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Coding & Development · TASK TOOLKIT

Build a small CSV import acceptance pack

Turn an import specification into a set of CSV fixtures with expected outcomes. Cover the formatting and data cases relevant to the contract, including quoted fields, identifiers, and rejected rows. Use the pack to expose ambiguous requirements before changing the importer or accepting implementation code.

For: Developers and product owners agreeing on the behavior of an existing CSV importer.

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YOUR STARTING MATERIAL

Supply the import contract, field definitions, duplicate policy, example files, current error output, and relevant importer code.

YOUR STARTING OPTIONS

Cursor · CodeRabbit · Replit

THE FINISHED DELIVERABLE

Named CSV fixtures, expected imported records and errors, an ambiguity register, and a repeatable acceptance run.

The situation

A customer success team imports account records from spreadsheets, but support reports inconsistent handling of duplicate identifiers and empty fields. The importer exists, so a rewrite would distract from the problem. Gather its documented contract and representative files, decide which behaviors are intentional, and create an acceptance pack. The pack should explain what gets imported, rejected, or reported for each case and make disagreement about expected behavior visible before development.

Build a small, reviewable version

  1. Agree on accepted input

    Document the delimiter, header names, required fields, encoding expectations, duplicate policy, and row rejection behavior from the existing contract. Ask the product owner to resolve gaps that affect outcomes. Keep an explicit unknown where a behavior remains undecided instead of letting generated code choose it.

    Check: Every fixture outcome can be justified by an agreed contract rule.

  2. Create independent small fixtures

    Build one compact file per relevant behavior, such as a quoted comma, an embedded line break, an empty required value, or a duplicate identifier. Include a valid control file. Name each fixture by its purpose and specify the exact expected records and error report.

    Check: Each fixture isolates one behavior and includes a concrete expected result.

  3. Run the existing importer

    Execute the current importer against the pack and compare actual records and errors with the expected outcomes. Record differences without immediately rewriting expectations to match implementation. Ask the coding assistant to trace confirmed mismatches, then use review to inspect any proposed change against the contract.

    Check: The result table distinguishes product ambiguity from a confirmed implementation mismatch.

  4. Preserve an acceptance run

    After approved corrections, rerun the complete small pack recording command and results. Include an explanation of how to add a new customer case. Keep the pack focused on contract boundaries rather than generating many redundant variations.

    Check: A teammate can rerun the pack and understand each failure's contract meaning.

Your acceptance checklist

  • Every fixture has exact expected records and a defined error outcome.
  • Quoted content and identifiers follow the agreed importer contract.
  • Undecided product behavior is visible instead of embedded silently in code.
  • The acceptance command produces a reviewable result table for the retained pack.

Where the process can go wrong

  • Changing expectations to match current output can conceal a real defect.
  • Combining several malformed cases makes the reason for failure unclear.
  • Generating dozens of redundant fixtures distracts from unresolved contract decisions.

Choose the workflow deliberately

Use Cursor or Replit as candidates and CodeRabbit as a review candidate where that fits your workflow. The comparison is whether the contract and fixture outcomes remain clear. Resolve product ambiguity before coding; test files cannot decide which duplicate or rejection behavior your users need.

A working brief to copy

Create a compact acceptance pack for [CSV IMPORTER] using [IMPORT CONTRACT] and [FIELD DEFINITIONS]. Propose a valid control plus individual fixtures for [RELEVANT INPUT BOUNDARIES]. For each, specify literal CSV content, expected imported records, and expected errors or rejection behavior. Flag any outcome the contract does not decide, especially [DUPLICATE POLICY] and [EMPTY FIELD POLICY]. Keep cases independent and explain the rule each tests. We will run the actual importer and use observed mismatches to guide focused corrections.

Tool context and original sources

This is an editorial task plan using the products’ published positioning, rather than a record of controlled product testing. The steps describe a trial for you to run. Confirm current access and terms, and review each tool’s limitations.

YOUR STARTING TOOLKIT

Meet the candidates.

Cursor

Work with AI assistance inside an editor built around your codebase.

Coding & Development

CodeRabbit

Bring AI review into pull requests and the process of assessing code changes.

Coding & Development

Replit

Describe an app and develop it in a workspace with building and publishing tools.

Coding & Development
A DIFFERENT TASK

Keep building.

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