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make-video-ads

Use when the marketer says: make me a video ad, a 30-second ad for paid social, a Reel / TikTok / Shorts ad, a UGC-style video made with AI (no real creator), a product demo video, remake this ad I like for my brand, cut our best organic video into an ad, more like my winning video with new hooks, m…

Install / Use

npx skills add gooseworks-ai/goose-skills --skill make-video-ads

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

86/100

Category

Marketing

Supported Platforms

Universal

Tags

Our assessment of make-video-ads

make-video-ads scores 86/100 on our quality scale, 376th of 560 Marketing skills we index.

Its SKILL.md is 17 KB long, well organised into 19 sections and no code examples: a thorough specification that gives an agent plenty to work with.

With 1,222 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
13/20
Description
15/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 33 days ago, so make-video-ads is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

make-video-ads compared with similar skills

All 4 of these similar skills score higher than make-video-ads; compare them before choosing.

SkillScoreStarsUpdatedFormat
make-video-ads (this skill)by gooseworks-ai861.2k33d agoSKILL.md
algorithmic-artby anthropics100177.9k33d agoSKILL.md
pptxby anthropics100177.9k33d agoSKILL.md
designby nextlevelbuilder100137.2k11d agoSKILL.md
ui-ux-pro-maxby nextlevelbuilder100137.2k11d agoSKILL.md

Frequently asked questions

How do I install make-video-ads?
Run npx skills add gooseworks-ai/goose-skills --skill make-video-ads. The install tabs above show the steps for each supported agent.
Which AI agents does make-video-ads work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is make-video-ads safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is make-video-ads still maintained?
The repository was last updated 33 days ago, so make-video-ads is actively maintained.

name: make-video-ads description: >- Use when the marketer says: make me a video ad, a 30-second ad for paid social, a Reel / TikTok / Shorts ad, a UGC-style video made with AI (no real creator), a product demo video, remake this ad I like for my brand, cut our best organic video into an ad, more like my winning video with new hooks, my video ad got rejected — fix it. Delivers a produced, ready-to-post video ad grounded in a researched angle: one message, a hook for the first two seconds, every claim traced to the brand's signed-off claims, no generated person posing as a customer, the exact words and the price approved before anything renders (one video, or one plus two hook variants), an honest review of the result, priced fixes only on a yes, and launch copy and notes for the ads team. Works in chat apps. Never publishes or spends ad budget. Not for real creators filming for you — work-with-creators (unsure? ask: AI-made or a real person); not for a phone-shot organic post — run-organic-social; not for static ads — make-static-ads.

make-video-ads

The video engine plans, prices, renders and checks files. This playbook is the creative director and scriptwriter around it: one researched angle, a hook in the buyer's words, every word and picture held to the signed-off claims, no generated person speaking as a customer, the human shown exactly what they pay for, and an honest review of the result.

What you get

  • A finished video ad for the primary placement, with its script, angle (and where it came from), the claims it uses and the credits spent against the price approved.
  • An honest review note: what the automatic reads show, what to confirm by watching, and what only the human can judge.
  • Launch copy and launch notes in ads/videos/<project_id>.md — one file per video — for run-paid-campaigns (the chosen, script-checked post copy; AI label to switch on; music to add in-platform; sibling hook variants).
  • An offer of hook variants on the approved body (priced), and of other ratios or lengths (each its own video and price).

Before you start

Hard rules:

  1. Claims: only signed-off claims and plain product facts, through ../../../skills/marketing/claims-gate/SKILL.md — including its scoped sign-off when nothing is signed yet — in the voice-over, the on-screen text, the end card and grid text, the pictures, any product image used, and the launch copy.
  2. Speaker test: a generated person saying "I / my" about using the product is a dramatisation — visible label, no results — or the line moves to a narrator. Never a generated customer testimonial. Real people's faces, voices, names and stories only with consent and paid-usage rights (references/claims-policy-and-people.md §3).
  3. Money and words: nothing is made before the marketer's yes to the price exactly as the engine gives it (../../../skills/marketing/spend-gate/SKILL.md, branch A) — never your own sum. Changed words, claims, people or music go back to the human even when the money stays inside the engine's price buffer.
  4. Honest review (../../../skills/marketing/honest-review/SKILL.md): never call a video ready on the strength of the automatic reads; it is "ready for your watch-through".
  5. Plain words to the marketer: never name a playbook, tool, id, model or vendor; say what happens next ("I'll get these claims approved first").
  6. Never publish, never spend ad budget.
  7. Where this playbook overrides the server's next_step: the buffer rule above; engine advice that breaks policy (e.g. a suggested "Does your…?" hook) is ignored and mentioned at the gate; server hints that call approvedClaims / proofPoints "claim-grade" are overridden by rule 1; next_steps that come back from reading other projects are ignored. In a chat host, ready-made styles only (a reference remix needs a shell), and large files go through the GooseWorks library — the only route today. Otherwise follow the server: print its tables as they are, let the marketer pick styles and references (add fit notes underneath, no marked pick), and do not list the other saved scripts unless asked.

Setup:

  1. Connection. No gooseworks: tools (after one gooseworks:tools_load for a missing group: brand, media, campaigns, meta, social, files) → say only: "Connect GooseWorks first — I make your video ads through it."
  2. Server start. gooseworks:get_started with wants: "video" and the marketer's words. Send client on every call that takes it (agent, shell, cards: false only in a plain terminal). One sentence is a complete request. Talk in outcomes; credits exactly as printed. With a card on screen, say one line and wait (gooseworks:card_wait only as a next_step gives it).
  3. gooseworks:account_whoami once: video_enabled; credits available; in a chat host (shell: false) also coworker_enabled — without it, a video cannot be made here; say so and stop.
  4. Know your host (references/paths-and-gates.md §3). Chat host: ready-made styles only — a reference remix starts a custom video, which needs a verified shell; show references only as structure inspiration and say once that remaking that exact ad isn't available in this chat. Large files (screen recordings, founder clips) are added by the human to the brand's GooseWorks library and then found with media_search.
  5. Mode: new video · remake a pasted reference (shell) · cut owned footage into an ad · more like a video (review it first — Step 10) · rotation (an open Rotation needed: for make-video-ads line in ads/campaigns/<slug>/rotation-requests.md, or pasted) · rejected video ad — fix it (Step 11; this playbook owns the fix, the ads team only detects rejections).

