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Text prompts

Explore 400 text prompts for writing, research, planning, coding and everyday tasks. Choose a goal, customise the inputs and check the response against your sources.

400 prompts to explore

Text & chatSummariseBeginner

Summarise a document into key points

Turn meeting notes, an email or a report into a focused summary for a specific reader. Choose the length while keeping important facts, numbers and unanswered questions visible.

Use this prompt

What to provide

  • The source text you want summarised, such as meeting notes, an email or a report.
  • Who will read the summary and how short it should be.
  • A short description of the material, such as meeting notes or a project report.
Make it yours

Fill in what you know. Empty fields stay as placeholders.

Describe the source, for example meeting notes, an email or a report.

Name the reader and their relevant background.

Use a word limit, number of bullets or another clear format.

Paste the material to summarise. Remove confidential details you cannot share with your chosen AI service.

Optional instructions
1 input to replace

Example Illustrative example

Input

Fictional example Type of material: meeting notes Audience: the project team Length: five bullet points Source text: The internal pilot has moved from 12 November to 19 November because accessibility checks are still unfinished. The pilot is limited to 12 staff members. Lena will finish the checks by 16 November. Amir will update the onboarding guide by 17 November. The team will review pilot feedback on 23 November before deciding whether to invite customers. A customer rollout date has not been agreed.

Output

• The internal pilot moves from 12 November to 19 November because accessibility checks are unfinished. • The pilot is limited to 12 staff members. • Lena will finish the accessibility checks by 16 November. • Amir will update the onboarding guide by 17 November. • The team will review feedback on 23 November before deciding whether to invite customers; no customer rollout date is agreed.

Improve the result

  • Check each statement in the summary against the source. Identify any unsupported claims or missing qualifications.
  • List the decisions, named owners and deadlines stated in the source. Mark anything not stated as unknown.
  • Shorten the summary to three bullets while preserving the main decision, dates and unresolved questions.

Compare the result with the source before sharing it. AI summaries can omit context or misread numbers, dates and qualifications. Process long documents in manageable sections and check the combined summary for omissions. The example is fictional and illustrative; it is not a recorded model test.

Revision 1

Text & chatSummariseBeginner

Summarise a document in three bullets and one takeaway

Condense an update into three bullets and a final takeaway while keeping the decision, deadline or risk that matters most.

Use this prompt

What to provide

  • The complete text to condense, including dates, decisions and qualifications.
Make it yours

Fill in what you know. Empty fields stay as placeholders.

Paste the update or notes themselves, not just their title.

Optional instructions
1 input to replace

Example Illustrative example

Input

Illustrative editorial example — not a recorded model test. Fictional update: The staff pilot starts on 19 November with 12 participants. Accessibility checks must finish by 16 November. Customer access remains undecided until feedback is reviewed on 23 November.

Output

• The staff pilot starts on 19 November with 12 participants. • Accessibility checks must finish by 16 November. • Customer access remains undecided until the 23 November feedback review. Takeaway: Prepare for the staff pilot while keeping the customer launch decision open.

Improve the result

  • Compare all three bullets with the source and identify any omitted decision, deadline or risk.

A four-part overview can omit important context. Use the full document for decisions and check that the takeaway does not turn an unresolved issue into a commitment. This example is illustrative and has not been tested in a named AI model.

Revision 1.0

Text & chatExplainBeginner

Explain an unfamiliar topic in plain language

Get a beginner-friendly explanation with an everyday analogy, a concrete example and the limits of the comparison.

Use this prompt

What to provide

  • A specific topic or concept you want to understand.
Make it yours

Fill in what you know. Empty fields stay as placeholders.

Name a specific idea and add the part you find confusing.

Optional instructions
1 input to replace

Example Illustrative example

Input

Illustrative editorial example — not a recorded model test. Topic: keeping a copy of a frequently used file nearby to avoid downloading it repeatedly.

