content-research-brief
installsforks
How to install content-research-brief?
affitor/affiliate-skills/content-research-brief
$npx -y skills add Affitor/affiliate-skills --skill content-research-briefResearch trending topics, collect source articles, and generate a structured research brief for content creation. Stop writing from thin air — write from real sources. Use this skill when the user wants to research a topic before writing, collect sources for an article, create a
SKILL.md
| 1 | # Content Research Brief |
| 2 | |
| 3 | Research a topic by collecting 5-10 real source articles, auto-tagging them by theme, |
| 4 | extracting key data points, and synthesizing unique content angles. The output is a |
| 5 | structured research brief that any downstream content skill can consume. |
| 6 | |
| 7 | **The problem this solves:** Most AI-written affiliate content is generic because it's |
| 8 | written from the model's training data — not from real, current sources. This skill |
| 9 | forces research-first content creation: find real articles, extract real data, then |
| 10 | write from those sources. The result is content with specific stats, real quotes, and |
| 11 | current information that readers (and Google) actually value. |
| 12 | |
| 13 | Inspired by the [content-pipeline](https://github.com/Affitor/content-pipeline) approach: |
| 14 | Topic → Search → Select sources → Synthesize → Write with context. |
| 15 | |
| 16 | ## Stage |
| 17 | |
| 18 | This skill belongs to Stage S2: Content — but acts as the research foundation for all content skills. |
| 19 | |
| 20 | ## When to Use |
| 21 | |
| 22 | - Before writing any article, blog post, or long-form content |
| 23 | - When you need current data and stats about a topic (not just AI-generated claims) |
| 24 | - When creating comparison content (need real feature/pricing data from sources) |
| 25 | - When writing about a product launch, funding round, or industry trend |
| 26 | - After `trending-content-scout` identifies a topic — research it deeper |
| 27 | - When you want unique angles: N sources → N different content pieces |
| 28 | |
| 29 | ## Input Schema |
| 30 | |
| 31 | ```yaml |
| 32 | topic: string # (required) "HeyGen AI video tool", "email marketing trends 2024" |
| 33 | source_count: number # (optional, default: 7) How many sources to collect (3-10) |
| 34 | source_types: string[] # (optional, default: ["news", "blog"]) |
| 35 | # Options: "news" | "blog" | "linkedin" | "youtube" | "reddit" | "academic" |
| 36 | freshness: string # (optional, default: "month") "day" | "week" | "month" | "year" | "any" |
| 37 | product: object # (optional) Focus research on a specific product |
| 38 | name: string # "HeyGen" |
| 39 | url: string # "https://heygen.com" |
| 40 | language: string # (optional, default: "en") "en" | "vi" | any ISO 639-1 code |
| 41 | angle_count: number # (optional, default: 3) How many unique content angles to generate |
| 42 | ``` |
| 43 | |
| 44 | ## Workflow |
| 45 | |
| 46 | ### Step 1: Search for Sources |
| 47 | |
| 48 | Execute multiple searches to find diverse, high-quality sources: |
| 49 | |
| 50 | ``` |
| 51 | Primary search: |
| 52 | web_search "[topic]" → top results |
| 53 | |
| 54 | Source-type-specific searches: |
| 55 | IF "news" in source_types: |
| 56 | web_search "[topic] news [current year]" → recent news articles |
| 57 | IF "blog" in source_types: |
| 58 | web_search "[topic] blog review analysis" → in-depth blog posts |
| 59 | IF "linkedin" in source_types: |
| 60 | web_search "[topic] site:linkedin.com" → LinkedIn posts/articles |
| 61 | IF "youtube" in source_types: |
| 62 | web_search "[topic] site:youtube.com" → YouTube videos with descriptions |
| 63 | IF "reddit" in source_types: |
| 64 | web_search "[topic] site:reddit.com" → Reddit discussions with real user opinions |
| 65 | IF "academic" in source_types: |
| 66 | web_search "[topic] research study data statistics" → data-heavy sources |
| 67 | |
| 68 | Product-specific (if product provided): |
| 69 | web_search "[product.name] review [current year]" |
| 70 | web_search "[product.name] alternatives comparison" |
| 71 | web_search "[product.name] pricing features" |
| 72 | web_search "[product.name] news launch update" |
| 73 | ``` |
| 74 | |
| 75 | Collect 15-20 search results, then filter down to `source_count` best sources. |
| 76 | |
| 77 | ### Step 2: Fetch and Extract Source Content |
| 78 | |
| 79 | For each selected source: |
| 80 | 1. `web_fetch [url]` → extract full article text |
| 81 | 2. If fetch fails (paywall, timeout) → use search snippet as summary, note limitation |
| 82 | 3. Extract from each source: |
| 83 | - **Title** and **URL** |
| 84 | - **Published date** (if available) |
| 85 | - **Key data points**: stats, numbers, percentages, dollar amounts |
| 86 | - **Key quotes**: noteworthy statements from experts or users |
| 87 | - **Main argumen |
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