How do I install the Clip Feedback skill?

Run npx skillmds@latest add luishiluy/clip-feedback in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Clip Feedback safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Clip Feedback?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Clip Feedback free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Clip Feedback?

LuisHiluy (@luishiluy) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Clip Feedback by luishiluy — Agent Skill

Name: Clip Feedback
Author: LuisHiluy

Clip Feedback

Analyze an AI-generated video clip against the prompt that produced it. Detects canon rule violations, emotion/energy/world mismatches, palette drift, and quality issues, then suggests specific prompt fixes to improve the next generation. Use whenever the user has a Veo, Seedance, Kling, Runway, or other AI-generated clip and asks "why does this look wrong", "check the clip", "check this clip", "prompt feedback", "analyze this clip", "compare clip to prompt", or anytime a video was generated from a prompt and needs iteration. Trigger this skill even when the user casually asks "is this good" about an AI clip — prompt vs reality analysis is the job.

LuisHiluy d666751 3 files · 11.1 KB Updated Sep 17, 2026

File contents

Clip Feedback — Prompt Intent vs Reality

What this does

Takes a video clip plus the prompt that generated it, analyzes what the clip actually looks like (via Gemini 2.5 Pro), and returns:

Rule violations — character names in prompt, 4th wall breaks, missing focal length, safety trigger stacking
Intent gaps — emotion mismatch, world palette drift, shot type wrong, energy level off
Quality issues — text overlays, CGI artifacts, motion blur, missing face
Specific prompt fixes — exact corrections to improve the next generation

Usage

Quick rule check (no API call — instant)

python3 scripts/prompt_feedback.py \
  --clip /path/to/clip.mp4 \
  --prompt "the generation prompt used" \
  --rules-only

Full analysis (calls Gemini 2.5 Pro — ~10s)

python3 scripts/prompt_feedback.py \
  --clip /path/to/clip.mp4 \
  --prompt "the generation prompt used" \
  --source veo

Supported sources: veo, seedance, kling, runway, or any label.

From a prompt file

python3 scripts/prompt_feedback.py \
  --clip /path/to/clip.mp4 \
  --prompt-file /path/to/prompt.txt \
  --source seedance

JSON output (for piping to other tools)

python3 scripts/prompt_feedback.py \
  --clip /path/to/clip.mp4 \
  --prompt "..." \
  --json

When the user says "check the clip"

Ask which clip (path) if not obvious from context
Ask for or find the prompt that generated it
Run --rules-only first for instant feedback
If the user wants deeper analysis, run the full version
Present the feedback summary and suggested fixes
Offer to apply the fixes and regenerate

What it checks (canonical rules)

Rule	What it catches
No character names	"Jane" → should be "the daughter"
No 4th wall	"looking at camera" → eyeline off-camera
No resolution text	"2K" in prompt → handled by tool settings
No music/dialogue	"music" in prompt → add to avoid line
Safety stacking	3+ trigger words in one sentence → split
Focal length required	Missing "85mm, f/1.4" → add lens spec
Material descriptors	No textures → add tactile nouns
World palette	Palette drift → strengthen palette direction
Emotion match	Prompt says "dread", clip reads "calm" → add atmosphere cues
Quality flags	Text overlays, CGI glow, motion blur → add negative prompts

Configuration

Configure your canonical rules in reference/prompt-rules.md. Each rule gets:

A pattern (regex or keyword list) to detect violations in prompts
A fix template (the correction to suggest)
A severity (block / warn / info)

Dependencies

Python 3.10+
google-generativeai for Gemini analysis
ffmpeg on PATH for frame extraction

Setup

pip install google-generativeai pillow
export GEMINI_API_KEY=your_key_here

---name: clip-feedbackdescription: Analyze an AI-generated video clip against the prompt that produced it. Detects canon rule violations, emotion/energy/world mismatches, palette drift, and quality issues, then suggests specific prompt fixes to improve the next generation. Use whenever the user has a Veo, Seedance, Kling, Runway, or other AI-generated clip and asks "why does this look wrong", "check the clip", "check this clip", "prompt feedback", "analyze this clip", "compare clip to prompt", or anytime a video was generated from a prompt and needs iteration. Trigger this skill even when the user casually asks "is this good" about an AI clip — prompt vs reality analysis is the job.---# Clip Feedback — Prompt Intent vs Reality## What this doesTakes a video clip plus the prompt that generated it, analyzes what the clip actually looks like (via Gemini 2.5 Pro), and returns:- **Rule violations** — character names in prompt, 4th wall breaks, missing focal length, safety trigger stacking- **Intent gaps** — emotion mismatch, world palette drift, shot type wrong, energy level off- **Quality issues** — text overlays, CGI artifacts, motion blur, missing face- **Specific prompt fixes** — exact corrections to improve the next generation## Usage### Quick rule check (no API call — instant)```bashpython3 scripts/prompt_feedback.py \ --clip /path/to/clip.mp4 \ --prompt "the generation prompt used" \ --rules-only```### Full analysis (calls Gemini 2.5 Pro — ~10s)```bashpython3 scripts/prompt_feedback.py \ --clip /path/to/clip.mp4 \ --prompt "the generation prompt used" \ --source veo```Supported sources: `veo`, `seedance`, `kling`, `runway`, or any label.### From a prompt file```bashpython3 scripts/prompt_feedback.py \ --clip /path/to/clip.mp4 \ --prompt-file /path/to/prompt.txt \ --source seedance```### JSON output (for piping to other tools)```bashpython3 scripts/prompt_feedback.py \ --clip /path/to/clip.mp4 \ --prompt "..." \ --json```## When the user says "check the clip"1. Ask which clip (path) if not obvious from context2. Ask for or find the prompt that generated it3. Run `--rules-only` first for instant feedback4. If the user wants deeper analysis, run the full version5. Present the feedback summary and suggested fixes6. Offer to apply the fixes and regenerate## What it checks (canonical rules)| Rule | What it catches ||---|---|| No character names | "Jane" → should be "the daughter" || No 4th wall | "looking at camera" → eyeline off-camera || No resolution text | "2K" in prompt → handled by tool settings || No music/dialogue | "music" in prompt → add to avoid line || Safety stacking | 3+ trigger words in one sentence → split || Focal length required | Missing "85mm, f/1.4" → add lens spec || Material descriptors | No textures → add tactile nouns || World palette | Palette drift → strengthen palette direction || Emotion match | Prompt says "dread", clip reads "calm" → add atmosphere cues || Quality flags | Text overlays, CGI glow, motion blur → add negative prompts |## ConfigurationConfigure your canonical rules in `reference/prompt-rules.md`. Each rule gets:- A pattern (regex or keyword list) to detect violations in prompts- A fix template (the correction to suggest)- A severity (block / warn / info)## Dependencies- Python 3.10+- `google-generativeai` for Gemini analysis- `ffmpeg` on PATH for frame extraction## Setup```bashpip install google-generativeai pillowexport GEMINI_API_KEY=your_key_here```

Frequently asked questions