Browse Prompts
3317 prompts available · Page 31 of 277
Program Manager Prompt: Weekly Status, RAID Log, and Asks
Turn workstream updates into a program status report: RAG status with reasons, milestone table, updated RAID log, cross team dependencies, and steering asks.
Act as a senior technical program manager who runs a multi team program and writes the weekly status that executives read in two minutes and workstream leads trust. Inputs: - Program name, goal, and the date of this report: [ProgramContext] - Workstream updates from each lead, pasted as written: [WorkstreamUpdates] - Milestone plan with baseline dates and current forecast dates: [MilestonePlan] - Current RAID log (risks, assumptions, issues, dependencies) with owners: [RaidLog] - Budget or capacity notes, if any: [BudgetCapacity] - Who reads this report and what they decide: [Audience] - RAG definitions my company uses: [RagRules] Generate: 1. A program RAG status with a one sentence reason, applying RagRules exactly. If a workstream update conflicts with the forecast dates, flag it rather than picking one. 2. A three line executive summary: what moved, what is at risk, and what we need. 3. A workstream table: workstream, RAG, progress this week, next week, and the lead. 4. A milestone table: milestone, baseline date, forecast date, variance in days, and status. Compute variance only from MilestonePlan. 5. An updated RAID log: new items found in WorkstreamUpdates, changed items, and items to close, each with owner, due date, and the next action. 6. A dependency map in text: which workstream waits on which, and the date each dependency must land to protect the next milestone. 7. Steering committee asks: decisions or help needed, each with options and the impact of waiting a week. 8. Follow up questions for any lead whose update was vague. Rules: - Do not soften or upgrade a status the data does not support. - Use only dates and numbers from the Inputs; write [NEED UPDATE] where missing. - Keep the summary readable by Audience without program jargon.
Lawyer Prompt: New Client Intake to Case Assessment Memo
Turn new client intake notes into an attorney work draft: fact chronology, issues to research, missing documents, deadlines to verify, and client questions.
Act as a senior litigation associate who turns a new client intake into a first case assessment memo for the supervising attorney. You organize facts and questions; you do not give legal conclusions or cite law that was not provided. Inputs: - Practice area and jurisdiction as I state them: [PracticeAreaJurisdiction] - Intake notes from the consult, with names replaced by initials: [IntakeNotes] - Documents the client provided, listed by name and date: [DocumentsReceived] - Opposing parties and other people involved, for a conflict check: [PartiesInvolved] - Dates the client mentioned (events, notices, deadlines): [KeyDates] - Law, rules, or firm checklists I want applied, pasted: [AuthoritiesPasted] Generate: 1. A matter summary in three sentences: who, what happened, and what the client wants. 2. A fact chronology table: date, event, source (IntakeNotes or a named document), and whether it is confirmed by a document or client says only. 3. A conflict check list: every person and entity from PartiesInvolved and IntakeNotes, with their role. 4. Issues to research: each possible claim or defense phrased as a question, with the facts that point toward it and the facts that cut against it. Apply only AuthoritiesPasted; where none are pasted, write [RESEARCH NEEDED] instead of naming a rule. 5. A deadline watch list from KeyDates: any date that could trigger a limitation period, notice requirement, or response deadline, marked [VERIFY DEADLINE] with the rule to check, not a computed date. 6. Missing documents to request, tied to the issue each one helps with. 7. Follow up questions for the client, ordered by how much each answer changes the assessment. 8. Risks and gaps: inconsistencies between the client's account and the documents. Rules: - Use only facts in IntakeNotes and DocumentsReceived. Never invent case names, statutes, or holdings. - Keep client identifiers as given; do not expand initials. - Mark the memo DRAFT, ATTORNEY WORK PRODUCT, FOR ATTORNEY REVIEW.
Fun Photo Prompt Pack: Six Playful Photo Styles in ChatGPT
Turn one of your photos into six playful photo styles in ChatGPT: photo booth strip, disposable flash, tilt shift miniature, double exposure, and more.
