deploy-prototype

A tool that builds a small browser-based app or utility and deploys it live on Vercel, a service for hosting web projects.

In plain words
What is it for?
Use it to create and publish prototypes such as visualizations, market tools, APIs, or landing pages. It can also choose a project from recent workspace context when no clear brief is provided.
Why use it?
It turns an idea, research result, or data signal into something people can use without requiring a separate manual deployment process.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/aeonfun/aeon/deploy-prototype
Any agent
npx skills add aeonfun/aeon --skill deploy-prototype
Clone the repo
git clone --depth 1 https://github.com/aeonfun/aeon

Made for: Claude Code, Codex.

Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,789 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 findings. Scan, not verified.
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 $0.00020 $0.03789
Opus 5 $0.00010 $0.01895
Sonnet 5 $0.00004 $0.00758
Haiku 4.5 $0.00002 $0.00379

Measured 2d ago against content hash 8bb7f04ace3e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

deploy-prototype scanned grade C with 2 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 2d 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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

rm -rf .pending-deploy # clear stale state from prior runs

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

Otherwise POST the inline deployment built in step 6. Write the key as the literal `{VERCEL_TOKEN}` placeholder so `./secretcurl` substitutes it internally — a bare `$VERCEL_TOKEN` on the command line is refused by the B
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/deploy-prototype/SKILL.md · 215 lines

How it starts

The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.

${var} — What to build and deploy.

  • Empty → auto-select from recent signals (articles, logs, memory topics).
  • Plain text (e.g. market heatmap) → interpret as a build brief.
  • Typed form type:slug description (e.g. tool:market-heatmap volume heatmap of top-20 tokens, viz:tx-graph, api:summarize, landing:startup-idea) → use type to bias shape and slug as the deployment name.

Today is ${today}. Your task is to ship a small, self-contained prototype that someone could actually use in the browser today.

Steps

  1. Read context. Read memory/MEMORY.md and the most recent entries in memory/logs/ for active topics. If running as part of a chain, scan injected upstream outputs for a concrete artifact worth making interactive.

  2. Pick what to build (if ${var} is empty or vague).

    Scan these sources, in order, for prototype-worthy signals:

    • output/articles/ — last 7 entries by mtime: any claim, finding, or dataset that would be more useful as an interactive page?
    • memory/topics/*.md — running narratives; pick one with a live data source (prices, feeds, markets)
    • memory/logs/${today}.md and the two prior days — skill outputs flagged as interesting
    • memory/MEMORY.md → "Next Priorities" and "Recent Articles"

    Score each candidate 1-5 on:

    • Leverage — does an interactive version beat the static write-up?
    • Concreteness — is the spec obvious in one sentence? (if no, reject)
    • Novelty — haven't shipped this in the last 14 days (check output/articles/prototype-*.md by mtime and any memory/topics/prototypes.md)

    Pick the highest-total candidate. If no candidate reaches 9/15, skip building and exit as DEPLOY_PROTOTYPE_EMPTY (step 9).

    Record the chosen signal — its source file(s) and one-line rationale — you'll use it in steps 6 and 7.

  3. Commit to a shape before writing code. Before touching .pending-deploy/, write out (in your reasoning, not a file):

    • Slug: aeon-prototype-<descriptor>, all lowercase, [a-z0-9-], 3–50 chars after prefix (e.g. aeon-prototype-market-heatmap). If ${var} supplied a typed slug, use it; otherwise derive one.
    • Tagline (≤90 chars) — the one-liner that appears in the page title and OG tags.
    • Primary action — what is the one thing a visitor does in the first 10 seconds? (read a number, click a filter, submit an input, compare two things). If you can't name it, go back to step 2.
    • Shape: static HTML+JS / static + api/ function / Next.js. Default to static single-file HTML unless the idea genuinely needs a serverless function.
  4. Write the files.

    rm -rf .pending-deploy        # clear stale state from prior runs
    mkdir -p .pending-deploy/files
    

    Write all project files into .pending-deploy/files/. This directory is the repo root — everything here is pushed to GitHub and deployed to Vercel.

    Quality bar — every prototype must meet these:

    • Self-contained — no external build step where avoidable. Prefer one index.html with inline <style> and <script>; fall back to a main.css / main.js only when size justifies it.
    • Loads in <1s on a cold visit. No jQuery, no CDN UI libraries for a single-page tool. Vanilla JS or a ~10KB util max. No <link rel="stylesheet"> to a CDN font unless it's one font.
    • Mobile-first, works on a phone. Viewport meta set, tap targets ≥40px, no horizontal scroll at 360px wide.
    • Share-friendly. Include <title>, <meta name="description">, <meta property="og:title">, <meta property="og:description">, <meta property="og:type" content="website">. Skip OG image unless you generate one.
    • Real content, not lorem. If the prototype shows data, fetch it from a public no-auth endpoint at load time (CoinGecko, GitHub public API, public RSS, public JSON feeds) — or hardcode a recent, realistic snapshot with the timestamp visible. Never ship placeholder [example data].
    • One visible CTA or primary surface. Clear hierarchy: what does the visitor look at first?
    • Works with JS disabled to at least show the tagline (progressive enhancement — not required for interactive tools, but the title and description must render server-free).
    • Light + dark via prefers-color-scheme — 4 CSS vars is enough.
    • No secrets. No API keys, tokens, or env vars embedded anywhere. If the idea requires auth, redesign around a public endpoint or drop the idea.
    • Include a README.md in .pending-deploy/files/ with: what it is (1 line), how to run locally (1 line), signal source (1 line link to the article/log/topic from step 2).

Read the full file on GitHub · 215 lines

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. 2d ago First seen · 215 lines · 20 tokens per session scan C 8bb7f04ace3e

Subscribe to this mod's changes

deploy-prototype is a skill published in the GitHub repository aeonfun/aeon (706 stars, last pushed 2d ago), licensed MIT. It adds 20 tokens to every session and 3,789 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 2 findings (recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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