How to Create an Agent That Writes Reports

An agent that writes reports can turn scattered data into a finished document on a schedule, freeing people from repetitive drafting. The hard part is not generating text but gathering the right inputs, structuring them, and producing output you can trust. This guide breaks the work into stages you can build and test one at a time.

Decide on the report's shape first

Before writing any logic, define the exact output you want. A weekly sales summary, a project status update, and a research brief each have different sections, tone, and length. Write a template that lists every section, what goes in it, and roughly how long it should be. Giving the agent a fixed skeleton dramatically improves consistency, because it fills sections rather than inventing a structure each time.

Decide who reads the report and what decisions they make from it. An executive summary needs headline numbers and a short narrative, while an analyst report needs detail and supporting tables. The audience determines what data you collect and how much explanation each figure needs.

Gather and validate the inputs

A report is only as good as its data. Connect the agent to the sources it needs, whether that is a database, an analytics tool, a spreadsheet, or a set of documents. Pull the raw numbers with deterministic code rather than asking the model to recall them, since models should reason about data, not be the source of truth for it.

Validate inputs before drafting. Check that expected fields are present, that date ranges match the reporting period, and that totals reconcile. If a data source is missing or returns something unexpected, the agent should flag it in the report rather than quietly filling the gap with a guess. A line such as "revenue data unavailable for this period" is far safer than a fabricated number.

Separate analysis from writing

Get better results by splitting the job into two passes. First, have the agent analyze the data and produce a structured set of findings: key metrics, notable changes, and supporting evidence. Then, in a second pass, have it turn those findings into prose that follows your template. This separation keeps the narrative grounded in the numbers and makes it easy to check that every claim traces back to real data.

When the agent makes a claim, have it cite the source. For a research report, that means linking to the document or page. For a metrics report, it means naming the dataset and period. Citations let readers verify conclusions and make the report defensible.

Format, review, and deliver

Decide on the final format: a document, an email, a slide deck, or a dashboard entry. Have the agent render the report into that format with consistent headings, tables, and styling. Keep visual design simple and readable rather than ornate.

Build a review step into the process. For high-stakes reports, route the draft to a person for a quick check before it goes out. For routine internal updates, automated checks may be enough, such as verifying that all required sections are filled and that totals add up. Over time, track which reports needed corrections so you can tighten the weak spots.

Schedule and maintain it

Once the agent produces good reports on demand, schedule it to run on a cadence that matches the reporting period. Monitor the first several automated runs closely. Data sources change schemas, definitions drift, and a metric that was reliable last quarter may break this one. Periodic maintenance keeps the reports accurate as the underlying systems evolve.