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snoopyrain

Boring Social Analytics

by snoopyrain · GitHub ↗ · v1.0.1 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install boring-social-analytics
Description
Track social media performance and analytics across platforms using Boring. Use when the user says 'show my analytics', 'check social media performance', 'ho...
README (SKILL.md)

Boring Social Analytics

Track performance and engagement across all your social media platforms. Powered by Boring.

Security & Data Handling

  • MCP link is a credential: Your MCP Server URL contains an embedded authentication token. Treat it like a password — do not share it publicly. Regenerate anytime in Settings.
  • Data flow: Analytics queries are sent from Boring's server to social media platform APIs (Facebook, Instagram, Threads, YouTube, TikTok) on your behalf. Only performance metrics are retrieved — no content is uploaded.
  • No local credentials: No local API keys or environment variables needed. All auth is embedded in the MCP link.

Prerequisites

  1. Sign up at boring.aiagent-me.com with Google
  2. Connect accounts — supports Facebook, Instagram, Threads, YouTube, TikTok
  3. Get your MCP link: Go to Settings → copy your MCP Server URL (contains your auth token — treat it like a password)
  4. Add to Claude: Paste the MCP link as a Connector — no install, no API key needed

Available Analytics Tools

Tool Data Source Best For
boring_get_performance Real-time platform API Account-level overview (reach, engagement, followers)
boring_get_video_analytics Real-time platform API Per-post/video metrics (views, likes, comments, shares)
boring_get_posts_performance Daily snapshots (collected at 2 AM) Historical post performance over date ranges
boring_get_publish_history Boring database Publishing history and status tracking

Workflow

Step 1: List Accounts

Call boring_list_accounts to see all connected platforms. Show a summary to the user.

Step 2: Determine What the User Wants

User Request Tool to Use
"How is my account doing?" boring_get_performance
"Show my best posts" boring_get_video_analytics
"Performance over the last month" boring_get_posts_performance
"What did I post recently?" boring_get_publish_history
"Compare platforms" boring_get_performance for each platform

Step 3: Fetch Data

Account-Level Performance

boring_get_performance(
  account_id="\x3Caccount_id>",
  platform="instagram",
  period="week"       // "day", "week", or "month"
)

Returns metrics like reach, follower count, engagement rate, profile views.

Per-Post Analytics (Real-Time)

boring_get_video_analytics(
  account_id="\x3Caccount_id>",
  platform="instagram",
  limit=20             // max 100
)

Returns per-post data: views, likes, comments, shares for up to 100 recent posts.

Historical Post Performance (Snapshots)

boring_get_posts_performance(
  account_id="\x3Caccount_id>",
  since="2025-12-01",  // YYYY-MM-DD (default: 30 days ago)
  until="2025-12-31",  // YYYY-MM-DD (default: today)
  limit=20             // max 100
)

Returns post-level engagement, metrics, and content from daily collected snapshots.

Publishing History

boring_get_publish_history(
  limit=20,
  platform="facebook"  // optional filter
)

Returns recent publishing activity with status and post IDs.

Step 4: Present Results

Format the data clearly for the user:

For account overview: Show key metrics in a summary table For post analytics: Rank posts by engagement, highlight top performers For cross-platform comparison: Side-by-side metrics across platforms For historical data: Show trends over time

Metrics by Platform

Facebook

  • page_media_view: Total video views
  • page_post_engagements: Likes, comments, shares
  • page_total_actions: Total page actions

Instagram

  • reach: Accounts reached
  • follower_count: Total followers
  • profile_views: Profile visits
  • total_interactions: Likes + comments + saves + shares
  • Reels: ig_reels_avg_watch_time, ig_reels_video_view_total_time

Threads

  • views: Post views
  • likes, replies, reposts, quotes
  • followers_count: Account followers

YouTube

  • views, likes, comments, shares
  • estimatedMinutesWatched: Total watch time
  • averageViewDuration: Average view duration
  • subscribersGained / subscribersLost

