{"product_id":"cross-dcc-ai-skill-error-reports-diagnostics-for-codex","title":"Cross-DCC AI Skill: Error Reports \u0026 Diagnostics for Codex","description":"\u003ch3\u003eCross-DCC AI Skill: Error Reports \u0026amp; Diagnostics for Codex\u003c\/h3\u003e\n\n\u003cp\u003eThe Cross-DCC AI Skill: Error Reports \u0026amp; Diagnostics for Codex provides developers and technical teams with essential tools for troubleshooting error conditions in Digital Content Creation (DCC) environments. It generates comprehensive error reports, captures diagnostic data, and monitors tool performance across various DCC applications such as Maya, Blender, Houdini, Unreal Engine, and standalone Python. This skill is an infrastructure component that assists in identifying the causes of tool failures.\u003c\/p\u003e\n\n\u003ch3\u003eWhat this skill does\u003c\/h3\u003e\n\u003cul\u003e\n    \u003cli\u003e\n\u003cstrong\u003edcc_diagnostics__error_report\u003c\/strong\u003e: Initiate diagnostics with this tool. It provides a detailed bundle including log tails, failed job summaries, and process snapshots to assess error conditions.\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003edcc_diagnostics__audit_log\u003c\/strong\u003e: Access audit logs to review sandbox-level denials and recent tool invocations for more context on issues.\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003edcc_diagnostics__tool_metrics\u003c\/strong\u003e: Evaluate and diagnose tool performance, identifying any tools that are consistently slow or failing.\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003edcc_diagnostics__screenshot\u003c\/strong\u003e: Capture the current visual state of the DCC application to assist with error confirmation and documentation.\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003edcc_diagnostics__process_status\u003c\/strong\u003e: Monitor the health of the DCC process to determine if it remains operational during troubleshooting.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003eWho it is for\u003c\/h3\u003e\n\u003cp\u003eThis skill is designed for developers and teams utilizing AI coding agents such as Claude Code, Cursor, and Codex who need to ensure robust debugging capabilities in their DCC workflows. It is particularly beneficial for technical artists, software engineers, and IT support staff involved in troubleshooting and maintaining DCC applications.\u003c\/p\u003e\n\n\u003ch3\u003eUse cases\u003c\/h3\u003e\n\u003cul\u003e\n    \u003cli\u003eTroubleshooting vague or uninformative error messages in digital content creation tools.\u003c\/li\u003e\n    \u003cli\u003eImproving diagnostic workflows in multi-application DCC environments.\u003c\/li\u003e\n    \u003cli\u003eDocumenting error conditions for later analysis or audit purposes.\u003c\/li\u003e\n    \u003cli\u003eMonitoring process health and performance metrics across different DCC tools.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003eTechnical details\u003c\/h3\u003e\n\u003cul\u003e\n    \u003cli\u003eDeveloped with the aid of the `dcc-mcp-core` library, facilitating cross-DCC environment support.\u003c\/li\u003e\n    \u003cli\u003eOperates independently of DCC-specific APIs, ensuring broad compatibility across multiple platforms and software versions.\u003c\/li\u003e\n    \u003cli\u003eIntegration-ready with AI coding environments, enhancing the troubleshooting capabilities of deployed agents.\u003c\/li\u003e\n\u003c\/ul\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\u003edcc-mcp\u003c\/strong\u003e (\u003ca href=\"https:\/\/github.com\/dcc-mcp\/dcc-mcp-core\" rel=\"nofollow noopener\" target=\"_blank\"\u003edcc-mcp\/dcc-mcp-core\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":53090800763191,"sku":"MCP-DCC-MCP-DCC-MCP-CORE-DCC-DIAGNOSTICS","price":61.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0981\/3950\/4951\/files\/S_cFgY7uTKmvkLlQSMDe1_d1f6afc371364da396d1b9dfc920e5c3.jpg?v=1791115489","url":"https:\/\/mcpcart.com\/products\/cross-dcc-ai-skill-error-reports-diagnostics-for-codex","provider":"SPF PRO","version":"1.0","type":"link"}