Social Listening Brief
unifapi-agent/agents
When the user wants to monitor what people are publicly saying about a brand, product, category, or launch across social and news.
Scan social platforms for top-performing content by engagement before you create anything.
$ npx skills add Affitor/affiliate-skills --skill trending-content-scout -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Affitor/affiliate-skills trending-content-scout --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Affitor/affiliate-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research/trending-content-scout .claude/skills/trending-content-scout && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "trending-content-scout" agent skill from https://github.com/Affitor/affiliate-skills/tree/main/skills/research/trending-content-scout into .claude/skills/trending-content-scout/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trending-content-scout", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Affitor/affiliate-skills/tree/main/skills/research/trending-content-scoutType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Affitor/affiliate-skills --skill trending-content-scout -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Affitor/affiliate-skills trending-content-scout --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Affitor/affiliate-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/research/trending-content-scout .agents/skills/trending-content-scout && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "trending-content-scout" agent skill from https://github.com/Affitor/affiliate-skills/tree/main/skills/research/trending-content-scout into .agents/skills/trending-content-scout/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trending-content-scout", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Affitor/affiliate-skills --skill trending-content-scout -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Affitor/affiliate-skills trending-content-scout --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Affitor/affiliate-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/research/trending-content-scout .cursor/skills/trending-content-scout && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "trending-content-scout" agent skill from https://github.com/Affitor/affiliate-skills/tree/main/skills/research/trending-content-scout into .cursor/skills/trending-content-scout/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trending-content-scout", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Affitor/affiliate-skills.git --path skills/research/trending-content-scout--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Affitor/affiliate-skills --skill trending-content-scout -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Affitor/affiliate-skills trending-content-scout --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Affitor/affiliate-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/research/trending-content-scout .gemini/skills/trending-content-scout && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "trending-content-scout" agent skill from https://github.com/Affitor/affiliate-skills/tree/main/skills/research/trending-content-scout into .gemini/skills/trending-content-scout/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trending-content-scout", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Affitor/affiliate-skills trending-content-scoutInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Affitor/affiliate-skills --skill trending-content-scout -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Affitor/affiliate-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/research/trending-content-scout .github/skills/trending-content-scout && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "trending-content-scout" agent skill from https://github.com/Affitor/affiliate-skills/tree/main/skills/research/trending-content-scout into .github/skills/trending-content-scout/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trending-content-scout", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Affitor/affiliate-skills --skill trending-content-scout -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Affitor/affiliate-skills trending-content-scout --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Affitor/affiliate-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/research/trending-content-scout .opencode/skills/trending-content-scout && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "trending-content-scout" agent skill from https://github.com/Affitor/affiliate-skills/tree/main/skills/research/trending-content-scout into .opencode/skills/trending-content-scout/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trending-content-scout", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
trending-content-scoutScan social platforms for top-performing content by engagement before you create anything.
Trending Content Scout is an agent skill from Affitor/affiliate-skills. Scan social platforms for top-performing content by engagement before you create anything. Use this skill when the user wants to see what content is winning in a niche, find viral content patterns, research what's working on YouTube/TikTok/X/Reddit, benchmark engagement, discover content gaps, or says "what content is working for [topic]", "show me top performing content about [keyword]", "what's trending in [niche]", "find viral content about [product]", "content research for [keyword]", "what gets views in…
Its SKILL.md is about 5.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent
It sits in Marketing & SEO, covering Social media marketing. It works with Reddit, TikTok and YouTube. The repository describes itself as: 50 AI agent skills for affiliate marketing. Research trending content, write data-backed posts, generate infographics, build landing pages, deploy — full flywheel with social… The licence is MIT.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit e43bfae. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml and markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
heygen.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent
From compatibility in the SKILL.md frontmatter.
Trending Content Scout loads about 5.4k tokens when it runs. Until then it costs about 208 tokens; SKILL.md has 1,416 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from Affitor/affiliate-skills at commit e43bfae, republished under its MIT licence (© Affitor). 1,416 words, ~5,384 tokens.
.claude/skills/trending-content-scout/SKILL.md (or your agent's skills folder).Scan YouTube, TikTok, X, and Reddit for top-performing content by real engagement data. Find winning formats, hooks, and content gaps — before you create anything. Stop guessing what works. See what's already winning, then build on proven patterns.