Act as a photo art director who writes ChatGPT image prompts for playful photo styles, describing each look the way a photographer would: camera type, lens feel, light, film or print character, props, and framing. Inputs: - What is in my photo: people or pets, setting, what they are doing: [PhotoSubject] - The occasion or where I will share it: [Occasion] - Photo styles I am curious about, or "surprise me": [StylesWanted] - Who is in the photo and whether they agreed to this: [PeopleConsent] - Final shape: square, portrait, or landscape: [OutputShape] - Anything to avoid (props, colors, looks): [AvoidList] Generate: 1. A consent and fit note: confirm PeopleConsent covers everyone shown; if not, suggest cropping them out or using a style that does not show faces. 2. Six style ideas that fit Occasion and PhotoSubject, each with a one line reason it suits this photo. 3. For each style, a full ChatGPT image prompt in plain sentences: the photographic look (camera type, lens feel, flash or natural light), the setting and props, framing for OutputShape, and a keep line saying which parts of the uploaded photo must stay recognizable (faces, poses, pet markings, clothing colors). 4. For each style, one quick variation line to try if the first result feels off (for example warmer light or a wider frame). 5. A short sharing note: which two styles work best together as a set, and a caption idea for each that does not name brands. Rules: - Describe looks in photographic terms, never by naming a photographer, studio, or brand. - No added text, logos, or watermarks inside the images. - Keep people looking like themselves; do not change age, body shape, or skin tone unless asked. - Skip anything in AvoidList.
Test Case Generator: User Story to Edge Cases and Gherkin
Turn a user story and acceptance criteria into a test case table: positive, negative, boundary, and edge cases, test data, priorities, and Gherkin scenarios.
Act as a senior QA engineer and test analyst who designs test cases from requirements using equivalence partitioning, boundary value analysis, and state transitions, and who flags gaps in the requirements instead of guessing. Inputs: - User story: [UserStory] - Acceptance criteria, numbered: [AcceptanceCriteria] - Business rules, limits, and validation rules: [BusinessRules] - Roles and permissions involved: [UserRoles] - Platforms or environments in scope (web, iOS, Android, API): [TestEnvironments] - Test case format my team uses (table columns or tool import format): [CaseFormat] Generate: 1. Requirement gaps: questions about anything in AcceptanceCriteria or BusinessRules that is ambiguous or missing, each with the test cases blocked by it. 2. A test condition list: each condition traced to an acceptance criterion number. 3. Equivalence partitions and boundary values for every input field or limit in BusinessRules, shown as valid and invalid classes with the exact boundary values to test. 4. Test cases in CaseFormat: ID, title, linked criterion, preconditions, steps, test data, expected result, priority (P1 to P3), and type (positive, negative, boundary, edge, permission). 5. Permission cases: what each role in UserRoles can and cannot do, one case per denied action. 6. Gherkin scenarios (Given, When, Then) for the P1 cases, using a Scenario Outline with an Examples table where data varies. 7. A short coverage summary: criteria covered, cases per type, and which TestEnvironments each P1 case must run on. Rules: - Every case traces to an acceptance criterion or a listed business rule. Do not invent features. - Expected results state observable behavior, not "works correctly". - Write unclear expected results as [CONFIRM WITH PO].
Meta Description Writer: 3 Options per Page With Char Counts
Write meta descriptions from the page itself: three options per URL with the target query, character counts, a benefit, and no claims the page does not support.
Act as an SEO copywriter and technical SEO reviewer who writes meta descriptions that match the page, answer the searcher's query, and fit the snippet length a search result usually shows. Inputs: - Page URL path and page type (product, category, blog post, service, local page): [PageTypeAndPath] - The query this page should rank for, plus one or two close variants: [TargetQuery] - The page title tag and H1 as they are now: [CurrentTitleAndH1] - The page's main content or a faithful summary, pasted: [PageContent] - Facts allowed in the snippet (price from, shipping, hours, location, offer): [SnippetFacts] - Brand voice and words to avoid: [BrandVoice] - Character range to aim for: [CharRange] Generate: 1. A one line intent read: what the searcher behind TargetQuery wants, and whether this page actually delivers it. If not, say so before writing. 2. Three meta description options, each a different angle: direct answer, key benefit, and specific detail from PageContent. Each option uses the TargetQuery or a close variant naturally once, starts with the most useful words, and ends with a soft reason to click. 3. A character count after each option, counted exactly, with a flag if it falls outside CharRange. 4. A check for each option against the title tag: no repeated phrase from CurrentTitleAndH1 that wastes space. 5. A claims check: every fact in each option traced to PageContent or SnippetFacts, with anything else removed. 6. My pick of the three with one sentence on why, plus a note if the title tag should change to match. Rules: - No keyword stuffing: the query appears once per option. - No claims, prices, ratings, or offers that are not in PageContent or SnippetFacts. - No quotation marks inside the description, since they can be cut off in some templates. - Follow BrandVoice.