Output

Think of keeping a printed timetable on your desk instead of visiting the noticeboard each time. A saved copy can make the next lookup quicker. The catch is freshness: if the timetable changes, your desk copy may be out of date. Unlike a printed copy, software can sometimes check or replace its saved copy automatically.

Improve the result

  • Replace the analogy with a short explanation of the actual mechanism, keeping the language simple.

An analogy deliberately leaves out detail. Do not treat every feature of the comparison as a property of the real system. This example is illustrative and has not been tested in a named AI model.

Revision 1.0

Text & chatExplainBeginner

Explain a technical concept for an experienced reader

Specify your existing knowledge to focus an explanation on mechanisms, design choices, limitations and a realistic example.

Use this prompt

What to provide

  • The technical topic and your relevant experience.
  • Any version, implementation or source material that limits the question.
Make it yours

Fill in what you know. Empty fields stay as placeholders.

Name the mechanism, system or design choice.

Describe what you already know.

Optional instructions
2 inputs to replace

Example Illustrative example

Input

Illustrative editorial example — not a recorded model test. Topic: memoising a pure function. Background: comfortable with functions, maps and basic performance analysis.

Output

Memoisation stores a function result under a key representing its arguments. A repeated call can return the stored result instead of recomputing it. For a pure function square(n), storing square(8) = 64 is valid while its definition remains unchanged. Key construction and memory use have costs; mutable inputs or hidden dependencies can make cached results incorrect.

Improve the result

  • Identify the assumptions in this explanation and describe one case where the design would fail.

The model may assume an implementation you did not specify. Verify version-specific behaviour against the implementation or its official documentation. This example is illustrative and has not been tested in a named AI model.

Revision 1.0

Text & chatPlanBeginner

Turn a task into a step-by-step guide

Request prerequisites, numbered actions, expected results and verification steps for a clearly defined task and environment.

Use this prompt

What to provide

  • The task, environment and relevant version.
  • Current official instructions when the task depends on software behaviour and your chosen AI cannot browse.
Make it yours

Fill in what you know. Empty fields stay as placeholders.

Describe the desired end state.

Include the tool, device or working setup and any relevant version.

Optional instructions
2 inputs to replace

Example Illustrative example

Input

Illustrative editorial example — not a recorded model test. Task: sort a paper archive alphabetically by surname. Environment/version: a desk, paper folders and A–Z dividers; use first name to break ties.

Output

Prerequisites: enough desk space, A–Z dividers and a readable name on each folder. 1. Separate folders with missing names for review; expected result: every remaining folder has a sort key. 2. Group by surname initial, then sort each group by surname and first name. 3. Insert the groups behind their dividers. Verification: scan neighbouring names for alphabetical order and check that every folder is accounted for.

Improve the result

  • For each step, add a visible success check and explain what to do if that check fails.

A prompt does not give the AI browsing access. If it cannot check current documentation, supply the relevant official instructions and have it identify unverified steps before you act. This example is illustrative and has not been tested in a named AI model.

Revision 1.0

Text & chatExplainBeginner

Explain a concept using three everyday analogies

Compare three analogies for your audience, map them to the concept and identify where each comparison breaks down.

Use this prompt

What to provide

  • A concept and a short description of the intended audience.
Make it yours

Fill in what you know. Empty fields stay as placeholders.

Specify the mechanism the analogy must preserve.

Describe their familiarity and interests.

Optional instructions
2 inputs to replace

Example Illustrative example

Input

Illustrative editorial example — not a recorded model test. Concept: first-in, first-out ordering. Audience: new office staff.

Output

1. A single checkout line: the next waiting person is served first; priority lanes would break the comparison. 2. A numbered ticket desk: lower waiting numbers are called first; skipped or recalled tickets need extra rules. 3. Letters placed at the back of an in-tray and taken from the front: arrival order determines processing order; urgent letters handled separately would change it. The checkout line is the clearest starting point because its ordering is easy to see.

Improve the result

  • Choose the clearest analogy and rewrite it without implying that all real systems follow its simplifying assumptions.

