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Shopping Lab, nine agents one after another

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Shopping Lab helps a shopper choose a product. It clarifies the need, reads the pages of two online stores, compares the offers, scores them and writes a report with the best picks. It is a Sequential team: nine agents work one after another.

ElementWhat it is
The team Shopping LabA Sequential team of nine members.
Nine agentsOne per step of the work.
Five data tablesWhere the agents keep and pass their results.

The team Shopping Lab in its editor: nine hexagons in a row, one per member, gathered in four tinted groups (Intake, Stores, Analysis and Report), and the pill Sequential beside the name

#MemberWhat it does
1Needs AnalystTurns a vague wish into a precise brief: product, budget, must-haves. It is the only member that asks the shopper questions.
2Query PlannerPrepares the search for each store from the brief.
3Quill ScoutReads the pages of the first store and reports prices, ratings, reviews and specifications.
4Staples ScoutDoes the same for the second store.
5Product MatcherMerges the same product found in both stores, and checks the must-haves.
6Spec NormalizerBuilds a side-by-side comparison in the same units. It never fills a gap with a guess.
7Customer Reviews AnalystSays what customers think, from the reviews collected.
8Scoring AnalystScores every product with a script, never by estimation.
9Report WriterWrites the final report: verdict, top picks, charts, comparison, sources. It sends the report without asking anything.
  • One job per agent. Each role is one sentence. Read the roles in the team, then open two or three agents and read their instructions.
  • Only one member asks questions. The Needs Analyst asks the shopper at the start. The Report Writer shows the report at the end, without asking anything. The seven others work only from what is in the tables.
  • The tables carry the work. In a Sequential team, each member receives what the previous one produced. Here the agents also write their results in tables, and the next ones read them. Open Resources > Data Tables to see the five tables.
  • A script for the scores. The Scoring Analyst has a tool that runs a small program. The same inputs always give the same score. This is how to get a result that does not vary from an AI team.
  • Groups. The members are sorted in four groups: Intake, Stores, Analysis and Report. See Name, group and give an icon to team members.
  • Reading web pages. The two scouts have the tool AI Agent Web Scraper Tool (Direct), which reads a page without a paid service.
  1. Open Studio > Agents and open the team Shopping Lab.
  2. In the switch at the top, select Execution.
  3. Ask for a product, with a budget. The Needs Analyst asks you questions first.

See Run a team and read its work.

An execution uses the AI model many times: nine agents work, and several of them make several calls.

  • To compare other stores, copy a scout and change its instructions. Check first that the terms of use of the store allow its pages to be read this way.
  • To compare something other than products, keep the shape: clarify, collect, match, compare, score, report.
  • The stores are real websites. Their pages can change, and a scout can then find nothing.
  • The showcase is written for stores in the United States, and it works in English.

Trip Manager Team.