Clip feedback

Skill LuisHiluy/claude-code-pipeline-skills/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.From its SKILL.md

Install

npx -y skills add LuisHiluy/claude-code-pipeline-skills --skill clip-feedback

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

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SKILL.md

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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

What ships with it: 2 files

7.6 KB alongside SKILL.md, 1 of them executable

scripts/

prompt_feedback.pyruns7.1 KB

README.md466 B