TikTok

  • Video views, likes, comments, shares
  • Account-level performance metrics

Cross-Platform Comparison

When the user asks to compare platforms, fetch boring_get_performance for each connected account and present a unified table:

| Platform   | Reach   | Engagement | Followers |
|-----------|---------|------------|-----------|
| Facebook  | 12,500  | 1,200      | 5,000     |
| Instagram | 8,300   | 2,100      | 3,200     |
| Threads   | 3,100   | 450        | 1,800     |
| YouTube   | 15,000  | 3,500      | 2,100     |

Error Handling

Error Solution
InvalidApiKey MCP link may be invalid — regenerate it at boring.aiagent-me.com Settings
InvalidAccountId Run boring_list_accounts to get valid IDs
TokenExpired Reconnect account at boring.aiagent-me.com
No data returned Account may be newly connected — data collection runs daily at 2 AM

Documentation

Full API docs: boring-doc.aiagent-me.com

Usage Guidance
This skill is coherent for its stated purpose, but before installing: (1) treat the MCP Server URL like a password — only paste it into agents or connectors you trust; (2) verify the domain (boring-doc.aiagent-me.com / boring.aiagent-me.com) and the service's privacy/permissions to ensure you are comfortable with Boring querying your social accounts; (3) use least-privilege or regenerate the MCP token if it is ever exposed; (4) remember the skill sends analytics to Boring's servers — do not use it with accounts or data you cannot share with an external service. If you want stronger control, ask whether Boring supports narrower-scoped tokens or per-platform API keys instead of a single embedded-token connector.
Capability Analysis
Type: OpenClaw Skill Name: boring-social-analytics Version: 1.0.1 The skill bundle provides instructions for an AI agent to interface with a social media analytics service via the Model Context Protocol (MCP). It correctly identifies the MCP URL as a sensitive credential and provides clear documentation on data flow and tool usage (e.g., boring_get_performance) without any evidence of malicious intent, data exfiltration, or prompt injection attacks in SKILL.md.
Capability Assessment
Purpose & Capability
Name/description (social analytics aggregator) match the declared requirement: an MCP connector URL that contains an embedded auth token used to query social platforms. No unrelated credentials, binaries, or install steps are requested.
Instruction Scope
SKILL.md only instructs the agent to use Boring-provided calls (boring_get_performance, boring_get_video_analytics, etc.) and to add the MCP Server URL as a Connector. It does not instruct the agent to read arbitrary local files, other environment variables, or to exfiltrate data to unexpected endpoints. The instructions explicitly note the MCP link is a credential and that queries go through Boring's servers.
Install Mechanism
No install spec and no code files — instruction-only skill. This minimizes on-disk risk; nothing is downloaded or executed locally by the skill itself.
Credentials
The only credential required is the MCP Connector link (embedded token) which is appropriate for a connector-based analytics integration. Note: the token is embedded in a URL rather than an env var; users should understand that pasting that link into the agent grants Boring access to the connected social accounts' analytics.
Persistence & Privilege
always is false and there are no requests to modify other skills or system-wide settings. The skill relies on a connector token and behaves as a typical, non-persistent integration.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install boring-social-analytics
  3. After installation, invoke the skill by name or use /boring-social-analytics
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
- Added a "Security & Data Handling" section explaining the credential nature of the MCP link and clarifying data flow and authentication. - Introduced a new "requires" metadata block specifying that a MCP Connector link is needed. - Updated setup instructions to emphasize the sensitive, credential-like nature of the MCP link. - No changes to functionality or API usage; documentation improvements only.
v1.0.0
- Initial release of Boring Social Analytics. - Track and report performance across Facebook, Instagram, Threads, YouTube, and TikTok. - Supports real-time and historical analytics for accounts and posts. - Simple workflow: connect accounts, select data, and view results in clear summaries or comparison tables. - Includes error troubleshooting and guided usage examples.
Metadata
Slug boring-social-analytics
Version 1.0.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is Boring Social Analytics?

Track social media performance and analytics across platforms using Boring. Use when the user says 'show my analytics', 'check social media performance', 'ho... It is an AI Agent Skill for Claude Code / OpenClaw, with 128 downloads so far.

How do I install Boring Social Analytics?

Run "/install boring-social-analytics" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Boring Social Analytics free?

Yes, Boring Social Analytics is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Boring Social Analytics support?

Boring Social Analytics is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Boring Social Analytics?

It is built and maintained by snoopyrain (@snoopyrain); the current version is v1.0.1.

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