product-design-spec

product-design-spec is a skill for Claude Code from mgiovani/cc-arsenal. It costs 160 tokens per session (2,636 once invoked), scanned A, original, MIT.

A design specification created from an approved product requirements document (PRD). It describes the information structure, user flows, screens, and each screen’s states and interactions without writing interface code.

In plain words
What is it for?
Use it to document a product’s screen inventory, user journeys, states, and interactions while reusing the project’s existing component library.
Why use it?
It gives implementation work a clear design plan and connects every screen to a specific requirement, reducing missing or unsupported design decisions.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: agent in frontmatter; mentions subagents; names the AskUserQuestion tool.

Part of the cc-arsenal-product plugin — 6 skills shipped together , and of cc-arsenal

Good fit Use it to document a product’s screen inventory, user journeys, states, and interactions while reusing the project’s existing component library.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mgiovani/cc-arsenal/product-design-spec
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 mgiovani/cc-arsenal --skill product-design-spec
Clone the repo
git clone --depth 1 https://github.com/mgiovani/cc-arsenal

Made for: Claude Code.

Or install cc-arsenal-product, the plugin that ships this one along with the rest of its 6 skills.

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-spec

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/mgiovani/cc-arsenal/product-design-spec"><img src="https://agentmods.dev/badge/skills/mgiovani/cc-arsenal/product-design-spec.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 160 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,636 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00160 $0.02636
Opus 5 $0.00080 $0.01318
Sonnet 5 $0.00032 $0.00527
Haiku 4.5 $0.00016 $0.00264

Measured 10d ago against content hash 4c040abfb75c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

product-design-spec 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 10d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/screen-states.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/product-design-spec/SKILL.md · 194 lines

How it starts

The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Product Design Spec

Turn an approved PRD into the design half of the spec (IA, flows, a screen inventory, and per-screen state/interaction specs), spec'ing only as much as the work warrants. This skill writes no UI code; it produces the design the build (implement-feature, team-implement) then works from. Output lands under docs/specs/design/.

Input

$ARGUMENTS

Parse the source (first match wins), then read it:

Pattern Source Read via
existing docs/specs/prd/*.md or any path the approved PRD / a file Read it (grab every PRD-<CAT>-NNN ID)
PROJ-123 Jira jira issue view PROJ-123
#42 / owner/repo#42 GitHub issue gh issue view 42 --json title,body,labels,comments
http(s):// URL WebFetch
anything else plain text the idea itself

A trailing --tier small|medium|big overrides the size assessment.

Prerequisites & fallback

Component-library detection and flow research use the Task tool with Explore/haiku subagents. No Task tool? Run every detection and research step inline, sequentially: the phase → gate → phase structure below is the workflow; subagents are just how it parallelizes.

Gate: an approved PRD is the source of truth

A design spec traces to requirements it does not invent. Before spec'ing anything:

  • If an approved PRD (or a clear requirement set) exists, read it and harvest every requirement ID.
  • If no PRD exists, do not fabricate requirements. Stop and say so:

    "There's no approved PRD to trace this design to. Point me at one, or run product-prd first and I'll spec the design against it."

Source-of-truth hierarchy (never silently violate it): approved requirement > design spec > mockup. A mockup or a nice-looking screen never overrides an approved requirement: if the design implies a change, flag it as an open question against the PRD, don't quietly redesign the requirement away.

Lean by default

The organizing principle. Default to a single docs/specs/design/design-spec.md and split a screen into its own file under docs/specs/design/screens/ only when it outgrows the inventory.

Read the full file on GitHub · 194 lines

Files

What ships with it

8 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. 10d ago First seen · 194 lines · 160 tokens per session scan A 4c040abfb75c

Subscribe to this mod's changes

product-design-spec is a skill published in the GitHub repository mgiovani/cc-arsenal (8 stars, last pushed yesterday), licensed MIT. It adds 160 tokens to every session and 2,636 once invoked, about $0.0008 per session on Opus 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 2026-08-31.

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