Analogies can introduce false expectations. Check the mapping and exceptions rather than choosing only the most memorable story. This example is illustrative and has not been tested in a named AI model.

Revision 1.0

Text & chatExplainBeginner

Create a glossary with definitions and examples

Turn a topic or source document into a glossary ordered from foundational terms to more advanced concepts.

Use this prompt

What to provide

  • A source document or topic, plus any terminology specific to your organisation.
Make it yours

Fill in what you know. Empty fields stay as placeholders.

Paste the source or name a narrowly defined topic.

Optional instructions
1 input to replace

Example Illustrative example

Input

Illustrative editorial example — not a recorded model test. Source material: Our table has a header row with Name and Hours. Each record describes one volunteer, and each field holds one value.

Output

Header: a label identifying a column, such as Hours. Do not confuse the label with a value such as 3. Field: one value within a record, such as a volunteer’s hours. Do not confuse one field with the whole record. Record: the related values describing one volunteer, such as Ana and 3 hours. Do not confuse a record with a column shared across many volunteers.

Improve the result

  • Mark which definitions come directly from my source and which require an external reference.

The same word can mean different things in different domains. Confirm local definitions and do not assume the glossary is exhaustive. This example is illustrative and has not been tested in a named AI model.

Revision 1.0

Text & chatAnalyseBeginner

Map relationships between concepts

Make dependencies, overlaps and differences easier to inspect with a compact concept map and explanations of each connection.

Use this prompt

What to provide

  • The concepts, their context and any confirmed relationships.
Make it yours

Fill in what you know. Empty fields stay as placeholders.

List the ideas and any relationships you already know.

Optional instructions
1 input to replace

Example Illustrative example

Input

Illustrative editorial example — not a recorded model test. For our fictional newsletter workflow: a draft is reviewed by an editor, an approved draft can be published, and an unapproved draft returns for revision.

Output

Draft → Editorial review → Approved draft → Publication Editorial review → Revision → Editorial review The arrows represent this team’s workflow, not proof of causation. Publication depends on approval in the supplied process; the review outcome determines which path follows.

Improve the result

  • Label every connection and separate confirmed relationships from assumptions.

A generated connection may be speculative. Mermaid output is text unless your viewer can render it, and the diagram syntax may need correction. This example is illustrative and has not been tested in a named AI model.

Revision 1.0

Text & chatCompareBeginner

Compare two concepts and their practical differences

Separate two easily confused ideas by comparing their meanings, overlap, differences and appropriate uses.

Use this prompt

What to provide

  • Two concepts and enough context to select their intended meanings.
Make it yours

Fill in what you know. Empty fields stay as placeholders.

Name the first idea and its context.

Name the second idea in the same context.

Optional instructions
2 inputs to replace

Example Illustrative example

Input

Illustrative editorial example — not a recorded model test. Concept A: a project goal. Concept B: a project task.

Output

A goal describes an outcome you want, such as making the onboarding guide easier to find. A task describes work you perform, such as adding a link from the staff homepage. Both guide activity, but completing the task does not by itself prove the goal was achieved. Use the goal to assess the outcome and tasks to organise the work.

Improve the result

  • Give one borderline example and explain why it fits one concept better than the other.

Some concepts overlap or use different definitions across fields. A neat comparison table may exaggerate differences that are matters of degree. This example is illustrative and has not been tested in a named AI model.

Revision 1.0

Text & chatExplainBeginner

Learn a concept through a worked example

Connect an idea to a concrete scenario, with explicit assumptions, visible calculation or implementation steps and a practice problem.

Use this prompt

What to provide

  • A concept and scenario with the values needed to work through it.
Make it yours

Fill in what you know. Empty fields stay as placeholders.

Name the rule or mechanism you want demonstrated.

Supply realistic values or constraints.

Optional instructions
2 inputs to replace

Example Illustrative example

Input

Illustrative editorial example — not a recorded model test. Concept: total cost from quantity, unit price and a fixed fee. Scenario: four notebooks at 3.50 each plus a fixed delivery fee of 2; no other charges.

