Agent skill

Render Myth Vs Fact

by gooseworks-ai in gooseworks-ai/goose-skills

Install Render Myth Vs Fact

skills CLI

$ npx skills add gooseworks-ai/goose-skills --skill render-myth-vs-fact -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install gooseworks-ai/goose-skills render-myth-vs-fact --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ 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-myth-vs-fact .claude/skills/render-myth-vs-fact && rm -rf skills-src

Use ~/.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/

Paste into Claude Code

Install the "render-myth-vs-fact" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-myth-vs-fact into .claude/skills/render-myth-vs-fact/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-myth-vs-fact", 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

$skill-installer install https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-myth-vs-fact

Type 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.

skills CLI

$ npx skills add gooseworks-ai/goose-skills --skill render-myth-vs-fact -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install gooseworks-ai/goose-skills render-myth-vs-fact --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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-myth-vs-fact .agents/skills/render-myth-vs-fact && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "render-myth-vs-fact" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-myth-vs-fact into .agents/skills/render-myth-vs-fact/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-myth-vs-fact", 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.

skills CLI

$ npx skills add gooseworks-ai/goose-skills --skill render-myth-vs-fact -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install gooseworks-ai/goose-skills render-myth-vs-fact --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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-myth-vs-fact .cursor/skills/render-myth-vs-fact && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "render-myth-vs-fact" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-myth-vs-fact into .cursor/skills/render-myth-vs-fact/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-myth-vs-fact", 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

$ gemini skills install https://github.com/gooseworks-ai/goose-skills.git --path skills/ads/capabilities/render-myth-vs-fact

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add gooseworks-ai/goose-skills --skill render-myth-vs-fact -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install gooseworks-ai/goose-skills render-myth-vs-fact --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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-myth-vs-fact .gemini/skills/render-myth-vs-fact && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "render-myth-vs-fact" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-myth-vs-fact into .gemini/skills/render-myth-vs-fact/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-myth-vs-fact", 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.

GitHub CLI

$ gh skill install gooseworks-ai/goose-skills render-myth-vs-fact

Installs 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).

skills CLI

$ npx skills add gooseworks-ai/goose-skills --skill render-myth-vs-fact -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ 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-myth-vs-fact .github/skills/render-myth-vs-fact && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "render-myth-vs-fact" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-myth-vs-fact into .github/skills/render-myth-vs-fact/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-myth-vs-fact", 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.

skills CLI

$ npx skills add gooseworks-ai/goose-skills --skill render-myth-vs-fact -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install gooseworks-ai/goose-skills render-myth-vs-fact --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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-myth-vs-fact .opencode/skills/render-myth-vs-fact && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "render-myth-vs-fact" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-myth-vs-fact into .opencode/skills/render-myth-vs-fact/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-myth-vs-fact", 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-myth-vs-fact
GitHub stars: 1.2k
Token cost: ~2.2k tokens
SKILL.md length: 1,003 words
Files: 15 (incl. scripts)
Skills in repo: 273
Repo updated: Oct 8, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

The myth-vs-fact format
SKILL.md covers The 8-beat spine (roles), Scripts (free — Python +…, Inputs (all via --config + a… and Choices, plus 2 more sections
Runs Python and JavaScript scripts from its folder
Tasks that involve Video production

What it does

Render Myth Vs Fact is an agent skill from gooseworks-ai/goose-skills. Assemble a myth-vs-fact kinetic-typography explainer video ad (≈29.5s, 9:16) from N myth/fact pairs + hook / turn / punch copy + palette + a brand end-card PNG + a VO track — a hook, 3 red-strike MYTH cards that flip to teal-check FACT cards (per-line strikethrough that crosses EVERY wrapped line), a "what actually works" turn, an optional proof reveal, a punch line, and a static end card. DETERMINISTIC assembly with ZERO AI-gen visuals — HTML hyperframes rendered frame-exact via Playwright (window.renderAt(t)…

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 17 other files, including scripts (for example `scripts/beat_snap.py`, `scripts/compose.py` and `scripts/config.example.json`).

It sits in Media & Creative, covering Video production, Motion graphics and Speech recognition and synthesis. It works with Playwright, FFmpeg, Python and HeyGen. 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 myth-vs-fact format
Tasks that involve Video production
Tasks that involve Motion graphics

Example prompts

“what actually works”
“/render-myth-vs-fact”

Requirements

Python 3
Node.js

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 12 files in scripts/ (Python and JavaScript), which the agent can run.
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 Myth Vs Fact loads about 2.2k tokens when it runs. Until then it costs about 251 tokens; SKILL.md has 1,003 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~251
When it runs · the whole SKILL.md, loaded when a task matches: ~2.2k

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). 1,003 words, ~2,189 tokens.

