source-feedback

Analyze asset-manifest.json to detect sourcing failures and recommend visual alternatives.

Updated Apr 26, 2026

Search Tags:#troubleshooting #gap analysis #visual assets #media production #asset sourcing

Ready to run

npx skills add https://github.com/fy538/project-parallax --skill source-feedback

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: source-feedback
Source: https://github.com/fy538/project-parallax/tree/main/skills/source-feedback
Command: npx skills add https://github.com/fy538/project-parallax --skill source-feedback

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill analyzes the output from asset sourcing processes to detect sourcing failures, low-quality matches, and gaps in visual assets, helping maintain production continuity.

Core Features & Use Cases

Gap Detection: Checks asset-manifest.json for zero results, low-quality assets, or shallow source availability.
Diagnostic Analysis: Determines why certain shots failed sourcing and assesses their narrative importance.
Alternatives Suggestion: Recommends search term modifications, template substitutions, archival sources, AI illustrations, or script revisions to fill visual gaps.
Use Case: If a hero shot of a factory is missing, this Skill suggests broader search terms or template-based visual alternatives to avoid delays.

Quick Start

Provide detailed gap reports by analyzing recent sourcing outputs and suggest quick re-search commands or visual alternatives to streamline production.

Frequently Asked Questions about source-feedback

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I identify missing visuals in my media production manifest?▼

To identify missing visuals in media production, you can analyze the asset-manifest.json file to detect zero results, low-quality matches, or shallow source availability. This diagnostic process highlights sourcing failures and assesses their narrative importance.

What is the best way to resolve asset sourcing gaps for multimedia projects?▼

The best way to resolve asset sourcing gaps is to perform a diagnostic analysis on failed shots and recommend alternative strategies. Suggestions include search term modifications, template substitutions, archival sources, AI illustrations, or script revisions to maintain production continuity.

Why do certain visual asset searches fail during production?▼

Visual asset searches fail during production due to zero results or low-quality matches in the asset-manifest.json. A diagnostic analysis determines why specific shots failed sourcing and evaluates their overall narrative importance for the project.

Can I use template substitutions to fill visual gaps in short-reaction media?▼

Yes, you can use template substitutions to fill visual gaps in short-reaction media. When a hero shot is missing, the Skill recommends broader search terms or template-based visual alternatives to resolve the gap quickly and avoid delays.

What are the limitations of automated asset gap detection for production continuity?▼

Automated asset gap detection relies strictly on the contents of the asset-manifest.json to flag sourcing failures. It cannot invent new assets; it only recommends alternative sourcing strategies like search term modifications, archival sources, or script revisions.