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Render Proof Points Overlay Agent Skill

Build the deterministic PIL pill overlays for a 'perfect-score + proof-points' UGC video ad (white 10/10 score header with a medal + orange sub with a finger-down + 3-4 green-check proof pills) and composite them onto a base clip in a diagonal L->R->L->R cascade, then mux the music bed into master-final.mp4. Config-driven (config.json), 1080x1920 9:16, FREE and deterministic (no paid calls, text stays pixel-crisp). Use for the overlay-proof-points format; the base clip + music come from separate paid capabilities.

4k tokens
context cost
the whole folder, loaded on every use
6
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
1086
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/gooseworks-ai/goose-skills --skill render-proof-points-overlay

What comes with it

13 384 bytes besides the instruction
scripts/build_overlays.py
scripts/compose_master.py
scripts/fetch_icons.py
skill.meta.json
tests/smoke-test.md

The instruction itself

4 sections, as written by the author

render-proof-points-overlay

Build the deterministic PIL/FFmpeg overlays for the "Instagram comparison-tool reviewer" UGC ad — a white "we got a perfect 10/10 score" headline pill (trailing medal), an orange "but here's also why you'll love us" sub pill (trailing finger-down, width-matched to the header), and 3-4 green-check proof pills — then composite them onto a base clip in the format's signature diagonal cascade and mux the music into the master. FREE and deterministic: the pills are PIL-rendered so the score, checks, and wordmark stay pixel-crisp (a video model would smear type). The base clip (create-image-fal keyframe -> create-video-fal i2v) and the music bed (create-music-elevenlabs) come from separate paid capabilities; this one only does the free rendering.

Run

fetch_icons.py --run-dir <run> ; build_overlays.py --config config.json --out-dir <run>/generated/overlays ; compose_master.py --config config.json --run-dir <run> — reads <run>/generated/clip-handheld.mp4 + generated/music-bed.m4a, writes <run>/master-final.mp4. 1080x1920, deterministic, $0. (Add --no-music to compose for a silent design preview.)

Scripts

  • fetch_icons.py — downloads the three Twemoji PNGs (medal 1f3c5, finger-down 1f447, check 2705) to <run>/assets/icons. PIL cannot render Apple Color Emoji, so pills paste Twemoji PNGs. Free, local.
  • build_overlays.py — PIL: renders the white score header (trailing medal), the orange subhead (trailing finger-down, width-matched to the header), and N green-check proof pills auto-sized to their copy. Bold weight and icon-centered-on-pill-middle are load-bearing.
  • compose_master.py — FFmpeg: scale/crop the base clip to 1080x1920@30, composite the always-on headers, cascade the proof pills (each enable='gte(t,T)' on its own alternating LEFT/RIGHT row), mux the music, apply the anti-AI grain pass, re-encode crf23/maxrate12M -> master-final.mp4.

Contract

  • Deterministic + FREE (PIL + FFmpeg); no paid calls, no AI-rendered text — the score, checks, and wordmark are composited, never generated.
  • Config-driven off one config.json (overlays, layout, duration_sec, optional music/post_production); the template recipe supplies the config from recipe.config.
  • Always re-run build_overlays.py before compose_master.py — the compositor reads pre-rendered PNGs and silently reuses stale ones on a copy change.
  • Headers stay on 0-duration and must not cover the bottle face; proof pills cascade one-per-beat down the diagonal (NOT four-corners) — the cascade is the format's signature.
  • Requires Pillow + ffmpeg. No API keys.

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How to use it

Copy the folder

Take gooseworks-ai/render-proof-points-overlay from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

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