Output

Assumption: the delivery fee applies once and there are no other charges. Item cost = 4 × 3.50 = 14. Total = 14 + 2 = 16. The fixed fee is added once, after multiplying the unit price by quantity. Practice: What is the total for six notebooks at 3.50 each with the same delivery fee?

Improve the result

  • Check each intermediate step and then give the answer to the practice problem with the same assumptions.

An apparently plausible worked example can contain arithmetic or implementation errors. Check calculations independently and run code in an appropriate test environment. This example is illustrative and has not been tested in a named AI model.

Revision 1.0

Text & chatExplainBeginner

Identify and correct common misconceptions

Explore misleading beliefs about a topic, why they are inaccurate and a clearer interpretation for your audience.

Use this prompt

What to provide

  • The topic, intended audience and any suspected misconceptions you want examined.
Make it yours

Fill in what you know. Empty fields stay as placeholders.

Name the subject and context.

Describe the reader’s knowledge level.

Optional instructions
2 inputs to replace

Example Illustrative example

Input

Illustrative editorial example — not a recorded model test. Topic: arithmetic averages. Audience: learners new to statistics.

Output

Misconception: the mean must be one of the observed values. For 2 and 4, the mean is 3, which is not in the list. Misconception: the mean alone describes a whole dataset. The lists 0, 10 and 5, 5 both have mean 5 but different spread. These examples correct possible misunderstandings; they do not establish how common those beliefs are.

Improve the result

  • Distinguish misconceptions supported by evidence from hypothetical misunderstandings, and supply verifiable sources where needed.

The model may invent claims and call them common. Check both the correction and any assertion about how widespread a belief is. This example is illustrative and has not been tested in a named AI model.

Revision 1.0

Text & chatExplainBeginner

Explain a document without losing its qualifications

Identify a document’s purpose, terms, dates and ambiguities while keeping explicit statements separate from interpretation.

Use this prompt

What to provide

  • The complete relevant document, including definitions, exceptions and referenced sections.
Make it yours

Fill in what you know. Empty fields stay as placeholders.

For example, a project brief, policy or specification.

Paste the text, or describe a file you will actually attach to your chosen AI tool.

Optional instructions
2 inputs to replace

Example Illustrative example

Input

Illustrative editorial example — not a recorded model test. Fictional project note: Draft artwork is due on 6 May. Printing can start after written approval. The note does not name the approver or set an approval deadline.

Output

Purpose: set the next steps for artwork and printing. Explicit statements: draft artwork is due on 6 May; printing depends on written approval. Ambiguities: the approver and approval deadline are not specified. Interpretation: the print schedule may depend on how quickly approval is obtained; the note does not establish a print start date.

Improve the result

  • For each obligation or date, quote the supporting passage and list anything the document leaves unspecified.

A summary cannot resolve an ambiguous document or determine obligations conclusively. Verify important interpretations against the full source and appropriate expertise. This example is illustrative and has not been tested in a named AI model.

Revision 1.0

Give the prompt a useful brief

A text prompt is most useful when it names the task, supplies the source material and describes the result you need. Replace the square-bracket inputs with your own details before copying it into your tool.

Make a summary easier to check

For a meeting summary, provide the notes and ask for decisions, action owners and unresolved questions in separate sections. Tell the tool to mark missing owners as unknown. Compare the result with the original notes before sharing it.

Refine one thing at a time

If an answer is too broad, specify the audience or ask for a shorter format. If it adds facts that are absent from your source, ask it to use only the supplied material and identify gaps. Keep sensitive information out of examples unless you have permission to use it.

Questions about text prompts

Supply the information named by each input, such as the text to summarise, your audience or the required format. The preview updates as you fill in the fields. Unfilled brackets remain visible so you can spot missing context.

Yes, but check the instructions and examples first. Change the goal, source material and output format together, then review the response. A prompt tested for one task does not guarantee the same result elsewhere.