Install
$ agentstack add skill-donvito-skillsbento-social-media-analyzer ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Social Media Analytics
Analyze social media data to extract insights and generate strategic recommendations.
Analysis Framework
1. Data Ingestion & Validation
Read the uploaded file and identify available metrics. Common columns:
| Category | Metrics | |----------|---------| | Reach | Impressions, Reach, Views, Profile visits | | Engagement | Likes, Comments, Replies, Shares, Reposts, Bookmarks, Saves | | Growth | New followers, Unfollows, Net followers | | Content | Posts created, Video views, Media views |
Validate data completeness. Note any missing or zero-value columns.
2. Calculate Key Performance Indicators
Engagement Rate = (Total Engagements / Total Impressions) × 100
Follow Conversion = (New Followers / Profile Visits) × 100
Net Growth = New Followers - Unfollows
Likes per Post = Total Likes / Posts Created
Impressions per Post = Total Impressions / Posts Created
3. Temporal Analysis
Identify patterns across time periods:
- Best performing days: Highest impressions, engagement rate, follower growth
- Worst performing days: Lowest metrics, potential issues
- Posting frequency correlation: Compare posts/day vs engagement/post
- Viral content detection: Days with 2x+ average performance
4. Engagement Composition Analysis
Break down total engagements by type:
- Likes (passive appreciation)
- Bookmarks/Saves (high-intent, reference value)
- Replies/Comments (active conversation)
- Shares/Reposts (amplification)
High bookmark rates suggest educational/reference content resonates. High reply rates indicate conversation-driving content.
5. Quality vs Quantity Assessment
Analyze the relationship between posting volume and performance:
for each day:
likes_per_post = likes / posts
impressions_per_post = impressions / posts
# Compare high-volume vs low-volume days
# Often: fewer high-quality posts > many low-quality posts
6. Growth Funnel Analysis
Track the conversion funnel:
Impressions → Engagements → Profile Visits → New Followers
Calculate conversion rates at each stage. Identify bottlenecks.
Visualization Guidelines
Create an interactive React dashboard with tabs:
- Overview: Key metrics cards, impressions/engagement trend, engagement breakdown pie chart
- Engagement: Daily engagement rate bar chart, likes per post analysis
- Growth: Follower gains/losses, profile visit to follower conversion
- Insights: Key findings cards with actionable recommendations
Use Recharts for charts:
- ComposedChart for dual-axis (impressions + engagements)
- BarChart for daily comparisons
- PieChart for engagement breakdown
Recommendation Categories
Posting Schedule Optimization
- Identify best/worst performing days
- Suggest optimal posting frequency based on quality vs quantity analysis
- Recommend content scheduling strategy
Content Strategy
- Analyze which content types drive bookmarks (save-worthy)
- Identify viral content patterns
- Suggest content pillars based on engagement composition
Growth Tactics
- Profile optimization suggestions based on follow conversion rate
- Engagement strategy (when to be active in replies)
- Audience retention insights from unfollow patterns
Output Structure
- Summary metrics: Total impressions, engagements, engagement rate, net followers
- Key findings: 3-5 bullet points of critical insights
- Interactive dashboard: React component with tabbed views
- Strategic recommendations: Prioritized action items with rationale
Example Insights
- "Monday drove 24% of weekly impressions—analyze what made it viral"
- "Tuesday underperformed despite 13 posts—consider reducing output"
- "30 posts yielded 99 likes/post vs 7 posts with 309 likes/post—quality over quantity"
- "5,312 bookmarks (6.8% of engagements) suggests save-worthy content resonates"
- "10.3% of profile visitors convert to followers—optimize bio for higher conversion"
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: donvito
- Source: donvito/skillsbento
- License: Apache-2.0
- Homepage: https://www.skillsbento.com/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.