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Vfx Review

Community
kanaworksai-hue
vfx-review

Independently score one rendered game VFX filmstrip against a fixed rubric and return a JSON verdict. Use when asked to review, score or judge an effect's strip images (for example from the effekseer-vfx skill's `vfx review`) as a reviewer who did not author it.

Overview

Publisherkanaworksai-hue
Repositoryeffekseer-vfx-skill
Skill namevfx-review
Stars
76
Forks
5
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by kanaworksai-hue on GitHub. Read the source before you install it.

Installation

Install the Vfx Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/kanaworksai-hue/effekseer-vfx-skill/tree/main/skills/vfx-review
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/kanaworksai-hue/effekseer-vfx-skill.git /tmp/effekseer-vfx-skill
mkdir -p .claude/skills
cp -r /tmp/effekseer-vfx-skill/skills/vfx-review .claude/skills/vfx-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vfx Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Vfx Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Vfx Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Independent VFX review

You are the reviewer, not the author. Judge only what is visible in the images you are given. Do not open, read or ask for the recipe code, the brief's intentions or the author's notes; a design sentence from the manifest is context, not evidence.

Inputs you should receive

Usually one brief file written by vfx review-handoff (vfx/work/handoff/<evidence_id>.md) that lists everything below and the report_file path to write your JSON to. Otherwise:

  • the whole-timeline strip vfx/previews/strips/<ID>.png and the key-frame sheet (paths from vfx review); optionally <ID>_compare.png (previous round above, current below) and a --bright strip;
  • the effect's manifest entry: id, category, element, duration, peak, impact, delivery, design;
  • its review flags;
  • the evidence ID of the capture.

Open every image with your image-viewing tool. Tiles are labelled with absolute frame numbers at 60 FPS from the effect's own start. If you need full-size frames, ask the author to run vfx frames <evidence_id> <frames...> and give you the paths (or run it yourself if you have the skill installed). If an image is missing, say so — do not score from flags.

Rubric

Score each criterion 0–3: 0 missing or wrong · 1 present but weak, a player would not notice it · 2 clearly works · 3 reads instantly and has a distinct identity.

idQuestionLook at
readFrom the first lit tile alone, can you tell what the effect is (hit, slash, element, buff...)?first 2–3 lit tiles
timingAnticipation → contact → body → secondary → dissipation (or the slow fade-in / inward build for heals, buffs and charges)? Is the contact the brightest moment and only 2–5 frames?tile labels against manifest peak
layeringAt the strongest tile: a white-hot core, a saturated body and a darker rim or residue, not one flat colour?peak tile; bright strip if provided
shape_changeDoes the main shape erode, sweep or distort over time, or only scale and fade like a sticker?the main shape across consecutive tiles
motionDo secondary particles burst fast then slow, and move as the element should (fire up, ice falls, dark draws in, holy descends or rises)?secondary particles across tiles
placementDo arcs, columns and ground decals sit on or under the dummy rather than beside it or floating?all tiles
tailDoes the last third still show deliberate dissipation, or is it empty or cut off?last third of the strip
identityWould it be distinguishable from other effects of the same category if recoloured grey?whole strip
coherenceDo all layers speak one visual language (one palette family, one shape language, one motion vocabulary), with no layer that looks borrowed from another effect?whole strip

The authoritative copy is vfx rubric (from assets/review_rubric.json of the effekseer-vfx skill); if it differs from this table, follow it.

Purpose exceptions: heals, shields and buffs need no attack-style white flash; charges build inward before one release; a projectile strip ends at arrival and does not include its impact.

Output

Return exactly one JSON object and save it where the author asks (for example report.json):

json
{"id": "VFX_Fire_Explosion",
 "scores": {"read": 2, "timing": 3, "layering": 3, "shape_change": 2, "motion": 3, "placement": 3, "tail": 2, "identity": 3, "coherence": 3},
 "worst": "shape_change",
 "fix": "From f18 to f30 let the main fire layer burn a large gap open on one side so the round outline breaks up.",
 "verdict": "ship",
 "observed_frames": [1, 4, 9, 10, 12, 18, 30, 42, 54, 72]}

Rules:

  • Every criterion gets an integer 0–3. worst names a lowest-scoring criterion.
  • verdict is iterate if any score is below 2, otherwise ship.
  • fix is one concrete change for the worst criterion in recipe terms (which layer, timing, texture or motion), naming frames. One fix only: each iteration round changes one class of problem.
  • observed_frames lists the frame labels you actually looked at.

Save it to the report_file named in the brief (or where the author asks), then reply with your scores, verdict and fix. The author then runs vfx review-submit <evidence_id> <report_file> --reviewer <your reviewer id>. Your reviewer id is whatever the host uses to identify you (subagent name or session id); never author or self.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Vfx Review AI skill do?

Independently score one rendered game VFX filmstrip against a fixed rubric and return a JSON verdict. Use when asked to review, score or judge an effect's strip images (for example from the effekseer-vfx skill's `vfx review`) as a reviewer who did not author it.

Why use Vfx Review on TypingMind?

Because you install it once and use it with any model. Vfx Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Vfx Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kanaworksai-hue/effekseer-vfx-skill/tree/main/skills/vfx-review. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Vfx Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Vfx Review?

As many as you like. As long as a model supports skills, you can use Vfx Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Vfx Review AI skill free?

Yes. It is published on GitHub by kanaworksai-hue under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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