Report card

Do AI agents pick Render?

How often agents choose Render when a developer needs hosting & deploy — measured across Claude, GPT, Gemini.

Render

#3 of 6 hosting
10%Pick Rate
95% CI 7%14%

When developers ask an AI agent for hosting, Render is picked 10% of the time — ranking #3 of 6 measured across Claude, GPT, Gemini.

Picked 10% Named, not picked 39% Never surfaced 51%

Beaten by Vercel (24%), Cloudflare Pages (12%).

Awareness

464 package downloads / week

Thin presence in the data models learn from — an awareness problem. Get into more code, docs, and developer discussion.

0 docs in FineWeb (10BT sample) · 286 URLs in Common Crawl

In the raw web crawl, but thin in the filtered corpus models actually train on — an awareness gap at the source.

Agent readiness

Level 4 · Agent-Integrated · 9/16 agent standards

Render is missing DNS-AID records, OAuth discovery, Protected resource metadata, auth.md. Readiness is what a site publishes for agents, not whether agents pick it — across our corpus the two barely correlate. Scored by Cloudflare's Agent Readiness score.

AdoptionDid the pick convert to installs? Public Adoption = npm downloads of your packages. The proof half of the funnel.

1K installs / month ▲ 13% MoM

Growing despite a low Pick Rate — winning the agent pick is upside, not a dependency.

Get the full report

The per-model and per-surface breakdown for Render — where it wins, where it loses, and to whom — plus an alert when the Pick Rate moves.

About Render

A command-line tool for rendering templates from Jade, Handlebars, Swig, and other engines into HTML or text files.

Render is a CLI utility that takes template files and optional JSON or YAML context data and produces rendered output. It supports one-to-one rendering (a single template to a single file) and one-to-many rendering (iterating over an array or object to produce multiple output files from one template). It's aimed at developers building static sites, generating config files, or populating code skeletons without needing a separate command-line tool for each templating language.

Where to start

Install the package globally via npm, then run the `render` command with a template file and optionally pass context data using `--context` to supply JSON or YAML variables. Redirect stdout or use `--output` with path placeholders to control where files are written.

Install

Links and summary verified from public sources.

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Render — do AI agents pick it? · Pickrate