demo-slap_skill

This skill generates CS2 highlights and fragmovies from demos using the Demo-Slap API, with optional Leetify integration for auto-fetching URLs.
  • Python

2.6k

GitHub Stars

2

Bundled Files

2 months ago

Catalog Refreshed

3 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill openclaw/skills --skill demo-slap

  • _meta.json284 B
  • SKILL.md4.8 KB

Overview

This skill generates polished MP4 highlights and fragmovies from CS2 demo files using the Demo-Slap API, with optional Leetify integration to auto-fetch recent match demos. It automates demo analysis, presents available highlights, and renders chosen clips or stitched fragmovies. Use it when you want fast, repeatable highlight creation without manual demo editing.

How this skill works

The skill can fetch demo URLs via Leetify (if a Leetify API key and a mapped Steam64 ID are available) or accept a direct demo URL from the user. It runs two asynchronous jobs through the demo-slap CLI: analyze (finds candidate highlights and returns JobIDs/Highlight IDs) and render (creates the MP4 clip or fragmovie). Long-running steps must run in background sessions; after rendering the skill uploads the MP4, compressing it if needed for size limits.

When to use it

  • A user asks to “record a highlight”, “make a fragmovie”, or “clip that round” from a CS2 demo.
  • You have a direct demo download link (.dem, .dem.gz) and want an automated highlight.
  • You want to auto-fetch recent matches for a user via Leetify by Steam64 ID.
  • You need an MP4 ready to share in chat or on social media without manual editing.

Best practices

  • Save Demo-Slap and Leetify API keys to data/config.json or environment variables before use.
  • Map chat usernames to Steam64 IDs for reliable Leetify match lookup.
  • Always run analyze and render steps asynchronously (sessions_spawn) to avoid blocking the main session.
  • Ask users to pick Highlight ID(s) from the analysis table before rendering.
  • Compress renders with ffmpeg when uploads exceed messaging platform size limits (example CRF 28).

Example use cases

  • User: “Clip my last match” → fetch recent match via Leetify, analyze, show highlight table, render selected highlights.
  • Team editor: stitch multiple highlight IDs into a single fragmovie for YouTube or Twitch recaps.
  • Community moderator: generate quick round highlights from a submitted demo link and share in Discord.
  • Streamer: compress and return a highlight clip small enough to upload to platform limits.

FAQ

No. Leetify is optional but recommended for automatically finding recent match demos. You can always supply a direct demo URL.

How long do analysis and rendering take?

Analysis typically takes 2–4 minutes; rendering and downloading an MP4 usually takes 2–5 minutes. Both steps must run asynchronously.

What if the rendered MP4 is too large to upload?

The workflow includes an ffmpeg compression step. Use a CRF around 28 and afast preset to reduce size while keeping acceptable quality.

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demo-slap skill by openclaw/skills | VeilStrat