a concise markdown file with: - YAML frontmatter: topic, date, depth - 5-10 bullet points, each a headline with 1-2 sentences of context - Each bullet must include the publication date (e.g., "Feb 5") - Inline source links as markdown hyperlinks - Discard any results older than 3 days ### Output Format ```yaml --- topic: Topic Name date: YYYY-MM-DD depth: deep --- ``` ### Output Path ``` {notebook_daily_dir}YYYY-MM-DD/news/.md ``` 6. **Summarize**: After all topics are written, tell the user what files were created and give a one-line summary per topic.