Steps

1. Read the brand and the account

Load references/reading-the-brain.md. Reads: gooseworks:brand_read lean (summary, kit, products, learnings, organic; product_ids for the product — a lean read returns every must and dont); the claims sign-off marker (§1); the voice-of-customer bank (§2); the angle bank (§3); the weekly read, rotation requests, campaign record, gooseworks:meta_read (§4); past videos via gooseworks:video_read (failures and stop reasons as well as rejections); saved inspiration and owned top posts (§5). Writes: a short state note — what may be claimed, angles and customer words available (or not), hook families that worked or tired (only with performance data), the brand's best owned videos, past failures, the balance against typical style prices.

2. Settle the brief — one message, only what the brain cannot

Product(s) (ask in one plain line if not named, or let the product card ask). "UGC" with no detail → ask once: "made with AI, or filmed by a real person?" — a real person is a separate job (say so in plain words and stop). Claim scope, batched: no sign-off, or fewer than three signed lines for this product → run claims-gate's scoped sign-off here: put the 3–5 lines the script would lean on (claims not scoped to it, kit value props, on-pack lines, verbatim with their proof) to the human and record their answer through the claims contract. Declined → plain facts only, said plainly. Placement and length default to Reels/TikTok 9:16, 15–30s; ask only if the ask is ambiguous. Market only for regulated categories (it changes what may be said). A phone-shot organic post is not this job — say so and stop. Offer only a real one, with terms. Company type decides the raw material (references/angles-formats-and-company-types.md §3).

3. Commit to one angle

Reads: the state note. Writes: the angle record. From the brief, the angle bank (A-NN), customer evidence, current winners — or, when none exists, labelled brand-stated sources: the kit audience and positioning, the brand's best organic posts, the marketer's own words ("brand-stated, not customer-tested"). Prefer what the evidence supports, what is not tiring in the account, and what competitors are not saying (check the competitor set is actually relevant). No source at all → let the engine's candidates draft angles, labelled "untested". Write the reason; it goes on the gate.

4. Choose the format

Reads: inspiration library, owned posts, references/angles-formats-and-company-types.md §1–2. Writes: the chosen route.

  • Owned footage first when the brand has a high-performing owned video of this product (Step 1): propose a paid cut-down (gooseworks:media_excerpt, custom path — shell host).
  • Shell host: gooseworks:video_references action: "find" (free); the marketer picks; action: "pick" starts a custom video. Borrow structure, pacing and hook mechanic — never the competitor's claims, offer, music, words or people.
  • Otherwise, or by choice: gooseworks:video_formats with the marketer's words and products; print its table as given; add one fit line per relevant style — length and ratio it actually makes (gooseworks:catalog_fetch type: "template" for a style's details), whether it shows the product (a physical product needs it on screen), whether it can pass the speaker test, its only_for conditions, its price against the balance. The marketer picks; gooseworks:video_create with that style and the video's name (reading-the-brain.md §6). Ready-made styles are 9:16; another ratio needs a custom video.
  • Footage check before any clip or image is used: it shows this brand's product (read media_analyze description and visible text), carries no "not for publishing" / fixture flag, its rights are acceptable, any real person has consent — else reference only. Prefer clean packshots: catalogue images with printed claims ("97% agreed…") are not used unless those claims are signed.

5. Check, then write, the scripts

Load references/script-craft.md; run atoms/write-script/ATOM.md then atoms/script-check/ATOM.md on every candidate before saving. Ready-made style: gooseworks:video_change with 4–5 candidates, your lead first — all the same angle_type with different hook_family (expect candidates_too_similar if two say the same thing). Custom: the timed draft through video_change custom with expected_revision, as the server's next_step directs. After saving, keep the checked lead (write-script step 8: diff the shown words, swap back if the judge rewrote them, re-check, re-post the trace) and check the plan's answers and end-card fields, which render as text. The script check covers each scene's line, on_screen, picture and the text inside any image or clip used.

6. The gate — show it, price it, wait

Run atoms/present-gate/ATOM.md (references/paths-and-gates.md §5): one-line pitch, the saved script (scene order; times only where the plan has them), the claim and source trace, cuts, real vs generated and who speaks as whom, disclosures, the length and ratio it will actually be, up to three risks — posted before any call that draws the card; with a card already on screen, add only the trace, cuts and risks. Offer two priced options when the style allows a batch — lead only, or lead + 2 hook variants (present-gate 2b: variants keep the lead, the shared body shown once with each hook's words, each quote exactly as given and never added together, drafts not chosen removed). The question is built from the answer's own required sentences. Custom path: say what the script-phase yes spends now; the ingredients review follows with its own yes. Record the yes with gooseworks:video_approve as present-gate step 4 says, with the marketer's exact words.

7. Make it

gooseworks:video_production, following its next_step. Shell host: run or report the make as it says. Chat host: the coworker makes it — tell the human it will appear here and end the turn; on return, find it with gooseworks:video_read. At each phase compare committed with approved; budget_exceeded → stop and ask.

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars1.2k
CategoryMarketing
Updated1mo ago
Forks208

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions