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Reader's Advisory Picks · Community, Faith & Civic

Personal reading picks from your own shelves, for every patron

A patron tells you what they loved, and AI suggests up to 5 titles you actually own, each with a reason, call number and branch. A librarian approves every list.

Available now $89 one-time · never renewsIncluded in Enterprise
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Free account to start. Buying and running live need a paid plan.

  • Starts when your form or app sends it something
  • 3 AI steps
  • A person approves before it acts
  • About 20 min to set up

Sound familiar?

The job, before and after this agent.

What it feels like today

  • “Patrons love personal recommendations, but each list takes us ages.”
  • “Online suggestions point to books we don't even have.”
  • “Our “what should I read next?” form gets answered weeks late.”

What you get with the agent

  • Plans searches of the free Open Library catalog from the books the patron loved, their mood, format and age band.
  • Shortlists candidates and checks each one against your catalog export.
  • Picks up to 5 titles you own, each with a “why you'll like it” line, call number, format and branch.
  • A librarian approves every list before it's emailed, with replies to your readers' advisory inbox.

Before

A patron's form asks for “cozy mysteries like Louise Penny”. It sits in a queue until a librarian has a free hour to search the catalog.

After

The librarian opens a draft of five titles on your shelves, each with a reason and call number, tweaks one line and sends it the same day.

How it works

The whole workflow, step by step.

When a patron fills in your readers' advisory form, AI plans 1–3 searches of the free Open Library catalogue from the books they loved, their mood, format and age band, shortlists up to 12 candidates and looks each one up in your catalogue export sheet in Google Sheets. It then picks up to 5 titles you own, each with a “why you'll like it” line, the call number, format and branch. A librarian approves every list before it's emailed. It suggests only titles in your catalogue export (refresh it monthly), doesn't place holds, and for children and teens uses the age band only.

  1. Trigger“What should I read next?” form
  2. AI stepPlan the search
  3. LogicEach search
  4. App callSearch Open Library
  5. AI stepShortlist the candidates
  6. LogicEach candidate
  7. App callFind it in your catalogue
  8. AI stepPick 5 titles you own
  9. Human approvalLibrarian approves the list
    • Approved:Email the patron
    • Rejected:Not sent
  10. OutputNot sent
  11. OutputEmail the patron
  12. OutputList sent

This is the workflow that opens in your workspace when you set the agent up. Every step can be edited.

  1. Step 1“What should I read next?” formStarts when your readers' advisory form posts a request: books they loved, mood, format, age band and anything to avoid.
  2. Step 2Plan the searchAI reads what the patron loved and wants, and picks 1–3 short Open Library searches (subjects, authors, themes).
  3. Step 3Each searchRuns each planned search on Open Library (at most 3).
  4. Step 4Search Open LibrarySearches the free Open Library catalogue (no key) and returns up to 10 works per search: title, author, first published year and subjects.
  5. Step 5Shortlist the candidatesAI removes duplicates, books the patron already read and anything to avoid, and keeps up to 12 candidates to look up in your catalogue.
  6. Step 6Each candidateLooks every candidate up in your catalogue export (up to 12).
  7. Step 7Find it in your catalogueLooks the title up in your catalogue export sheet (case-insensitive match on the title column) to get the call number, format and branch.
  8. Step 8Pick 5 titles you ownAI picks up to 5 titles found in your catalogue, writes a “why you'll like it” line for each with the call number, and drafts the email.
  9. Step 9Librarian approves the listA librarian checks the picks (owned, right age, right format) and the email in Reviews, edits anything and approves; nothing is sent before that.
  10. Step 10Not sentNothing was sent; the run history keeps the list.
  11. Step 11Email the patronSends the approved reading list to the patron, with replies going to your readers' advisory inbox.
  12. Step 12List sentThe run history keeps the picks and the email.

Example run

What goes in, and what comes out.

Example with fictional data

Comes in

Request (fictional): loved “The Thursday Murder Club”, wants something cozy and funny, print, adult.

The agent produces

Five titles found in your catalog export, each with a one-line reason, call number, format and branch. Waiting for a librarian to approve before emailing.

What you need

Everything it takes to run it.

About 20 minutes from purchase to live. A checklist above the canvas takes you through each step.

Plan

Included in Enterprise; on other paid plans it's $89 once. Agents run live on paid plans, from Basic ($39/mo).

Your AI key

Connect any of 14 AI providers on your own key. Your provider bills usage directly, at cost; we add no markup.

Apps

Checklist

  • A paid plan (agents run live on paid plans).
  • An AI provider key (Settings → AI Providers).
  • Google Sheets, connected in Settings → Integrations, plus an HTTP / Custom API connection to https://openlibrary.org (free, no key).
  • A catalogue export sheet of the titles you own (refresh it monthly), and a form that can post JSON to a webhook.

Setup, about 20 minutes

  1. Connect your AI provider. The AI steps run on your own key (OpenAI, Anthropic, Google and more). Add one in Settings → AI Providers.
  2. Connect Open Library (HTTP / Custom API). In Settings → Integrations, add an HTTP / Custom API connection named “Open Library” with base URL https://openlibrary.org and Authentication “None”. Open Library's search is free and needs no key; the agent makes at most 3 searches per request.
  3. Connect Google Sheets. Connect the Google account that can open your catalogue export (Settings → Integrations → Google Sheets).
  4. Pick the Open Library connection. Open “Search Open Library” and pick the connection.
  5. Pick your catalogue export. Open “Find it in your catalogue” and pick your account, spreadsheet, tab and the title column.
  6. Describe your library. Open “Pick 5 titles you own” and replace the placeholder with your holds instructions, formats and sign-off.
  7. Add your readers' advisory inbox. Open “Email the patron” and enter the Reply-to address.
  8. Test it with Dry Run. Press Dry Run: the agent runs on sample data with no messages sent and nothing written to your apps.
  9. Switch the trigger on. Open the trigger, switch the webhook on and copy its URL and secret into your readers' advisory form.

Is it a fit?

Who it's for, and what it won't do.

Built for

  • Public library readers' advisory staff
  • Adult services and teen librarians
  • School and community libraries

What it doesn't do

  • It suggests only titles found in your catalogue export, matched by title, so it can miss editions with different titles.
  • It doesn't place holds or check availability (ILS systems aren't connectors).
  • For children and teens it uses the age band only: no names or other details.
  • Nothing is sent before a librarian approves the list.

We list the limits up front so you can decide before you buy.

Price

$89 one-time

Per workspace. It never renews.

Available now
  • Included at no extra cost on Enterprise.
  • Buying and running it live need a paid plan, from Basic ($39/mo).
  • Dry Run costs nothing: simulated AI and app calls, nothing sent.
  • AI usage is billed by your own provider, at cost. No AI credits to buy from us.
Get this agent See how it works

One-time agent purchases aren't covered by the 30-day money-back guarantee. Refund policy

FAQ

Questions about Reader's Advisory Picks.

Will it recommend books we don't have?

No. It only suggests titles found in your catalog export, matched by title, so it can miss editions with different titles. A librarian approves every list.

What about children and teens?

For younger readers it uses the age band only, with no names or other details.

Does it place holds?

No. ILS systems aren't connectors. The email tells the patron how to place a hold your usual way. Setup takes about 20 minutes.

Is it worth paying for?

It's a one-time purchase that never renews, set against building every list by hand. You need a paid plan and your own AI key; Dry Run is free.

What should the form send?

A JSON POST with patron_name, email, loved_books, mood, format, age_band (e.g. Adult, Teen, Children), avoid and notes. Your form or site posts it with the webhook's signature header.

What catalogue export do I need?

A Google Sheet with one row per title you own: Title (the main title, without subtitle), Author, Call number, Format and Branch. Most ILS report tools can export this; refresh it monthly. Lookups match the title exactly (ignoring case), so titles with long subtitles may be missed.

Is this a subscription?

No. Reader's Advisory Picks is a one-time purchase of $89 per workspace and never renews. The Enterprise plan includes it at no extra cost. Running it live needs a paid plan (from Basic ($39/mo)), and your AI provider bills you directly for usage.

Can I test it before it touches real data?

Yes. Once it's set up in your workspace, Dry Run plays every step on sample data with simulated AI and app calls: nothing is sent and nothing in your apps changes. Switch the trigger on only when you're happy.

Put Reader's Advisory Picks to work.

Free account, no credit card. Your Agents page opens with Reader's Advisory Picks ready to buy and set up, then Dry Run it before it goes live.

Get this agent See how it works