{"product_id":"ai-agent-skill-for-in-depth-self-media-content-analysis","title":"AI Agent Skill for In-Depth Self-Media Content Analysis","description":"\u003ch3\u003eAI Agent Skill for In-Depth Self-Media Content Analysis\u003c\/h3\u003e\n\n\u003cp\u003eThis 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.\u003c\/p\u003e\n\n\u003ch3\u003eWhat this skill does\u003c\/h3\u003e\n\u003cul\u003e\n  \u003cli\u003eVerifies data including platform, content, publication date, observation window, field definitions, missing values, and outliers.\u003c\/li\u003e\n  \u003cli\u003eProvides core conclusions on performance against its baseline and identifies key signals.\u003c\/li\u003e\n  \u003cli\u003eAttributes results based on evidence strength for elements like topics, audience targets, headlines, and more.\u003c\/li\u003e\n  \u003cli\u003eCompares similar content within the same platform and time window using median, P75, new followers per thousand views, deep interaction rate, and production time.\u003c\/li\u003e\n  \u003cli\u003eForms decisions and experiment proposals with hypotheses, changes, success criteria, and observation windows.\u003c\/li\u003e\n  \u003cli\u003eOutputs core findings, data quality explanations, attribution evidence, and executable actions.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003eWho it is for\u003c\/h3\u003e\n\u003cul\u003e\n  \u003cli\u003eDevelopers and teams employing AI coding agents such as Claude Code, Cursor, and Codex.\u003c\/li\u003e\n  \u003cli\u003eProfessionals involved in media content performance analysis and decision-making.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003eUse cases\u003c\/h3\u003e\n\u003cul\u003e\n  \u003cli\u003eAnalyzing the performance of a series of blog posts to determine effective and ineffective strategies.\u003c\/li\u003e\n  \u003cli\u003eConducting a monthly review of social media campaigns to optimize periodic engagement efforts.\u003c\/li\u003e\n  \u003cli\u003eAttributing changes in engagement to specific content features like titles or publication times.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003eTechnical details\u003c\/h3\u003e\n\u003cul\u003e\n  \u003cli\u003eWorks with data from platform backend screenshots and export files.\u003c\/li\u003e\n  \u003cli\u003eUtilizes certified connectors or user-owned account read-only statistical interfaces.\u003c\/li\u003e\n  \u003cli\u003eCapable of reading content task cards, registers, and historical retrospectives for comprehensive analyses.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003eNote: 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.\u003c\/p\u003e\n\u003c!-- mcpcart:static-blocks:start --\u003e\n\u003chr\u003e\n\u003ch3\u003eSource \u0026amp; Licence\u003c\/h3\u003e\n\u003cp\u003eThis package is built on open-source work published by \u003cstrong\u003eyanhua1010\u003c\/strong\u003e (\u003ca href=\"https:\/\/github.com\/yanhua1010\/self-media-content-workflow\" rel=\"nofollow noopener\" target=\"_blank\"\u003eyanhua1010\/self-media-content-workflow\u003c\/a\u003e) and distributed under \u003cstrong\u003eMIT\u003c\/strong\u003e. The original licence text and copyright notice are included in your download.\u003c\/p\u003e\n\u003cp\u003ePersonal and commercial use, modification and redistribution are permitted, provided the original copyright and licence notice are retained.\u003c\/p\u003e\n\u003cp\u003eYour 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.\u003c\/p\u003e\n\u003ch3\u003eDelivery \u0026amp; Support\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eDelivery:\u003c\/strong\u003e instant — a secure download link is emailed to you as soon as payment is confirmed.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFormat:\u003c\/strong\u003e ZIP archive containing the skill files, documentation and the original licence.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSupport:\u003c\/strong\u003e \u003ca href=\"mailto:support@mcpcart.com\"\u003esupport@mcpcart.com\u003c\/a\u003e — we aim to reply within 2 business days.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eUpdates:\u003c\/strong\u003e updates are included only where stated on this page.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eRefunds\u003c\/h3\u003e\n\u003cp\u003eThis 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.\u003c\/p\u003e\n\u003cp style=\"font-size:0.85em;color:#666;\"\u003eClaude, 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.\u003c\/p\u003e\n\u003c!-- mcpcart:static-blocks:end --\u003e","brand":"MCP Cart","offers":[{"title":"Default Title","offer_id":52777593340215,"sku":"MCP-YANHUA1010-SELF-MEDIA-CONTENT-WORKFLOW-SELF-MEDIA-CONTENT-ANALYTICS","price":22.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0981\/3950\/4951\/files\/wg-Z4lDpPWQ_AIsGBykKD_9acf5351291542bd9855a3d8731d5a32.jpg?v=1785676055","url":"https:\/\/mcpcart.com\/products\/ai-agent-skill-for-in-depth-self-media-content-analysis","provider":"SPF PRO","version":"1.0","type":"link"}