This skill is the data foundation for the entire content pipeline. Run it first,
then feed its output into content-angle-ranker, viral-post-writer, tiktok-script-writer,
or any S2/S3 content skill.
This skill belongs to Stage S1: Research
keyword: string # (required) Search keyword — "AI video tools", "email marketing tips"
platforms: string[] # (optional, default: ["youtube", "tiktok"])
# Options: "youtube" | "tiktok" | "x" | "reddit"
sort_by: string # (optional, default: "engagement_score")
# Options: "views" | "likes" | "engagement_score" | "recency"
time_range: string # (optional, default: "30d") "7d" | "30d" | "90d" | "all"
limit: number # (optional, default: 20) Max content pieces to analyze
product: object # (optional) Specific product to focus on
name: string # "HeyGen"
url: string # "https://heygen.com"No api_config needed in input — skills auto-detect configuration from conversation
context, project settings, or CLAUDE.md. See shared/references/social-data-providers.md
for setup instructions.
Check if the user has API configuration available:
IF social_data_config exists in context/settings for a platform:
→ Use configured API for that platform
→ Structured data: exact views, likes, comments, shares
ELSE (default — no API):
→ Use web_search + web_fetch
→ Still effective — see fallback methods belowAPI mode (when configured):
For each platform in platforms:
See shared/references/social-data-providers.md for specific API endpoints and config.
web_search fallback (no API — default):
For YouTube:
web_search "[keyword] site:youtube.com" → top 10-15 video results
For each result: extract title, channel, view count from search snippet
Optional: web_fetch individual video pages for likes/comments (slower)
For TikTok:
web_search "[keyword] tiktok" → find popular TikTok content
web_search "[keyword] site:tiktok.com" → direct TikTok results
Extract: titles, creators, approximate view counts from snippets
For X:
web_search "[keyword] site:x.com" OR "[keyword] site:twitter.com" → top tweets
Extract: tweet text, author, engagement signals from snippets
For Reddit:
web_search "[keyword] site:reddit.com" → top Reddit discussions
web_fetch top results → extract upvotes, comments from page
web_search "reddit [keyword] top upvoted" → find popular threadsNote which data source was used — include in output for transparency.
For each content piece found, extract and normalize into a standard schema:
ContentItem:
title: string # Video title, tweet text (first line), post title
url: string # Direct link to content
platform: string # "youtube" | "tiktok" | "x" | "reddit"
creator: string # Channel name, @handle, username
views: number # View/impression count (0 if unavailable)
likes: number # Like/upvote count (0 if unavailable)
comments: number # Comment/reply count (0 if unavailable)
shares: number # Share/retweet count (0 if unavailable)
published_date: string # ISO date or relative ("3 days ago")
duration: string # Video duration ("2:34") — video only
engagement_score: number # Calculated — see formula below
content_format: string # Detected format (see classification below)
hook_type: string # Detected hook style (see classification below)Engagement Score Formula (consistent across all Affitor skills):
engagement_score = (likes × 2 + comments × 3 + shares × 5) / max(views, 1) × 1000Platform-specific adjustments:
(score × 2 + num_comments × 3) / max(score, 1) × 1000 (no share count)comments × 0.5 (not available via most APIs)views as the ranking signal and note that engagement_score is estimatedSee shared/references/social-data-providers.md for full formula documentation.
Content Format Classification:
Detect format from title and description:
Hook Type Classification:
Detect from first sentence/title:
Sort all collected content by the chosen sort_by parameter:
Take top limit results after sorting.
From the top content, extract actionable patterns:
Format Analysis:
For each content_format in top results:
count: how many of top 20 use this format
avg_engagement: average engagement_score for this format
best_example: highest engagement content in this formatHook Analysis:
For each hook_type in top results:
count: how many use this hook
avg_engagement: average engagement_score
best_example: highest engagement content with this hookDuration Analysis (video platforms only):
Group videos by duration buckets:
<30s, 30-60s, 60-120s, 2-5min, 5-10min, 10-20min, 20min+
For each bucket: count and average engagement
→ Identify optimal duration rangeCreator Analysis:
For each unique creator in top results:
content_count: how many pieces in top results
avg_engagement: average engagement score
platforms: which platforms they're on
dominant_format: their most-used formatGap Analysis:
This is the most strategically valuable output. Look for:
For gap analysis with web_search fallback:
web_search "[keyword] reddit questions" → find unanswered user questionsweb_search "[keyword] alternatives nobody talks about" → find underserved anglesSet benchmark ranges so user knows what "good" looks like:
engagement_benchmark:
sample_size: number # how many content pieces analyzed
median_views: number # 50th percentile views
median_engagement_score: number
top_10_percent_threshold:
views: number # views needed to be in top 10%
engagement_score: number # engagement_score needed for top 10%
platform_averages: # per-platform breakdown
youtube:
median_views: number
median_engagement: number
tiktok:
median_views: number
median_engagement: numberBefore presenting output, verify:
If any check fails, fix the output before delivering. Do not flag the checklist to the user.
