# Send Viral Video Analysis to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "viral-video-analysis", "name": "Viral Video Analysis", "source": "tencent", "type": "skill", "category": "数据分析", "sourceUrl": "https://clawhub.ai/shawnshenopeninterx/viral-video-analysis", "canonicalUrl": "https://clawhub.ai/shawnshenopeninterx/viral-video-analysis", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/viral-video-analysis", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=viral-video-analysis", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "SKILL.md", "references/creator-feedback-framework.md", "scripts/analyze_video.py", "scripts/generate_report.py" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-04-23T16:43:11.935Z", "expiresAt": "2026-04-30T16:43:11.935Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard", "contentDisposition": "attachment; filename=\"4claw-imageboard-1.0.1.zip\"", "redirectLocation": null, "bodySnippet": null }, "scope": "source", "summary": "Source download looks usable.", "detail": "Yavira can redirect you to the upstream package for this source.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/viral-video-analysis" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/viral-video-analysis", "downloadUrl": "https://openagent3.xyz/downloads/viral-video-analysis", "agentUrl": "https://openagent3.xyz/skills/viral-video-analysis/agent", "manifestUrl": "https://openagent3.xyz/skills/viral-video-analysis/agent.json", "briefUrl": "https://openagent3.xyz/skills/viral-video-analysis/agent.md" } } ``` ## Documentation ### Requirements API Key: Requires MEMORIES_API_KEY from Memories.ai External API: Sends video URLs to https://mavi-backend.memories.ai for transcription Python packages: generate_report.py will auto-install fpdf2, pandas, openpyxl if missing ### Privacy Note Video URLs are sent to Memories.ai for transcription Batch analysis reads Excel files with creator/ROI data Review Memories.ai privacy policy before use ### Viral Video Analysis Analyze videos and provide actionable feedback for creators. ### Core Insight High ROI videos: <100 words, ~5s per product, visual-first + background music Low ROI videos: >150 words, >15s per product, too much explaining The core problem: Creators spend too much time "selling" instead of "showing". Remember: Ads reach non-followers who need to be hooked in 3 seconds. ### Quantitative Thresholds Metric✅ GOOD (High ROI)❌ BAD (Low ROI)Word Count<100 words>150 wordsTime per Product~5 seconds>15 secondsShows All Products UpfrontYESNOFormatVisual + MusicTalking/Explaining ### Setup Requires Memories.ai API key. Get one at https://api-tools.memories.ai Set environment variable: export MEMORIES_API_KEY="sk-mavi-your-key-here" ### 1. Get Audio Transcript (Word Count) import os import requests BASE_URL = "https://mavi-backend.memories.ai/serve/api/v2" API_KEY = os.environ.get("MEMORIES_API_KEY") HEADERS = {"Authorization": API_KEY} def get_transcript(url: str, platform: str = "instagram"): resp = requests.post( f"{BASE_URL}/{platform}/video/transcript", headers=HEADERS, json={"video_url": url, "channel": "rapid"}, timeout=60 ) data = resp.json() if data.get("success"): text = data["data"]["transcripts"][0]["text"] return {"text": text, "word_count": len(text.split())} return {"error": data.get("msg")} # Platform detection def detect_platform(url): url = url.lower() if "tiktok" in url: return "tiktok" if "instagram" in url: return "instagram" if "twitter" in url or "x.com" in url: return "twitter" return "youtube" ### 2. Analyze Against Thresholds def analyze_video(url): platform = detect_platform(url) result = get_transcript(url, platform) if "error" in result: return result word_count = result["word_count"] return { "url": url, "word_count": word_count, "word_count_status": "GOOD" if word_count < 100 else "OK" if word_count < 150 else "BAD", "issues": [], "transcript_preview": result["text"][:200] } ### 3. Generate Creator Feedback Based on analysis, provide specific feedback: If word_count > 150: "Your video has {X} words. Top performers use <100 words. Try replacing verbal explanations with visual demonstrations - stretch the fabric, spin around, show the fit." If pace is slow (>15s per product): "You're spending ~{X} seconds per product. High-performers show each item in ~5 seconds. Try quick cuts - one outfit = one scene transition." If no upfront overview: "Show ALL products in the first 2-3 seconds. Let viewers see the full haul immediately - it sets expectations and keeps them watching." Always remind: "Remember: Ads reach people who DON'T follow you. You have 3 seconds to grab a stranger's attention - don't waste it on intros." ### The Exception: Kirstin Approach Detailed verbal reviews CAN work if: Show all products FIRST before explaining Use low-pressure language: "if it doesn't fit, just return it" Focus on introducing products, not "selling" them Word count: 373 words can still perform if structure is right. ### GOOD Examples (share with creators) instagram.com/reel/Cy1zs4gLGFG - 46 words, 15s for 3 outfits, pure visual instagram.com/reel/DEybxPbNeOl - 56 words, quick showcase, background music instagram.com/reel/DHHr5o2s1LG - 91 words, fast cuts, shows product features instagram.com/reel/DBd6NxbOeBb - 91 words, demonstrates fit visually ### EXCEPTION Example (detailed review done RIGHT) instagram.com/reel/DCQJ355RWSE - 373 words but works: shows all upfront, low-pressure ### BAD Example (avoid) instagram.com/reel/DRCdjLlDcla - 168 words, 30s per outfit, too much explaining ### Feedback Template Hi [Creator], Thanks for your video! Here's some feedback to help improve performance: **What's Working:** - [Specific positive] **Opportunities:** 1. **Pacing**: Currently ~{X}s per product. Try ~5s per item with quick cuts. 2. **Word Count**: {X} words detected. Top performers use <100. Show more, tell less. 3. **Opening**: Consider showing all products in first 2-3 seconds. **Key Reminder:** Ads reach people who don't follow you yet. They need to be hooked in 3 seconds! **Reference Videos:** [Link to good example] Best, [Team] ### Batch Analysis def analyze_batch(excel_path, sample_size=20): import pandas as pd df = pd.read_excel(excel_path) df.columns = [c.lower().replace('sum of ', '').replace(' ', '_') for c in df.columns] # Get top and bottom performers top = df.nlargest(sample_size // 2, 'roi') bottom = df.nsmallest(sample_size // 2, 'roi') results = [] for _, row in pd.concat([top, bottom]).iterrows(): url = row.get('video_url') or row.get('row_labels') analysis = analyze_video(url) analysis['roi'] = row['roi'] analysis['tier'] = 'TOP' if row['roi'] > 1.0 else 'BOTTOM' results.append(analysis) return results ### Quick Commands "Analyze this video: [url]" → Word count + feedback "Why is this video underperforming?" → Detailed analysis "Give me feedback for [creator]" → Coaching template "Compare these videos" → Side-by-side analysis "Analyze my performance data" → Batch analysis from Excel ## Trust - Source: tencent - Verification: Indexed source record - Publisher: shawnshenopeninterx - Version: 1.0.1 ## Source health - Status: healthy - Source download looks usable. - Yavira can redirect you to the upstream package for this source. - Health scope: source - Reason: direct_download_ok - Checked at: 2026-04-23T16:43:11.935Z - Expires at: 2026-04-30T16:43:11.935Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/viral-video-analysis) - [Send to Agent page](https://openagent3.xyz/skills/viral-video-analysis/agent) - [JSON manifest](https://openagent3.xyz/skills/viral-video-analysis/agent.json) - [Markdown brief](https://openagent3.xyz/skills/viral-video-analysis/agent.md) - [Download page](https://openagent3.xyz/downloads/viral-video-analysis)