Download SKILL.mdSave it as .claude/skills/render-myth-vs-fact/SKILL.md (or your agent's skills folder). This skill also uses 14 other files; get the full folder from GitHub.

name: render-myth-vs-fact
description: Assemble a myth-vs-fact kinetic-typography explainer video ad (≈29.5s, 9:16) from N myth/fact pairs + hook / turn / punch copy + palette + a brand end-card PNG + a VO track — a hook, 3 red-strike MYTH cards that flip to teal-check FACT cards (per-line strikethrough that crosses EVERY wrapped line), a "what actually works" turn, an optional proof reveal, a punch line, and a static end card. DETERMINISTIC assembly with ZERO AI-gen visuals — HTML hyperframes rendered frame-exact via Playwright (`window.renderAt(t)`, animation a pure function of beat-local time), Whisper beat-snap to VO word onsets, concat at a uniform fps, karaoke `.ass` captions burned last (suppressed on the proof + end-card beats), and a VO + optional music mix (music −20 dB, `amix normalize=0`, tail fade). FREE (Python + Playwright + ffmpeg); the recipe supplies the copy / palette / end-card / VO and gates the paid VO / music / Whisper calls to their own capabilities. Use for the myth-vs-fact format.
status: active

render-myth-vs-fact

The free, deterministic renderer for the myth-vs-fact video ad format — the sound-off-safe kinetic-typography explainer that busts N common myths and hands the viewer a credible resolution. Red-strike MYTH cards flip to teal-check FACT cards over a VO (voice + tone are the caller's choice; the demo used a calm-authority expert), then a "what actually works" turn + an optional proof reveal + a punch line + a static brand end card.

Every on-screen word is a deterministic HTML hyperframe — no AI image/video gen, no b-roll, no character. Visuals cost $0. The only metered spend is upstream (VO + Whisper word-timestamps + an optional music bed), gated to its own capabilities. This capability OWNS the whole FREE assembly: beat-snap → render → captions → mix → burn → master. Iterate the cut for free; re-roll only the offending paid audio beat.

It ports the validated build from the Clinikally "acne myths" run — brand-neutralised, config-driven, and portable (no /Users, no clients/; everything via --config + --work-dir).

SOUND-OFF SAFE is the whole point: every claim is legible on-screen and the VO only reinforces it. VO-FIRST: render the VO, extract Whisper word onsets on the RENDERED audio, then snap every beat boundary + strike wipe + reveal to those onsets.

The 8-beat spine (roles)

hook → 3× myth-fact (the flip triad — identical grammar so it reads as a pattern) → turn (the "what actually works" pivot) → proof (optional actives/proof reveal, omit if empty) → punch (full-frame closer) → end-card (the static brand PNG). Each beat carries its role, duration, and its copy; ONE role template renders any pair.

Scripts (free — Python + Playwright + ffmpeg, no paid calls)

scripts/beat_snap.py — VO-first alignment. FAL Whisper word-timestamps on the RENDERED VO → re-snap every beat boundary to the nearest word onset. Writes beat-manifest.json + whisper/words-flat.json into the work dir. --no-whisper keeps the config durations un-snapped for a fully offline run.
scripts/render_beats.py — the deterministic renderer. Per mg beat: pick the role template under hyperframes/, inject the beat's copy + palette + fonts as window.BEAT, drive window.renderAt(t) frame-by-frame via Playwright, screenshot each frame → ffmpeg at EXACTLY the configured fps (default 25/1). The end-card beat is built from the pre-supplied brand PNG (scale/crop + a ~0.35s fade-up) — never generated per run.
scripts/make_captions.py — karaoke .ass from the manifest + Whisper words. ≤3 words per cue; close on a >0.4s gap / beat-window edge / sentence-ending punctuation. Captions are burned ONLY in caption-allowed windows; the proof + end-card beats are suppressed.
scripts/compose.py — the assembler: concat the beats → mix VO + optional music (music −20 dB, amix normalize=0, ~0.8s tail fade) → burn the .ass LAST → master mp4.
scripts/config.example.json — the shape of the brand config the recipe binds (the brand-neutralised Clinikally values as a worked reference).
scripts/hyperframes/ — the bundled hyperframe scaffold: _shared.css (palette-tokened tokens + card/tag/fact/pill/chain type), _shared.js (the initRenderer / springScale / buildLineStrikes + strikeLines per-line-strike / popIn / revealWords helpers + config injection), and one template per role (beat-hook.html, beat-myth-fact.html, beat-turn.html, beat-proof.html, beat-punch.html).

