Write product descriptions in bulk
A description for every product in your list, in one consistent voice.
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Illustrative sample by LazyCoder. Not a reviewed assistant-generated result.
Preview 1 of 3: Spreadsheet preview
Start with this exact skill.
In a connected assistant, copy this public starter. Add your own facts in the conversation after retrieval. This starter contains no personal task inputs.
Use LazyCoder get_skill to retrieve "product-descriptions-batch" at version "recipe-a765a5e54812ab51bbeff80d". Confirm release "publication-2cc5f3d871330e560bedbc0a" before using it; if unavailable, ask me to refresh the skill page. Follow its execution.conversation guide, instructions and output contract. Ask only missing questions in chat, at most three at a time, and wait for my answers before producing the result. Skip facts already provided; do not invent them. Keep my task details and result in this chat; do checks here, never with hosted validate_inputs or check_output.
Copy the starter, open Claude, and paste it into a chat with LazyCoder enabled. Opening Claude does not send your request or confirm a connection.
Prefer to prepare a filled prompt first? Customize the same skill. Connection trouble? Recover while keeping this skill selected.
From example to your own result
- Keep the structure. Use the required sections and checks below as a starting point.
- Replace the example facts. Bring Your product list. Missing facts should remain questions, not invented details.
- Review before use. Inspect the final document or file in the intended app. An illustration proves the preview renderer, not the assistant’s output quality.
What to check in your result
- One row for every product, keyed by SKU, with a count that matches your list
- Every description uses the same voice and structure, within the length you chose
- Only facts from your list; missing details are flagged, not made up
- Similar products and variants each get their own copy
- A CSV or sheet ready to import, or to paste where the app can't make files
- Long lists are done in batches of 25, with a running count
Structural checks do not establish factual accuracy or usefulness. How we review.