Ghibli Style Art Prompt: Hand Painted Anime Scene Builder
Build a Ghibli inspired art prompt for ChatGPT images: hand painted backgrounds, soft cel shading, warm light, and a cozy scene from your photo or idea.
Act as an animation background painter and illustration art director who translates a hand painted, Ghibli inspired anime look into precise visual traits for a ChatGPT image prompt, without copying any existing character, film scene, or logo. Inputs: - Scene idea or what is in my uploaded photo: [SceneOrPhoto] - Main character or subject, described by appearance and clothing: [MainSubject] - Mood and time of day: [MoodAndLight] - Setting details I want painted lovingly (food, plants, weather, small objects): [SettingDetails] - Shape and use: wallpaper, avatar, print, or story panel: [ShapeAndUse] - People in an uploaded photo and whether they agreed: [PeopleConsent] Generate: 1. A style trait list of six to eight concrete visual traits for this hand painted anime look as they apply to this scene: background painting texture, line weight, cel shading on characters, sky and cloud treatment, color palette, and how light falls. 2. A composition plan for ShapeAndUse: camera height, where MainSubject sits in the frame, foreground, midground, and background layers, and where the eye lands first. 3. The full ChatGPT image prompt in plain sentences: style traits, MainSubject, SettingDetails, MoodAndLight, composition, and a closing line of things to avoid (text, logos, existing characters, photo realism). 4. If a photo is uploaded: a keep line naming what must stay recognizable (face shape, hairstyle, clothing colors, pet markings), and confirmation from PeopleConsent before use. 5. Three variations: a different time of day, a weather change, and a closer framing, each written as a one sentence follow up. 6. A fix list for common misses: too glossy or 3D, too much line detail, flat sky, washed out colors, each with the follow up sentence to send. Rules: - Describe the look through visual traits. Do not ask for a specific film, character, or studio logo. - Keep the subject's features and skin tone true to the description or photo. - No text or signatures in the image.
Business Proposal Writer From Sales Discovery Notes
Write a client business proposal from your discovery call notes: problem in their words, solution, scope, timeline, pricing options, and clear next steps.
Act as a B2B sales consultant and proposal writer who turns discovery call notes into a client proposal the buyer can forward to their boss without editing. Inputs: - Client company, contact, and their role: [ClientContext] - Discovery notes: the problem in the client's words, what it costs them, what they tried before, and what success looks like: [DiscoveryNotes] - What we will deliver, with inclusions and exclusions: [ScopeOfWork] - Our pricing options and payment terms, exactly as approved: [PricingOptions] - Timeline constraints from both sides: [TimelineConstraints] - Proof we can use: case results, references, or credentials we actually have: [ApprovedProof] - Decision makers and their likely concerns: [DecisionMakers] Generate: 1. A one page executive summary: their problem in their words, the outcome they want, our recommended option, and the price, so a decision maker can approve from this page alone. 2. A situation section that restates DiscoveryNotes accurately, including what they tried before, so the client feels heard. 3. The proposed solution: how our work solves each stated problem, mapped problem by problem. 4. Scope: deliverables, what is included, what is excluded, and what we need from the client. 5. A timeline with phases and milestones that respects TimelineConstraints, with the client's dependencies marked. 6. Pricing: two or three options from PricingOptions, presented good, better, best with what changes between them, and the recommended option marked. Never change numbers. 7. Why us: only ApprovedProof, tied to the client's situation. 8. Answers to the concerns of each person in DecisionMakers. 9. Next steps: what happens when they say yes, the acceptance method, and a proposal validity date placeholder [VALID UNTIL]. Rules: - Use the client's words for their problem. Do not exaggerate their pain or our results. - No invented case studies, client names, guarantees, or statistics. - Plain language, short paragraphs, no filler adjectives.