Inputs (all via `--config` + a runtime work dir — NO hardcoded paths)

config.json carries: fps (25) / width / height; vo + optional music + mix{music_db:-20, tail_fade:0.8}; palette (the five CSS-var tokens bg, myth_strike, fact_accent, headline_ink, accent); brand_name; display_font; end_card_png + end_card_fade; caption_style; suppress_beats; and beats[] — each {n, role, duration, captions, cues{...}} plus the role's copy:

hook: eyebrow, hook_line, emphasis, strike_word
myth-fact: myth_index, myth_line, and either fact_line (a [bracketed] phrase becomes the accented payload) OR fact_clauses[] (a staggered clause chain)
turn: turn_slate, turn_sub ([brackets] → emphasis)
proof: proof_eyebrow, proof_items[] ({name, badge}), proof_footnote
punch: punch_line
end-card: none (built from end_card_png)

The recipe's myth_fact_pairs, hook_line, turn_slate, punch_line, palette, end_card_png, and optional actives_or_proof map onto these beats 1:1. See config.example.json (a worked example — the Clinikally acne build; its copy and palette are that brand's, never defaults).

Show full SKILL.md (422 more words)Show less

Choices

The creative calls the caller makes upstream (the video-format recipe asks the user). This renderer never picks them — it only consumes the rendered files and copy:

Narrator voice → the vo file (made by create-vo-elevenlabs). The demo used a calm expert voice.
Tone → the VO direction + the hook / turn / punch copy. The demo was calm-authority, warm, plain-language.
Music → the optional music file (made by create-music-elevenlabs). The demo used a calm clinical pad + sparse warm keys, no drums.

The palette is a brand fact (brand kit), not a choice.

Craft rules (load-bearing — faithful to the source molecule)

MYTH strikethrough is PER-LINE. Measure each wrapped line box (Range.getClientRects, deduped to one rect per visual line) and lay one red bar at each line's vertical MIDDLE, driven as ONE continuous L→R sweep. A single fixed-Y rule reads as an underline the moment the headline wraps.
The end card is the pre-built brand PNG — NEVER generated per run. Scale/crop to the canvas with a short fade-up; it carries its own baked logo + claim + CTA.
Animation is a pure function of beat-local time — no setTimeout, no CSS keyframes — so Playwright seeks frame-exact and the render is fully reproducible.
Every beat mp4 is exactly the configured fps (25/1). render_beats.py enforces + warns; a mismatch makes the concat demuxer silently drop frames.
All text fits the 88% safe area at the ~15% spring-overshoot PEAK, not at rest.
Captions burned LAST, ≤3 words/cue, closing on >0.4s gap / window edge / sentence end. The ASS Events Format: line MUST carry the Name field or every cue gets a leading-comma artifact. Suppress the proof/footnote + end-card beats (two text layers at one spot both go unreadable).
Mix constants are validated — music −20 dB under the VO, amix normalize=0 (with normalize on the bed pumps), ~0.8s tail fade. Sound-off must still work without the bed.
Keep the MYTH triad's flip grammar + internal timing identical so it reads as a pattern (anaphora).

Requires

Python 3 + Playwright chromium (pip install playwright && playwright install chromium) for the frame-exact hyperframe render, and ffmpeg/ffprobe on PATH. If Playwright is unavailable, compose.py + make_captions.py (the concat / mix / caption path) still run; only render_beats.py needs the browser.
watch (QC the final master — the red strike crosses the vertical MIDDLE of EVERY wrapped myth line, the VO is intelligible, captions are legible with no card collision, suppression is correct on the proof + end-card beats, framerate is uniform 25/1, no clipping, every claim is legible sound-off). The recipe gates the paid create-vo-eleven (VO), create-music-elevenlabs (bed), and FAL Whisper calls — this capability itself makes NO paid calls.

Files

SKILL.md and 14 other files (scripts) in skills/ads/capabilities/render-myth-vs-fact of gooseworks-ai/goose-skills.

