AI Agent Skill for In-Depth Self-Media Content Analysis

AI Agent Skill for In-Depth Self-Media Content Analysis

This AI Agent Skill assists in analyzing single articles, series, or weekly and monthly self-media data. It generates actionable retrospective insights by reading platform backend screenshots, CSV files, spreadsheets, public links, or user-provided data. The skill calculates engagement efficiency and deep interaction, comparing to the platform baseline, and attributes results to factors like topic selection, titles, covers, openings, structure, publication timing, tags, and actions. It outputs decisions for amplification, repackaging, re-adaptation, sample collection, or discontinuation.

What this skill does

• Verifies data including platform, content, publication date, observation window, field definitions, missing values, and outliers.
• Provides core conclusions on performance against its baseline and identifies key signals.
• Attributes results based on evidence strength for elements like topics, audience targets, headlines, and more.
• Compares similar content within the same platform and time window using median, P75, new followers per thousand views, deep interaction rate, and production time.
• Forms decisions and experiment proposals with hypotheses, changes, success criteria, and observation windows.
• Outputs core findings, data quality explanations, attribution evidence, and executable actions.

Who it is for

• Developers and teams employing AI coding agents such as Claude Code, Cursor, and Codex.
• Professionals involved in media content performance analysis and decision-making.

Use cases

• Analyzing the performance of a series of blog posts to determine effective and ineffective strategies.
• Conducting a monthly review of social media campaigns to optimize periodic engagement efforts.
• Attributing changes in engagement to specific content features like titles or publication times.

Technical details

• Works with data from platform backend screenshots and export files.
• Utilizes certified connectors or user-owned account read-only statistical interfaces.
• Capable of reading content task cards, registers, and historical retrospectives for comprehensive analyses.

Note: For public content analysis, the skill targets publicly available information only. Users must comply with the target site's terms, and the skill does not bypass authentication or CAPTCHA.

Source & Licence

This package is built on open-source work published by yanhua1010 (yanhua1010/self-media-content-workflow) and distributed under MIT. The original licence text and copyright notice are included in your download.

Personal and commercial use, modification and redistribution are permitted, provided the original copyright and licence notice are retained.

Your purchase covers curation, licence verification, packaging, documentation and instant delivery. It does not grant exclusive rights to the underlying open-source code, which remains available under its original licence.

Delivery & Support

• Delivery: instant — a secure download link is emailed to you as soon as payment is confirmed.
• Format: ZIP archive containing the skill files, documentation and the original licence.
• Support: support@mcpcart.com — we aim to reply within 2 business days.
• Updates: updates are included only where stated on this page.

Refunds

This is a digital product delivered immediately after purchase. By completing your order you request immediate delivery and acknowledge that, once the download has been accessed, the statutory right to cancel no longer applies to the extent permitted by law. Refund requests are handled in accordance with our published Refund Policy.

Claude, Codex, Gemini and Cursor are trademarks of their respective owners. MCP Cart is an independent marketplace and is not affiliated with, endorsed by, or sponsored by any of them. Compatibility references describe interoperability only.