Other skills can consume these fields from conversation context:
output_schema_version: "1.0.0"
keyword: string
platforms_scanned: string[]
data_source: "api" | "web_search" | "mixed" # transparency
total_content_analyzed: number
top_content: ContentItem[] # top results sorted by sort_by
pattern_analysis:
winning_formats:
- format: string # "comparison"
count: number # 9
percentage: number # 45
avg_engagement: number # 35.2
best_example:
title: string
url: string
engagement_score: number
winning_hooks:
- hook_type: string
count: number
avg_engagement: number
best_example:
title: string
url: string
optimal_duration:
range: string # "45-60 seconds"
platform: string # "tiktok"
avg_engagement: number
top_creators:
- name: string
platform: string
content_count: number
avg_engagement: number
dominant_format: string
content_gaps: string[] # specific, actionable gaps
engagement_benchmark:
sample_size: number
median_views: number
median_engagement_score: number
top_10_percent_threshold:
views: number
engagement_score: number
platform_averages: object
recommended_angles: string[] # top 3 content angles based on gaps + engagement
recommended_next_skill: string # "content-angle-ranker"## Trending Content Scout: [Keyword]
### Data Source
📊 **[API: YouTube Data API + RapidAPI TikTok | web_search (no API configured)]**
Scanned: [X] content pieces across [Y] platforms
Time range: [30 days]
---
### 🏆 Top Performing Content
| # | Title | Platform | Creator | Views | Eng. Score | Format | Hook |
|---|-------|----------|---------|-------|------------|--------|------|
| 1 | [Title] | YouTube | @creator | 150K | 42.3 | comparison | bold_claim |
| 2 | [Title] | TikTok | @creator | 800K | 38.1 | demo | demo_first |
| 3 | [Title] | YouTube | @creator | 95K | 35.7 | tutorial | question |
| ... | ... | ... | ... | ... | ... | ... | ... |
---
### 📈 Pattern Analysis
**Winning Formats:**
| Format | Count | % of Top 20 | Avg Engagement | Verdict |
|--------|-------|-------------|----------------|---------|
| Comparison | 9 | 45% | 35.2 | 🔥 Dominant — proven winner |
| Tutorial | 5 | 25% | 28.4 | ✅ Solid performer |
| Review | 4 | 20% | 22.1 | ⚡ Works but competitive |
| Listicle | 2 | 10% | 18.5 | ➖ Below average |
**Best Hooks:**
1. 🥇 **Bold claim** — "This tool replaced my $5K/mo agency" (avg engagement: 41.3)
2. 🥈 **Demo first** — Show end result in first 3 seconds (avg: 36.8)
3. 🥉 **Contrarian** — "Stop using X, use this instead" (avg: 33.2)
**Duration Sweet Spot:**
- TikTok: 45-60 seconds (avg engagement: 34.2)
- YouTube: 8-12 minutes (avg engagement: 31.5)
**Top Creators in This Space:**
| Creator | Platform | Pieces in Top 20 | Avg Engagement | Style |
|---------|----------|-------------------|----------------|-------|
| @creator1 | YouTube | 4 | 38.5 | In-depth comparisons |
| @creator2 | TikTok | 3 | 35.2 | Quick demos |
---
### 🕳️ Content Gaps (Opportunities)
1. **[Gap 1]:** Nobody comparing [Product A] vs [Product B] on TikTok — YouTube has 5 comparisons, TikTok has zero
2. **[Gap 2]:** No "honest cons" content — all top content is positive. Authentic negative review = differentiation
3. **[Gap 3]:** Missing "[keyword] for [specific audience]" — all content targets general audience
4. **[Gap 4]:** Top content is 4-6 months old — fresh 2024 take is an opportunity
5. **[Gap 5]:** Reddit has high engagement (avg score: 450) but no affiliate content → underserved platform
---
### 📏 Engagement Benchmark
| Metric | Median | Top 10% Threshold | Your Target |
|--------|--------|-------------------|-------------|
| Views | 12,000 | 85,000 | Beat median to start |
| Engagement Score | 18.5 | 45.0 | Aim for top 10% |
**Per Platform:**
| Platform | Median Views | Median Engagement |
|----------|-------------|-------------------|
| YouTube | 25,000 | 22.3 |
| TikTok | 45,000 | 16.8 |
---
### 🎯 Recommended Next Steps
Based on this data, the highest-opportunity path is:
1. **Run `content-angle-ranker`** — rank specific angles for [best platform]
2. **Create a [winning format]** using a [best hook] hook
→ Skill: `viral-post-writer` (format: [format], hook: [hook])
3. **Fill [Gap 1]** — this is the lowest-competition, highest-potential opportunity
→ Skill: `tiktok-script-writer` (if TikTok) or `comparison-post-writer` (if blog)shared/references/social-data-providers.md"Example 1:
User: "What content is working about HeyGen on TikTok?"