SKILL.md
scripts/beat_snap.py
scripts/compose.py
scripts/config.example.json
scripts/hyperframes/_shared.css
scripts/hyperframes/_shared.js
scripts/hyperframes/beat-hook.html
scripts/hyperframes/beat-myth-fact.html
scripts/hyperframes/beat-proof.html
scripts/hyperframes/beat-punch.html
scripts/hyperframes/beat-turn.html
scripts/make_captions.py
scripts/render_beats.py
skill.meta.json
tests/smoke-test.md

Open the folder on GitHubat commit c650c6d

Compare with similar skills

Render Myth Vs Fact 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.

Render Myth Vs Fact compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Render Myth Vs Fact this skillgooseworks-ai/goose-skills	1.2k	—	~2.2k	Automated safety check: Pass	MIT	2 days ago
KinocutKyaniteLabs/kinocut	198	—	~5.7k	Automated safety check: Pass	Apache-2.0	yesterday
Motion Adfabricioctelles/skills	106	—	~4.1k	Automated safety check: Pass	Apache-2.0	today
Browser Video Recordingnirholas/three.ws	230	1 repos	~1.5k	Automated safety check: Pass	Apache-2.0	today
Motion FilmCoWork-OS/CoWork-OS	477	—	~2.4k	Automated safety check: Pass	MIT	yesterday
Motion EditorCoWork-OS/CoWork-OS	477	—	~2.1k	Automated safety check: Pass	MIT	yesterday

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Works with

Questions about Render Myth Vs Fact

What does Render Myth Vs Fact do?

Assemble a myth-vs-fact kinetic-typography explainer video ad (≈29.5s, 9:16) from N myth/fact pairs + hook / turn / punch copy + palette + a brand end-card PNG + a VO track — a hook, 3 red-strike…. Render Myth Vs Fact is an agent skill from gooseworks-ai/goose-skills.5s, 9:16) from N myth/fact pairs + hook / turn / punch copy + palette + a brand end-card PNG + a VO track — a hook, 3 red-strike MYTH cards that flip to teal-check FACT cards (per-line strikethrough that crosses EVERY wrapped line), a "what actually works" turn, an optional proof reveal, a punch line, and a static end card.

When should I use Render Myth Vs Fact?

Render Myth Vs Fact fits situations like: the myth-vs-fact format; tasks that involve Video production; tasks that involve Motion graphics.

How do I install Render Myth Vs Fact in Claude Code?

Run `npx skills add gooseworks-ai/goose-skills --skill render-myth-vs-fact -a claude-code`. Or copy the skill folder (skills/ads/capabilities/render-myth-vs-fact in gooseworks-ai/goose-skills) into .claude/skills/render-myth-vs-fact in your project. Claude Code loads it when a task matches its description.

How do I install Render Myth Vs Fact in Codex?

Run `npx skills add gooseworks-ai/goose-skills --skill render-myth-vs-fact -a codex`. Or copy the skill folder (skills/ads/capabilities/render-myth-vs-fact in gooseworks-ai/goose-skills) into .agents/skills/render-myth-vs-fact in your project. Codex loads it when a task matches its description.

Can I use Render Myth Vs Fact 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-myth-vs-fact -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-myth-vs-fact, .gemini/skills/render-myth-vs-fact, .github/skills/render-myth-vs-fact and .opencode/skills/render-myth-vs-fact in your project.

What does Render Myth Vs Fact need to run?

Going by SKILL.md and its folder, Render Myth Vs Fact needs Python and JavaScript for the scripts in its folder. Our summary lists: Python 3; Node.js.

Does Render Myth Vs Fact 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 Myth Vs Fact 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 Myth Vs Fact use?

Render Myth Vs Fact 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 Myth Vs Fact use?

About 2.2k tokens (SKILL.md is roughly 8.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Render Myth Vs Fact?

Skills that share tags, products or a category with Render Myth Vs Fact: Kinocut (KyaniteLabs/kinocut, 198 stars), Motion Ad (fabricioctelles/skills, 106 stars), Browser Video Recording (nirholas/three.ws, 230 stars) and Motion Film (CoWork-OS/CoWork-OS, 477 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Render Myth Vs Fact?

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.

Install Render Myth Vs Fact

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

render-myth-vs-fact

The 8-beat spine (roles)

Scripts (free — Python + Playwright + ffmpeg, no paid calls)

Inputs (all via --config + a runtime work dir — NO hardcoded paths)

Choices

Craft rules (load-bearing — faithful to the source molecule)

Requires

Files

Compare with similar skills

Similar skills

More from gooseworks-ai/goose-skills

Related

Questions about Render Myth Vs Fact

Inputs (all via `--config` + a runtime work dir — NO hardcoded paths)