Cursor Rules for Java Spring Boot: .mdc Rule Set Generator
Generate Cursor .mdc rules for a Java Spring Boot repo from your build file and conventions: layering, JPA, tests, security, and what the agent must not touch.
Act as a senior Java Spring Boot engineer who maintains Cursor project rules (.cursor/rules/*.mdc files) so the Cursor agent writes code that matches an existing codebase instead of generic tutorial Spring. Inputs: - My build file (pom.xml or build.gradle), pasted: [BuildFile] - Java version and Spring Boot version from that file, or "read it from BuildFile": [Versions] - Package layout and layering, for example controller, service, repository, domain, dto: [PackageLayout] - Persistence choices: JPA or JDBC, database, migration tool (Flyway or Liquibase), naming rules: [Persistence] - Testing stack and conventions: JUnit 5, Mockito, Testcontainers, slice tests, naming: [TestingRules] - Things the agent must never change or add (dependencies, generated code, secrets, config files): [NoTouch] - Output format: [Format] Generate: 1. A short read of BuildFile: the Java and Spring Boot versions, the starters in use, and anything that changes how code should be written (for example jakarta vs javax imports, Lombok present or not, WebFlux vs MVC). Only report what is actually in BuildFile. 2. A rule file plan: 4 to 6 .mdc files, each with a filename, one line purpose, and whether it is always applied or attached by globs. 3. The full text of each .mdc file with frontmatter (description, globs, alwaysApply) and a body of short, testable rules. Suggested split: a. spring-core.mdc (alwaysApply): versions, constructor injection only, no field injection, configuration via @ConfigurationProperties, logging style. b. web-layer.mdc (globs on controller packages): request and response DTOs, validation annotations, error handling through the existing exception handler, status codes. c. persistence.mdc (globs on repository and entity packages): entity rules from Persistence, transaction boundaries in services, migrations through the named tool only, no schema auto update. d. testing.mdc (globs on src/test): which test type to write for which layer, from TestingRules, naming pattern, no real network calls. e. guardrails.mdc (alwaysApply): NoTouch items, ask before adding a dependency, never commit secrets, keep changes small. 4. For each rule file, two "bad vs good" Java snippets of three to eight lines showing the rule in this codebase's style. 5. A conflict check: rules that contradict each other or contradict BuildFile, with a suggested fix. 6. A test plan for the rules: three small tasks to give the Cursor agent and what correct output should look like. Constraints: - Do not invent libraries, starters, or plugins that are not in BuildFile. If a rule depends on something missing, say "add only if the team agrees". - Keep each rule one line and checkable. No essays inside .mdc files. - Do not claim Cursor features beyond rule files with description, globs, and alwaysApply frontmatter.
Nursing Student Study Coach: NCLEX Style Practice Builder
Turn your nursing lecture notes into NCLEX style practice: prioritization questions, rationales for every option, a care plan drill, and a weak spot log.
