shortfilm-prompt

shortfilm-prompt is a skill for Claude Code from jnMetaCode/ai-shortfilm-prompts. It costs 100 tokens per session (4,927 once invoked), scanned B, original, MIT.

A prompt-writing guide for cinematic AI short videos made with tools such as Sora, Kling, Veo, or Seedance. It structures transformation, action, emotional, atmospheric, and multi-shot scenes into five stages.

In plain words
What is it for?
Use it to write prompts for short narratives, transformations, combat or weapon-charge scenes, emotional farewells, atmospheric shots, and character posters.
Why use it?
It turns a loose video idea into a prompt with clearer scene progression and model-specific advice. It also helps account for differences between video-generation tools.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: names the AskUserQuestion tool.

Part of the ai-shortfilm-prompts plugin — 1 skill shipped together

Good fit Use it to write prompts for short narratives, transformations, combat or weapon-charge scenes, emotional farewells, atmospheric shots, and character posters.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jnmetacode/ai-shortfilm-prompts/shortfilm-prompt
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add jnMetaCode/ai-shortfilm-prompts --skill shortfilm-prompt
Clone the repo
git clone --depth 1 https://github.com/jnMetaCode/ai-shortfilm-prompts

Made for: Claude Code.

Or install ai-shortfilm-prompts, the plugin that ships this one along with the rest of its 1 skill.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for shortfilm-prompt

README.md
[![agentmods](https://agentmods.dev/badge/skills/jnmetacode/ai-shortfilm-prompts/shortfilm-prompt/github.svg)](https://agentmods.dev/skills/jnmetacode/ai-shortfilm-prompts/shortfilm-prompt)
Your own site
<a href="https://agentmods.dev/skills/jnmetacode/ai-shortfilm-prompts/shortfilm-prompt"><img src="https://agentmods.dev/badge/skills/jnmetacode/ai-shortfilm-prompts/shortfilm-prompt/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for shortfilm-prompt

Your own site · 80×15
<a href="https://agentmods.dev/skills/jnmetacode/ai-shortfilm-prompts/shortfilm-prompt"><img src="https://agentmods.dev/badge/skills/jnmetacode/ai-shortfilm-prompts/shortfilm-prompt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,927 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Anti-Refusal · line 63
    Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.
    Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00100 $0.04927
Opus 5 $0.00050 $0.02464
Sonnet 5 $0.00020 $0.00985
Haiku 4.5 $0.00010 $0.00493

Measured 12d ago against content hash 4781b477ed20, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade B, and why

shortfilm-prompt scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Strips warnings and disclaimersmediumAnti-refusal

Omitting safety caveats hides risk from the user and is a common jailbreak preamble.

Don't lecture. Point at the parts the user is most likely to want to
skills/shortfilm-prompt/SKILL.md · 412 lines

How it starts

The opening of the file, as written. The whole thing — 412 lines — stays where its author put it; the contents beside it link to each section on GitHub.

shortfilm-prompt — Cinematic AI Video Prompt Generator

You play the role of a director's assistant fluent in the 5-stage AI shortfilm prompt structure (first proven by Mx-Shell in Zombie Scavenger). When the user invokes this skill they want a prompt they can paste directly into a video model: Seedance 2.0 / Xiaoyunque / Sora / Kling / Jimeng / Veo.

Model-agnostic core: the 5-stage structure itself is the same across all models. At the end of your output, give one line of model-specific advice (Sora prefers concise; Kling is more permissive on IP names; Seedance blocks IP names; etc.).

Workflow (execute in order)

Step 1 — Did the user already specify enough?

If their initial request already includes all of the following, skip Step 2 and go straight to Step 3:

  • Video type (transformation / multi-shot narrative / emotional narrative (family · pet · farewell) / atmospheric single shot / weapon-charge / combat / static character poster)
  • Duration (5s / 10s / 15s / 20s / multi-shot edited)
  • Subject base setup (person / robot / mech)
  • Scene (location + time + atmosphere)
  • Visual style preference (reference film or aesthetic)

Step 2 — If info is incomplete, ask at most 2–3 key questions

Use AskUserQuestion. Priority order:

  1. Video type + duration (decides which template branch)
  2. Subject + scene (decides content)
  3. Visual style / reference aesthetic (decides the atmosphere stage)

Don't over-ask. Mx-Shell himself worked iteratively, making it up as he went. Writing a first draft and refining beats interrogating the user for 10 details.

Step 3 — Output a prompt in the 5-stage structure

First, load the matching template from the Template library below — Read that file for the fuller skeleton + genre-specific phrasing, then write your prompt in the 5-stage structure. The SKILL rules in this file always win on any conflict; templates supply depth, not overrides.

Read the full file on GitHub · 412 lines

Files

What ships with it

9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 412 lines · 100 tokens per session scan B 4781b477ed20

Subscribe to this mod's changes

shortfilm-prompt is a skill published in the GitHub repository jnMetaCode/ai-shortfilm-prompts (405 stars, last pushed 2d ago), licensed MIT. It adds 100 tokens to every session and 4,927 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it B with 1 finding (strips warnings and disclaimers). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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