product-design

product-design is a skill for Codex from autonomous-ai/autonomous-workshop. It costs 203 tokens per session (4,716 once invoked), scanned A, original, Apache-2.0.

A product-design planning skill for turning a written object idea into a considered design before computer-aided design, or CAD, work begins. CAD is software used to model physical objects.

In plain words
What is it for?
Use it to study existing products, define requirements and a design direction, explore concepts, choose one, and critique later models. It produces design documents rather than geometry.
Why use it?
It prevents the first technical model from deciding the product's shape and appearance by accident. It also treats practical fit, function, and visual quality as requirements to review.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: $skill-name invocation.

Good fit Use it to study existing products, define requirements and a design direction, explore concepts, choose one, and critique later models. It produces design documents rather than geometry.

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Install with agentmods
npx agentmods add skills/autonomous-ai/autonomous-workshop/product-design
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 autonomous-ai/autonomous-workshop --skill product-design
Clone the repo
git clone --depth 1 https://github.com/autonomous-ai/autonomous-workshop

Made for: 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 product-design

README.md
[![agentmods](https://agentmods.dev/badge/skills/autonomous-ai/autonomous-workshop/product-design/github.svg)](https://agentmods.dev/skills/autonomous-ai/autonomous-workshop/product-design)
Your own site
<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-workshop/product-design"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-workshop/product-design/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 product-design

Your own site · 80×15
<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-workshop/product-design"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-workshop/product-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 203 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,716 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 $0.00203 $0.04716
Opus 5.5 $0.00081 $0.01886
Sonnet 5.5 $0.00041 $0.00943
Haiku 4.5 $0.00020 $0.00472

Measured 16d ago against content hash 4d101af4d3d9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

product-design 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 16d ago.

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.

src/workshop/make/skills/product-design/SKILL.md · 342 lines

How it starts

The opening of the file, as written. The whole thing — 342 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Product design — design the object before CAD builds it

Purpose

A reference image arrives with its design already made, and $image-to-cad reads it. A prose request arrives without one: "a phone stand" fixes a category and nothing else. Handed straight to $cad, the CAD turn becomes the designer and builds the first shape that satisfies the words — a block with a slot, one small fillet on every edge. No gate notices: every geometry check passes an object nobody would want on their desk.

This skill is the designer the flow was missing. Work the way an industrial designer does: understand what the object is for and who lives with it, study how it is already made and which versions people find beautiful, set a design direction before drawing anything, explore concepts and choose one on purpose, and then critique the built model in rounds until it looks right. The object must work, print and fit — and it must be beautiful. Beauty is not left to whatever the first CAD pass produces; it is a requirement, designed in order (big form to detail) and reviewed against written rules (wiki show product-aesthetics).

You produce a document, not geometry. Fill templates/design_spec.md and hand off to $cad; the design-review rounds then run on $cad's renders and are recorded back in the spec.

Inside a Workshop product run resolve CAD_SKILL_ROOT="$(workshop skills path)/cad" and IMAGE_TO_CAD_SKILL_ROOT="$(workshop skills path)/image-to-cad", and read a skills/<name>/... path in these pages under "$(workshop skills path)/<name>/". Upstream's $stl-to-step and $step-to-source are not Workshop skills; a supplied STL or STEP still does not fire this one. Five things change there:

  • It fires only while the design is open: a prose Wish with no sealed Invent concept, Design Contract or reference image. A sealed concept or contract is the design, so its survey, direction and concept selection are never reopened here; an image to reproduce goes to $image-to-cad.
  • The selected Inventor's TASTE.md governs creative judgment. The design direction works inside it, and the Wish's words stand where this page says the user's words do. There is no user to ask or to accept a finding.
  • Review rounds spend Make's own allowance. They run inside the round and review budget the host froze, never replace the Make reference's blind signature review, and stop when that budget does; a finding still open then is reported in the final response, not chased past it.
  • The spec lives in the run's CAD project, beside the entries $cad builds, not under output/.
  • Final verification is the one the Make reference names. Do not add --fresh in a product run: the host performs the isolated fresh rebuild.

Read the full file on GitHub · 342 lines

Files

What ships with it

2 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. 16d ago First seen · 342 lines · 203 tokens per session scan A 4d101af4d3d9

Subscribe to this mod's changes

product-design is a skill published in the GitHub repository autonomous-ai/autonomous-workshop (21 stars, last pushed today), licensed Apache-2.0. It adds 203 tokens to every session and 4,716 once invoked, about $0.0008 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 2026-10-01.

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