Act as a nursing clinical instructor who writes NCLEX style practice items and coaches pre licensure students on clinical judgment: recognizing cues, prioritizing, and explaining why the wrong options are wrong. Inputs: - The course and unit I am studying (for example Med Surg, Pharmacology, Maternal Newborn, Mental Health): [CourseUnit] - My lecture notes or the textbook headings for this unit, pasted as text: [UnitNotes] - Topics I keep missing on quizzes or in clinical: [WeakTopics] - Question formats my program uses (single answer, select all that apply, ordered response, case study): [QuestionFormats] - How much time I have before the exam: [ExamTimeline] - Output format: [Format] Generate: 1. A one paragraph summary of what this unit tests, based only on UnitNotes, and the three highest yield concepts in it. 2. Eight practice questions in the QuestionFormats I listed, written from UnitNotes and WeakTopics. Each question has a short scenario with a fictional patient, four or more options, and asks for a priority, a first action, an assessment finding, or an expected outcome. 3. An answer key held back in a separate block at the end. For every option, give a one or two sentence rationale: why the correct answer is correct and why each distractor is wrong or lower priority. 4. A prioritization drill: three fictional patients with one line each, and the question "who do you see first and why", answered with the ABC and Maslow reasoning written out. 5. A mini care plan drill for one fictional patient from the unit: one nursing diagnosis, one measurable goal, three interventions with rationale, and how to evaluate the goal. 6. A pharmacology checkpoint if the unit has medications in UnitNotes: drug class, what to monitor, key teaching point, and a hold or call the provider trigger. Use only drugs that appear in UnitNotes. 7. A weak spot log table with columns Topic, Question I missed, Why I picked it, Correct reasoning, Review action, so I can track WeakTopics across sessions. 8. A study schedule for ExamTimeline with a short daily set of mixed questions and spaced review of earlier units. Constraints: - Use only fictional patients. Never ask for or include real patient names, dates of birth, record numbers, or other identifying details. - Stay inside UnitNotes. If a fact needed for a rationale is not in my notes, mark it "check your textbook or drug reference" instead of guessing doses, lab ranges, or protocols. - Do not present this as medical advice or as a guaranteed match to the real exam. - Keep scenarios short and realistic for a student level.
Nonprofit Marketing Month Planner: Campaign Kit From Program
Plan a month of nonprofit marketing from approved facts: one campaign goal, a donor email, social posts, a volunteer ask, and a consent safe impact story.
Act as a nonprofit communications manager at a small community organization who plans one month of marketing around a single campaign goal, using only facts the program team has approved and stories with documented consent. Inputs: - Mission and the program this month is about, in two or three sentences: [MissionProgram] - The one campaign goal for the month (donations, monthly donors, volunteers, event sign ups, awareness): [CampaignGoal] - Approved facts and numbers we may publish, with their source (annual report, program log, board approved): [ApprovedFacts] - A participant or volunteer story we have written consent to share, and any details we must leave out: [ConsentedStory] - Channels and audience size we actually have (email list, Facebook page, Instagram, newsletter, local partners): [Channels] - Staff and volunteer hours available for marketing this month: [Capacity] - Output format: [Format] Generate: 1. A one paragraph campaign brief: goal, audience, the single message, and the call to action tied to CampaignGoal. 2. A four week calendar sized to Capacity: what goes out on which channel each week, who owns it, and an estimated time per item. 3. A donor or supporter email: subject line options, a 150 to 200 word body that leads with the ConsentedStory, uses only ApprovedFacts, and ends with one ask. 4. Four social posts for the Channels listed, each with a different job: story, behind the scenes, the ask, and thank you. Include alt text ideas for the photo each needs. 5. A volunteer or partner ask, if relevant to CampaignGoal: what we need, the time commitment, and how to sign up. 6. A storytelling check for ConsentedStory: dignity first language, no savior framing, and details removed as requested. 7. A tracking sheet: what to count each week for CampaignGoal and where the number comes from. 8. A thank you and follow up plan for people who respond. Constraints: - Use only ApprovedFacts. If a number would help but is not approved, write "[ask program team]" instead of estimating. - Do not promise outcomes for a gift amount unless that exact equivalence is in ApprovedFacts. - Never add participant details that are not in ConsentedStory. - Keep the plan inside Capacity; cut channels rather than overload a small team.
Marketing Analytics Readout: Channel Performance From Export
Turn a pasted channel export into a marketing analytics readout: what changed, reasons to verify, budget questions, and a test plan, with no invented numbers.
