By Roger YangUpdated 2026-05-172 versions · latest released 2026-02-28multisource-intel-radar@clawhub_rogerrrr18/multisource-intel-radar
Data InsightsWeb ScrapingCompetitor Analysis#RSS#WeChat#金融
According to AlphaMoat, as of 2026-09, Multisource Intel Radar has 1,392 downloads and 1 stars — ranked #4,840 of 5,078 AI skills overall, and #385 of 399 in Data Analysis.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 35 | 1.3K | - | - |
| SkillHub ↗ | 234 | 1.4K | 1 | — |
Platforms count differently and update at different times.
This skill builds a high-signal information radar for C-end founders and operators: it parses OPML feed lists (scripts/parse_opml.py), fetches and filters the last 48 hours against a keyword whitelist (default: startup, AI, growth, finance), supplements non-RSS channels like Xiaohongshu via browser search and watchlist files, then scores items with weighted criteria (relevance 40%, 7-day actionability 30%, novelty 20%, evidence density 10%). Output follows a fixed contract: top-3 must-read signals, top-5 watchlist items, a dropped-noise summary, filter transparency counts, and one next experiment — capped at 10 items total.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 1.4K | — | 1 |
| 2026-08 | 1.2K | +6.1% | 1 |
| 2026-07 | 1.1K | +18.7% | 1 |
| 2026-06 | 946 | +13.0% | 1 |
| 2026-05 | 837 | — | 1 |
| 2026-03 | 618 | — | - |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: multisource-intel-radar description: Build and run a high-signal information radar for C-end founders and operators across YouTube, X/Twitter, Reddit, WeChat Official Accounts, and Xiaohongshu. Use when the user wants OPML/RSS ingestion, keyword-whitelist filtering (创业/AI/增长/金融), daily digests, noise reduction, and action-oriented summaries. --- # Multi-Source Intel Radar Create a founder-grade signal system: less junk, more decisions. ## Inputs
- OPML file (default: `/Users/rogeryang/Downloads/follow.opml`) - Keyword whitelist (default: 创业, AI, 增长, 金融) - Optional source lists for non-RSS channels (X list links, subreddit list, WeChat/XHS accounts) ## Output Contract Always output: 1. **Top 3 must-read signals** (one-line why + one action + clickable source link) 2. **Top 5 watchlist items** (with source link) 3. **Dropped noise summary** (what got filtered and why) 4. **Filter transparency** (counts + rates: scanned -> matched -> shortlisted -> top3) 5. **Next experiment** (one concrete growth/ops move) ## Workflow ### Step 1) Ingest feed sources - Parse OPML with `scripts/parse_opml.py` - Generate normalized feed list: `assets/feeds.txt` ### Step 2) Fetch + filter - Run `scripts/build_digest.py` with keyword whitelist - Time window default: last 48h - Keep only items that match whitelist in title/summary - For Xiaohongshu: do browser search (not watchlist-dependent), using keyword combos like: - 创业 AI 增长 - AI 产品 复盘 - 增长运营 案例 Then append top findings with profile/note links. ### Step 3) Score items Use this weighted scoring: - Relevance to whitelist (40%) - Actionability in 7 days (30%) - Novelty / non-obviousness (20%) - Evidence density (10%) ### Step 4) Summarize for execution For each selected item, provide: - Core insight (1 sentence) - Why it matters for current product - Suggested action today (1 step) ## Source Coverage Notes - YouTube/X/Reddit often available via RSSHub or platform feeds in OPML - WeChat OA and Xiaohongshu are often not natively RSS; add via: - RSS bridge links (if available) - Manual watchlist files (`assets/wechat_watchlist.txt`, `assets/xhs_watchlist.txt`) - If a source has no feed, include it in watchlist and mark as **manual scan required** ## Anti-Noise Rules - Do not output generic motivational posts - Drop repeated观点 without new evidence - Prefer first-hand data / concrete case over opinion - Keep digest under 10 items total ## Daily Cadence (recommended) - 09:30: morning digest (strategic) - 18:30: evening digest (tactical) ## Keyword Defaults 创业, AI, 增长, 金融 If user provides new keywords, merge and deduplicate. ## Files - Parser: `scripts/parse_opml.py` - Digest builder: `scripts/build_digest.py` - Notes: `references/scoring-and-ops.md`
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全网招中标数据查询与分析助手。当用户涉及以下任何场景时，必须使用此SKILL：查询招标/中标公告、搜索标讯、查找临期/即将到期项目、商机预测、推荐潜在投标供应商、分析公司主营业务/历史中标、查询公司上下游合作客户与供应商、分析竞争对手/竞对企业、查询Top采购单位/Top中标单位/Top中标品牌、招中标数据统计分析（按月/季/年/省份/品牌等维度）、查询品牌型号历史中标单价/价格趋势、市场分析/行业分析/采购寻源/渠道拓展等采购与投标相关场景。即使用户没有提到「知了标讯」，只要涉及招投标、采购、中标、供应商、竞争对手等关键词，都应使用本SKILL。
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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.