From xactions
Audits X/Twitter follower quality, engagement authenticity, unfollower patterns, and network efficiency to produce a community health score. Use when monitoring account health or detecting bot/spam followers.
npx claudepluginhub nirholas/xactionsThis skill uses the workspace's default tool permissions.
MCP-powered workflow for auditing follower quality, engagement health, and network efficiency. Produces a scored health report.
Provides browser console JavaScript scripts to analyze X/Twitter engagement metrics, best posting times, hashtags, competitors, follower demographics, tweet performance, virality, and A/B testing. Useful for optimizing social media accounts without APIs.
Audits X (Twitter) followers for bots, inactive accounts, and ghosts via Xquik API. Extracts lists, flags suspects by heuristics like low tweets/followers ratio and recent creation; analysis-only.
Master X (Twitter) algorithm with engagement weights, viral formulas, shadowban avoidance, thread optimization, and growth strategies from open-source code and 10M+ tweet data.
Share bugs, ideas, or general feedback.
MCP-powered workflow for auditing follower quality, engagement health, and network efficiency. Produces a scored health report.
| Tool | Purpose |
|---|---|
x_get_profile | Account-level stats |
x_get_followers | Follower list for quality audit |
x_get_following | Following list for reciprocity check |
x_get_non_followers | Identify non-reciprocal follows |
x_get_tweets | Engagement data for authenticity check |
x_detect_unfollowers | Track recent unfollower patterns |
Complement MCP analysis with browser-side tools:
| Goal | Script |
|---|---|
| Audit follower quality | src/auditFollowers.js |
| Detect unfollowers | src/detectUnfollowers.js |
| Audience demographics | src/audienceDemographics.js |
| Follow ratio analysis | src/followRatioManager.js |
| Account health dashboard | src/accountHealthMonitor.js |
| Shadowban check | src/shadowbanChecker.js |
x_get_profile to get follower count, following count, and calculate follower-to-following ratio.x_get_followers with limit: 200. Classify each follower:
x_get_tweets with limit: 30. For each tweet, compare engagement volume to follower count. Flag anomalies: likes/follower ratio > 10% (potential engagement pods) or < 0.1% (ghost followers).x_detect_unfollowers. Note churn rate and whether unfollowers correlate with specific content types or posting gaps.x_get_non_followers. Calculate reciprocity rate: mutual_follows / total_following * 100. Identify high-value accounts not following back.## Community Health Report: @{username}
Date: {date} | Health Score: {score}/100
### Score Breakdown
| Category | Score | Weight | Weighted |
|----------|-------|--------|----------|
| Follower Quality | {n}/100 | 30% | {n} |
| Engagement Authenticity | {n}/100 | 25% | {n} |
| Churn Rate | {n}/100 | 20% | {n} |
| Reciprocity | {n}/100 | 15% | {n} |
| Growth Trend | {n}/100 | 10% | {n} |
### Follower Audit
- Total: {count} | Active: {n}% | Low quality: {n}% | Suspect bots: {n}%
### Engagement Health
- Avg engagement rate: {rate}%
- Anomalous posts: {count} flagged
### Reciprocity
- Following: {count} | Follow back: {n}% | Non-followers: {count}
### Recommendations
1. {actionable recommendation}
2. {actionable recommendation}
3. {actionable recommendation}
src/accountHealthMonitor.js for quick between-audit checks| Score | Grade | Action |
|---|---|---|
| 80-100 | Excellent | Maintain current strategy |
| 60-79 | Good | Minor adjustments needed |
| 40-59 | Fair | Review engagement strategy, clean follower list |
| 20-39 | Poor | Major cleanup needed, block bots, reassess content |
| 0-19 | Critical | Possible shadowban, mass bot followers, or inactive account |
src/blockBots.jssrc/unfollowback.js