Analyze Video
krusemediallc/arcads-claude-code
Analyze a reference video and reverse-engineer its style into a reusable Seedance 2.0 prompting template.
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…
Install Render Proof Points Overlay
$ npx skills add gooseworks-ai/goose-skills --skill render-proof-points-overlay -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install gooseworks-ai/goose-skills render-proof-points-overlay --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ads/capabilities/render-proof-points-overlay .claude/skills/render-proof-points-overlay && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "render-proof-points-overlay" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-proof-points-overlay into .claude/skills/render-proof-points-overlay/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-proof-points-overlay", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-proof-points-overlayType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add gooseworks-ai/goose-skills --skill render-proof-points-overlay -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install gooseworks-ai/goose-skills render-proof-points-overlay --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ads/capabilities/render-proof-points-overlay .agents/skills/render-proof-points-overlay && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "render-proof-points-overlay" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-proof-points-overlay into .agents/skills/render-proof-points-overlay/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-proof-points-overlay", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gooseworks-ai/goose-skills --skill render-proof-points-overlay -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install gooseworks-ai/goose-skills render-proof-points-overlay --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ads/capabilities/render-proof-points-overlay .cursor/skills/render-proof-points-overlay && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "render-proof-points-overlay" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-proof-points-overlay into .cursor/skills/render-proof-points-overlay/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-proof-points-overlay", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/gooseworks-ai/goose-skills.git --path skills/ads/capabilities/render-proof-points-overlay--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add gooseworks-ai/goose-skills --skill render-proof-points-overlay -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install gooseworks-ai/goose-skills render-proof-points-overlay --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ads/capabilities/render-proof-points-overlay .gemini/skills/render-proof-points-overlay && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "render-proof-points-overlay" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-proof-points-overlay into .gemini/skills/render-proof-points-overlay/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-proof-points-overlay", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install gooseworks-ai/goose-skills render-proof-points-overlayInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add gooseworks-ai/goose-skills --skill render-proof-points-overlay -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ads/capabilities/render-proof-points-overlay .github/skills/render-proof-points-overlay && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "render-proof-points-overlay" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-proof-points-overlay into .github/skills/render-proof-points-overlay/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-proof-points-overlay", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gooseworks-ai/goose-skills --skill render-proof-points-overlay -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install gooseworks-ai/goose-skills render-proof-points-overlay --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ads/capabilities/render-proof-points-overlay .opencode/skills/render-proof-points-overlay && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "render-proof-points-overlay" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-proof-points-overlay into .opencode/skills/render-proof-points-overlay/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-proof-points-overlay", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
render-proof-points-overlay- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 641 words
- Files
- 10 (incl. scripts, references)
- Skills in repo
- 273
- Repo updated
- First seen
- Licence
- MIT
At a glance
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…
- The overlay-proof-points format
- SKILL.md covers Run, Scripts, Contract and Choices, plus 2 more sections
- Runs Python scripts from its folder; calls python
- The base clip + music come from separate paid capabilities
What it does
Render Proof Points Overlay is an agent skill from gooseworks-ai/goose-skills. 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.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including scripts and reference files (for example `references/music.md`, `scripts/build_overlays.py` and `scripts/compose_master.py`).
It sits in Marketing & SEO, covering Influencer and creator marketing. It works with FFmpeg. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.
When your agent uses it
- The overlay-proof-points format
- The base clip + music come from separate paid capabilities
Example prompts
- “perfect-score + proof-points”
- “/render-proof-points-overlay”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit c650c6d. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 4 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Render Proof Points Overlay loads about 1.3k tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 137 tokens; SKILL.md has 641 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 641 words, ~1,311 tokens.
Download SKILL.mdSave it as
.claude/skills/render-proof-points-overlay/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.- name
- render-proof-points-overlay
- description
- 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.
- status
- active
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 (eachenable='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, optionalmusic/post_production); the template recipe supplies the config fromrecipe.config. - Always re-run
build_overlays.pybeforecompose_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 product 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. - The overlay copy (
overlays.header.lines,overlays.subhead.lines,overlays.proof_points) is per brand and must be the brand's own approved claims;build_overlays.pyexits with a clear message if any of it is empty (the template recipe ships it empty, withoverlays._example_contentas the shape).
Show full SKILL.md (274 more words)Show less
Choices
This atom renders no people, setting or music. The template's creative choices (whose hand, the setting, the music style) are asked of the user by the recipe and go to the paid keyframe / i2v / music capabilities; this atom only composites the pills over whatever base clip and music bed it is given.
