Original explainer
Read official prompt samples: models, context and acceptance criteria
Use Google’s document Q&A and Go commit-message samples to separate task, input, model and parameters, then keep your own review record instead of treating a displayed answer as a general guarantee.
Official prompt libraries show how an input is organized and how an answer is presented. Before adapting one, check the task, material and execution conditions, then define how to evaluate the result. This explainer combines official descriptions with editorial checking suggestions. No model call, sample execution or complete-plan review was performed.
Check three layers before adapting a sample
Task and material
Identify the question, files and code supplied by the sample. Context is part of the input.[2][3]
Model and parameters
Record the displayed model and parameters, then compare them with the interface you will use.[2][3]
Display and review
The library shows an answer to one sample. Your own input needs an independent review.[1]
Start with a matching task type
Google organizes prompt samples by question answering, classification, code, extraction, summarization, transformation and generation. Find a sample for the intended outcome, then check whether its input resembles yours.[1]
The document Q&A sample asks a specific date question over an attached file. The Go commit-message sample combines system instructions, a code diff and a request. They illustrate different input structures.[2][3]
Separate task, material and execution conditions
| Check | Document Q&A sample | Go commit-message sample |
|---|---|---|
| Task | Answer a specific question over the document | Describe the supplied Go code changes |
| Material | Attachment and question | System instructions, code diff and request |
| Execution record | Displays model and sampling parameters | Displays model and sampling parameters |
| Review focus | Check the answer against the attachment | Check the description against the actual diff |
Editorial suggestion: store these items separately. Missing material, changed versions and a different execution interface should be explicit in your record.
Treat the displayed answer as a sample to review
Both pages display a prompt, response and model parameters. The answer helps illustrate an expected format; it does not prove correctness for other documents, code versions, models or languages.[2][3]
- Trace numbers, dates and citations back to the original input.
- A change description should cover the actual diff without inventing features.
- Save a separate result when changing the model, parameters or system instructions.
These are editorial suggestions. This site did not reproduce the displayed answers or evaluate model accuracy.
Write your own review record
Editorial suggestion: define the problem first and prepare material you have rights to use and can handle appropriately. Use the sample as a structural reference while defining acceptance criteria for your own content.
- Task: summarize, extract fields, answer a question or explain code?
- Input: preserve material version, filename and necessary context.
- Conditions: record the actual model, interface, system instructions and visible parameters; write “unknown” for unavailable items.
- Output: save the answer and mark what passed, failed or cannot yet be judged.
- Review: connect each key conclusion to its original passage or diff.
Record an executed test as passed only after reviewing the result. Keep incomplete inputs pending and add missing material when needed.
Confirm access and usage conditions before execution
The prompt library can be read directly. Trying samples in the Cloud console requires the relevant Google Cloud account, and the pages also describe an API path. Reading a page and executing a model request are separate operations.[1][2][3]
- Check the project, model, region and permissions for your current account.
- Review the selected product’s current pricing and quota; this article does not certify free calls or a task budget.
- Check upload and output rights. Public sample content does not authorize your own third-party material.
The documentation navigation says Vertex AI has become part of Gemini Enterprise Agent Platform. Names and parameters in an existing sample describe that sample; equal entitlements across newer interfaces, plans and versions are not inferred.[1]
Article sources
Original editorial content; official descriptions and checking suggestions are distinguished.