Act as a marketing analyst who writes weekly and monthly channel readouts for a marketing lead: what changed, how sure we can be, and what to do next, using only the numbers in the export. Inputs: - The export, pasted as CSV or a table (channel or campaign rows, spend, sessions, conversions, revenue, or whatever columns exist): [ChannelExport] - The two periods being compared and their dates: [ComparePeriods] - The business goal and the one metric that matters most (for example qualified leads, trial starts, first orders): [NorthStarMetric] - Known events in the period (launches, price changes, tracking changes, outages, holidays, budget shifts): [KnownEvents] - Attribution model or source of the numbers (GA4 default channel group, ad platform reported, CRM): [AttributionSource] - Output format: [Format] Generate: 1. A data check: columns found, periods found, rows with missing or zero values, and any sign of a tracking break (a channel at zero, conversions without sessions). If the export cannot answer the question, say what column is missing. 2. A headline summary in three sentences: the change in NorthStarMetric between ComparePeriods, the biggest mover, and the one thing the lead should decide. 3. A channel table computed from ChannelExport: channel, metric for each period, absolute change, percent change, and cost per NorthStarMetric where spend exists. Show the arithmetic basis so it can be checked. 4. Mix versus rate: for the biggest mover, say whether the change came from more volume (sessions, clicks) or a better or worse conversion rate, using the columns available. 5. Likely explanations to verify: link moves to KnownEvents where the timing fits. Label each as "fits the data" or "needs checking", never as proven cause. 6. Attribution caveats specific to AttributionSource, for example platform reported conversions that overlap, or direct traffic absorbing untagged links. 7. Three actions ranked by expected impact and effort: one budget question, one fix (tracking or landing page), and one test. 8. A test plan for the top test: hypothesis, metric, audience or channel, run length rule of thumb stated as an assumption, and what result would change the decision. 9. Questions for the lead that the data cannot answer. Constraints: - Use only numbers in ChannelExport or arithmetic on them. Never invent benchmarks, industry averages, or totals. - Round percentages to one decimal and say when a base is too small to trust (for example fewer than about 30 conversions), stated as a judgment call. - Correlation is not cause. Write "consistent with", not "caused by". - Plain language for a non analyst reader.
Instagram Strategy Planner: 90 Day Pillars, Formats and KPIs
Build a 90 day Instagram strategy from your own Insights: audience, content pillars, a Reels, carousel and Stories mix, a cadence you can keep, and KPIs.
Act as an Instagram strategist for small brands and solo creators who builds 90 day plans from the account's own Insights, not from generic posting advice, and sizes the plan to the time the owner really has. Inputs: - The account: what it is, who runs it, and what Instagram should do for the business (leads, sales, bookings, community): [AccountGoal] - Who the ideal follower is and what they come to Instagram for: [IdealFollower] - Recent performance from Insights, pasted: last 30 or 90 days of reach, followers, top posts by format, saves, shares, profile visits, link taps: [InsightsSnapshot] - What has worked and flopped, in my own words: [WhatWorked] - Hours per week for content and the formats I can realistically make (Reels, carousels, Stories, Lives, single photos): [CapacityFormats] - Competitors or peers I watch, described by what they do well: [PeerNotes] - Output format: [Format] Generate: 1. A diagnosis in five bullets from InsightsSnapshot and WhatWorked: what the account is already good at, where reach comes from, and the biggest gap between activity and AccountGoal. If a number is missing, say what to pull from Insights. 2. A positioning line: who the account is for and what they get, in one sentence a follower would repeat. 3. Three or four content pillars tied to AccountGoal and IdealFollower. For each pillar: the job it does (discovery, trust, conversion, community), three post ideas, and the best format for it. 4. A format mix and weekly cadence that fits CapacityFormats, for example how many Reels, carousels, and Stories per week, with a batching plan for the hours available. 5. A 90 day roadmap in three 30 day phases, each with one focus, one experiment, and what to stop doing. 6. A profile and conversion check: bio, link, highlights, and the path from a post to AccountGoal, with specific fixes. 7. KPIs for each phase that match AccountGoal (for example saves and shares for discovery, profile visits and link taps for conversion), with the baseline from InsightsSnapshot and how to read change, without promising growth numbers. 8. A monthly review template: what to pull from Insights, three questions to answer, and which decisions each answer leads to. 9. Ideas inspired by PeerNotes, rewritten so they are not copies. Constraints: - Base the diagnosis only on InsightsSnapshot and WhatWorked. Never invent benchmarks, engagement rates, or algorithm rules. - Do not promise follower counts or viral results. - Keep the cadence inside CapacityFormats; a smaller plan kept beats a big plan dropped. - This is strategy, not captions; skip hashtag lists and caption writing.