Music coverage
Read the music preparation instructions for the composition options and listening checks.
The bed must cover the complete master, including its end card. Composition checks audio coverage before rendering and stops for missing, short or prematurely silent music. A silent preview requires the explicit no-music option.
Use a full-length approved bed first. For an approved instrumental that can repeat cleanly, the loop-music option trims silent edges and extends it locally with crossfades. It preserves the source and puts the final half-second fade at the master ending. Do not loop speech, lyrics or a musical ending that makes the join obvious. Do not regenerate paid music automatically.
Listen to every join and the final seconds before delivery. The automated check detects silence and insufficient duration; it does not judge musical phrasing, a gradual early fade or how the bed sounds under dialogue.
Local layout checks
The renderer preserves the bold text font and falls back to an installed symbol font for missing glyphs such as ★. Trailing icons sit beyond the longest line of the pill. The composer reserves at least 120 px at the right edge for platform controls and stops if copy does not fit; wrap the text or reduce its font size before rendering.
Run the free regressions with python -m unittest discover -s tests -p 'test_*.py' -v.
© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 9 other files (scripts, references) in skills/ads/capabilities/render-proof-points-overlay of gooseworks-ai/goose-skills.
- SKILL.md
- references/music.md
- scripts/build_overlays.py
- scripts/compose_master.py
- scripts/fetch_icons.py
- scripts/music_coverage.py
- skill.meta.json
- tests/smoke-test.md
- tests/test_layout.py
- tests/test_music.py
Open the folder on GitHubat commit c650c6d
Compare with similar skills
Render Proof Points Overlay next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Render Proof Points Overlay this skillgooseworks-ai/goose-skills | 1.2k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Analyze Videokrusemediallc/arcads-claude-code | 1.6k | — | ~4.2k | Automated safety check: Pass | MIT | |
| Reelclaw Adsdansugc/reelclaw | 145 | — | ~3.9k | Automated safety check: Notes | MIT | |
| Super Video MakerBomx/super-video-maker-skill | 310 | — | ~11k | Automated safety check: Notes | None | |
| Reelclawdansugc/reelclaw | 145 | 1 repos | ~8.2k | Automated safety check: Notes | None | |
| Bggg Tiktok Readvideobinggandata/bggg-skills | 605 | — | ~1.6k | Automated safety check: Pass | MIT |
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Categories
Questions about Render Proof Points Overlay
What does Render Proof Points Overlay do?
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…. Render Proof Points Overlay is an agent skill from gooseworks-ai/goose-skills.mp4.
When should I use Render Proof Points Overlay?
Render Proof Points Overlay fits situations like: the overlay-proof-points format; the base clip + music come from separate paid capabilities.
How do I install Render Proof Points Overlay in Claude Code?
Run `npx skills add gooseworks-ai/goose-skills --skill render-proof-points-overlay -a claude-code`. Or copy the skill folder (skills/ads/capabilities/render-proof-points-overlay in gooseworks-ai/goose-skills) into .claude/skills/render-proof-points-overlay in your project. Claude Code loads it when a task matches its description.
How do I install Render Proof Points Overlay in Codex?
Run `npx skills add gooseworks-ai/goose-skills --skill render-proof-points-overlay -a codex`. Or copy the skill folder (skills/ads/capabilities/render-proof-points-overlay in gooseworks-ai/goose-skills) into .agents/skills/render-proof-points-overlay in your project. Codex loads it when a task matches its description.
Can I use Render Proof Points Overlay in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gooseworks-ai/goose-skills --skill render-proof-points-overlay -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/render-proof-points-overlay, .gemini/skills/render-proof-points-overlay, .github/skills/render-proof-points-overlay and .opencode/skills/render-proof-points-overlay in your project.
What does Render Proof Points Overlay need to run?
Going by SKILL.md and its folder, Render Proof Points Overlay needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Render Proof Points Overlay access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Render Proof Points Overlay safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Render Proof Points Overlay use?
Render Proof Points Overlay is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Render Proof Points Overlay use?
About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 317 tokens, read only when the agent opens those files.
What are the alternatives to Render Proof Points Overlay?
Skills that share tags, products or a category with Render Proof Points Overlay: Analyze Video (krusemediallc/arcads-claude-code, 1.6k stars), Reelclaw Ads (dansugc/reelclaw, 145 stars), Super Video Maker (Bomx/super-video-maker-skill, 310 stars) and Reelclaw (dansugc/reelclaw, 145 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Render Proof Points Overlay?
gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.
Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.