→ keyword: "HeyGen", platforms: ["tiktok"]
→ web_search "HeyGen tiktok" + "HeyGen site:tiktok.com" + "HeyGen TikTok viral"
→ Find 15 TikTok videos, extract view counts and creators
→ Pattern: demo_first hooks dominate (60%), 30-45s duration optimal
→ Gap: nobody doing "HeyGen for [specific profession]" content
→ Recommend: tiktok-script-writer with demo_first hook, 30s, angle: "HeyGen for real estate agents"
Example 2: User: "I want to create content about email marketing tools. What's performing well?" → keyword: "email marketing tools", platforms: ["youtube", "tiktok", "reddit"] → Scout all 3 platforms → YouTube: dominated by listicles ("Top 10 email marketing tools 2024") — avg 45K views → TikTok: very few results — gap opportunity → Reddit: high engagement on comparison threads in r/emailmarketing → Recommend: Fill TikTok gap with comparison format, or target Reddit with authentic discussion
Example 3:
User: "Scout trending content about AI writing tools, I have RapidAPI configured"
→ Use configured APIs for YouTube + TikTok
→ Get exact engagement data: views, likes, comments, shares
→ Engagement scores calculated precisely
→ Pattern: "I replaced my copywriter with AI" hook has 3x average engagement
→ Output includes exact benchmark: median 18K views, top 10% needs 120K+
→ Recommend: content-angle-ranker to pick best angle, then viral-post-writer
When this skill produces unexpected, incomplete, or incorrect output, generate a
skill_feedback block (see shared/references/feedback-protocol.md for full schema).
Skill-specific failure modes:
data_quality with the keyword used.data_quality, note which platforms had no metrics.wrong_output with the misclassified content.Auto-detect triggers:
top_content array has <5 items after scanning all platformsengagement_benchmark.sample_size < 1050% of
content_gapsare generic rather than specific
Report issues: GitHub Issues | Discussions
shared/references/social-data-providers.md — API configuration and provider optionsshared/references/flywheel-connections.md — master flywheel connection mapshared/references/affiliate-glossary.md — affiliate marketing terminologyshared/references/feedback-protocol.md — issue detection and reporting standardcontent-angle-ranker (S1) — full scout output for angle scoringviral-post-writer (S2) — pattern_analysis (winning formats, hooks, benchmark)tiktok-script-writer (S2) — top TikTok content + engagement datatwitter-thread-writer (S2) — top X threads + engagement datareddit-post-writer (S2) — top Reddit posts + engagement datacontent-pillar-atomizer (S2) — platform performance data for allocationcompetitor-spy (S1) — top_creators data (who's dominating this keyword)keyword-cluster-architect (S3) — engagement data per keyword for cluster prioritizationaffiliate-blog-builder (S3) — winning formats and gaps for blog content anglescompetitor-spy (S1) — competitor URLs/channels to analyze specificallyniche-opportunity-finder (S1) — niche keywords to scoutperformance-report (S6) — your content metrics to compare against benchmarkperformance-report provides your actual content metrics → compare against engagement_benchmark from this skill → identify where you're beating or trailing the benchmark → refine content strategy in the next scout runchain_metadata:
skill_slug: "trending-content-scout"
stage: "research"
timestamp: string
suggested_next:
- "content-angle-ranker"
- "viral-post-writer"
- "tiktok-script-writer"© Affitor, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/research/trending-content-scout of Affitor/affiliate-skills.
