video-production-harness

video-production-harness is a skill for Claude Code, Codex from gooseworks-ai/goose-skills. It costs 48 tokens per session (1,301 once invoked), scanned A, original, MIT.

A guided process for producing videos from a brief, including script review, approved ingredients, controlled generation, editing, captions, quality checks, and final delivery.

In plain words
What is it for?
Use it to run end-to-end video production when a host provides storage, approvals, provider access, and billing.
Why use it?
It makes clear which approvals and inspections are required, so a successful script or export is not mistaken for an approved final video.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to run end-to-end video production when a host provides storage, approvals, provider access, and billing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gooseworks-ai/goose-skills/video-production-harness
About the project

Goose Skills is a library of workflows and data APIs that lets coding agents handle growth and go-to-market work such as advertising, social media, content, SEO, lead generation, and customer research. It is intended for teams using Claude Code, Cursor, Codex, and similar agents. The catalogue entries are its reusable skills.

gooseworks-ai/goose-skills · 1,254 stars · on GitHub · gooseworks.ai

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add gooseworks-ai/goose-skills --skill video-production-harness
Clone the repo
git clone --depth 1 https://github.com/gooseworks-ai/goose-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for video-production-harness

README.md
[![agentmods](https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/video-production-harness/github.svg)](https://agentmods.dev/skills/gooseworks-ai/goose-skills/video-production-harness)
Your own site
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/video-production-harness"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/video-production-harness/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for video-production-harness

Your own site · 80×15
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/video-production-harness"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/video-production-harness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,301 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00048 $0.01301
Opus 5.5 $0.00019 $0.00520
Sonnet 5.5 $0.00010 $0.00260
Haiku 4.5 $0.00005 $0.00130

Measured today against content hash e4ba4bd5d201, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

video-production-harness scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.

The scan reads SKILL.md. This mod also ships 12 executable files (scripts/assemble_sources.py, scripts/assemble.py, scripts/assembly_timeline.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/ads/playbooks/video-production-harness/SKILL.md · 44 lines

How it starts

The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Non-negotiables (every state, every host)

  1. Copy the reference. Study the whole reference, picture and sound. Keep its people, action, camera, hook, length (±25%) and its shot and setup counts (±30%, from scripts/reference_shots.py); list every change in changes_from_reference, shown first at the script approval.
  2. Match its sound and pace. Speech, music and effects follow the reference. Silence only when the reference is silent or the owner asks for it. Never a sine tone, a drone or an empty track. scripts/reference_rate.py measures the reference's words per second (never estimate it); a voice more than 10% slower is regenerated or sped up (at most 1.25×) before lip-sync and picture timing.
  3. People and demos stay people and demos. Plan a person, hands or a live demonstration in the reference as one; never plan a text card, dots or a still in its place. One that ends up on screen anyway is an ask finding you recommend fixing.
  4. The script comes from write-video-ad-script. Fetch it with catalog_fetch; never write the script inline.
  5. Use the real product. Its real photos, its real size and its usage steps. A still packshot gets the real photo through overlay. A pack held or used on screen is made with openai/gpt-image-2/edit, the real product photo as reference image 1, front label facing the camera. A blank, unprinted or label-less brand pack is must_fix. Every use step and product state (dry contents, cooked dish, strip on the nose) comes from a real brand photo sent as a reference.
  6. Look real. Phone capture, deep focus, no bokeh, a lived-in room, no retouching or beauty filter, clothes that fit the activity. Every photoreal still and every motion prompt, B-roll included, carries the one light and realism block in libraries, look and rubric: light from a window or lamp, normal exposure, no HDR, matte skin, no over-sharpening, the first frame's light kept.
  7. Review the final against the reference, listened or measured, never claimed. scripts/qc_evidence.py must exit 0 on the exact final bytes (it fails only a broken file); then mark the video complete and read the host's final check.
  8. Two owner approvals, both in this chat: the script and the ingredients. In review_mode: auto one yes to the full total covers both (see check severity). Agent checks add no other approval step.
  9. Quality warns, never blocks. Every finding is must_fix (always redone, never delivered), ask (shown with the price of the fix; in review_mode: auto you decide) or fine (kept). Only money, consent, safety and broken files stop the run. A redo is paid from the approved total when it fits, otherwise after a new yes to its price; never drop a scene. See check severity.

Reading rule. Read one file per call. If the output says it was truncated, re-read that file in parts before acting.

Read the full file on GitHub · 44 lines

Files

What ships with it

53 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. today Changed · +1 lines e4ba4bd5d201
  2. yesterday Changed · +9 lines 3e659d9dc200
  3. 12d ago Changed · +14 lines e12896636e68
  4. 15d ago First seen · 20 lines · 48 tokens per session scan A aba66dd45ba5

Subscribe to this mod's changes

video-production-harness is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,254 stars, last pushed today), licensed MIT. It adds 48 tokens to every session and 1,301 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-03.

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