Open the folder on GitHubat commit e43bfae
Trending Content Scout next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Trending Content Scout this skillAffitor/affiliate-skills | 700 | — | ~5.4k | Automated safety check: Pass | MIT | |
| Social Listening Briefunifapi-agent/agents | 589 | — | ~2.7k | Automated safety check: Pass | MIT | |
| Paid Ads AuditAgriciDaniel/claude-ads | 9.8k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Influencer Discoverytigerless-labs/influencer-discovery | 212 | — | ~2.5k | Automated safety check: Notes | None | |
| Comment MiningScrapeCreators/social-media-research-skills | 3.4k | — | ~1k | Automated safety check: Notes | MIT | |
| Competitor Social ResearchScrapeCreators/social-media-research-skills | 3.4k | — | ~1.1k | Automated safety check: Notes | MIT |
unifapi-agent/agents
When the user wants to monitor what people are publicly saying about a brand, product, category, or launch across social and news.
AgriciDaniel/claude-ads
Runs a source-grounded paid advertising audit across up to 12 ad platforms, with parallel platform workers, deterministic scoring and a versioned JSON bundle.
tigerless-labs/influencer-discovery
Find the bloggers/creators who can help promote your work, capture their contact info, and append them to the target sheet in Google Sheets.
ScrapeCreators/social-media-research-skills
A skill your agent uses when the user wants to mine comments and replies for audience reactions, customer language, questions, objections, complaints, product ideas, buying intent, sentiment, or…
ScrapeCreators/social-media-research-skills
A skill your agent uses when the user wants to research competitors' social media strategy, compare brands or creators, find what content is working in a niche, identify content gaps, or produce a…
browser-act/skills
Finds a company's official website and social profiles from its name, or collects social links from a website URL, using BrowserAct templates run by a Python script.
Affitor/affiliate-skills
Live affiliate program data from openaffiliate.dev. An agent skill from Affitor/affiliate-skills.
Affitor/affiliate-skills
Research and evaluate affiliate programs to find the best ones to promote.
Affitor/affiliate-skills
Create a Linktree-style bio link hub page as a single self-contained HTML file.
Affitor/affiliate-skills
Set up affiliate conversion tracking with UTM parameters and link tagging.
Affitor/affiliate-skills
Generate affiliate performance reports with KPIs and recommendations.
Affitor/affiliate-skills
Build a single-product deep-dive showcase page as a self-contained HTML file.
Categories
Scan social platforms for top-performing content by engagement before you create anything. Trending Content Scout is an agent skill from Affitor/affiliate-skills. Scan social platforms for top-performing content by engagement before you create anything.
Trending Content Scout fits situations like: the user wants to see what content is winning in a niche; find viral content patterns; research whats working on YouTube/TikTok/X/Reddit; benchmark engagement.
Run `npx skills add Affitor/affiliate-skills --skill trending-content-scout -a claude-code`. Or copy the skill folder (skills/research/trending-content-scout in Affitor/affiliate-skills) into .claude/skills/trending-content-scout in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Affitor/affiliate-skills --skill trending-content-scout -a codex`. Or copy the skill folder (skills/research/trending-content-scout in Affitor/affiliate-skills) into .agents/skills/trending-content-scout in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Affitor/affiliate-skills --skill trending-content-scout -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/trending-content-scout, .gemini/skills/trending-content-scout, .github/skills/trending-content-scout and .opencode/skills/trending-content-scout in your project.
SKILL.md names no scripts, command-line tools or credentials: Trending Content Scout is instructions for the agent only. Compatibility (from SKILL.md): Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent.
SKILL.md names 1 domain. In commands or code: heygen.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Trending Content Scout is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 5.4k tokens (SKILL.md is roughly 22k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Trending Content Scout: Social Listening Brief (unifapi-agent/agents, 589 stars), Paid Ads Audit (AgriciDaniel/claude-ads, 9.8k stars), Influencer Discovery (tigerless-labs/influencer-discovery, 212 stars) and Comment Mining (ScrapeCreators/social-media-research-skills, 3.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Affitor (a GitHub organization) maintains it in Affitor/affiliate-skills, which has 700 GitHub stars. The repository holds 50 skills in this directory. The repository was last updated on September 15, 2026.
Source: Affitor/affiliate-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.