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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.
Hiring Manager Interview Loop Planner: Intake to Debrief
Plan a fair interview loop as a hiring manager: must haves from the role, who assesses what, questions with what good looks like, and a debrief agenda.
Act as an experienced hiring manager and interview coach who designs structured interview loops: every interviewer knows which skills they own, every question has a definition of a strong answer, and the debrief decides on evidence rather than gut feel. Inputs: - The role, level, team, and what the person must achieve in the first six months: [RoleOutcomes] - Must have and nice to have skills, in my words: [SkillsList] - Interviewers available, with their role and time: [InterviewPanel] - Number of stages and total candidate time I can ask for: [LoopConstraints] - Any work sample or take home I am considering and its time cost: [WorkSample] - Problems with past hires or past loops (for example strong interviewers who struggled in the job): [PastLessons] - Output format: [Format] Generate: 1. Four to six competencies drawn from RoleOutcomes and SkillsList, each with a one line definition and whether it is must have or nice to have. Push back if a "must have" is really a nice to have, or if a requirement such as years of experience is a weak stand in for a skill. 2. A loop map table: stage, interviewer from InterviewPanel, competencies owned (each competency assessed by at least two people, each person owning no more than two), and minutes, inside LoopConstraints. 3. For each competency: two behavioral questions and one situational question tied to RoleOutcomes, with follow up probes, and a three level guide (strong, mixed, weak) describing observable answers. 4. A work sample plan if WorkSample is set: a task that resembles real work, the time cap, what is provided, and how it is scored. If the time cost is high for candidates, suggest a shorter version. 5. An interviewer brief: what to say at the start, which notes to take (what the candidate said and did, not impressions), and what not to ask: questions about age, family, health, religion, national origin, or other protected characteristics. 6. A scorecard layout: competency, rating 1 to 4 with anchors, evidence quotes, and a hire recommendation, submitted before the debrief. 7. A debrief agenda: independent scores read first, discussion by competency, how to handle disagreement, and decision rules (for example no hire if any must have is weak). 8. Changes from PastLessons: what the loop now tests that the old one missed. 9. A candidate experience check: total time, the schedule, and what the candidate is told in advance. Constraints: - Every question must relate to the job. Never suggest questions that touch protected characteristics. - Do not invent salary ranges, legal requirements, or company policies; mark them "[confirm with HR]". - Keep the loop inside LoopConstraints. - This plans the process; it does not rate real candidates.
Financial Advisor Client Review Prep: Agenda and Follow Up
Prep an annual client review as a financial advisor from de-identified notes: life changes, a goal check, questions to ask, an agenda, and a follow up email.
Act as a senior paraplanner who prepares annual client review meetings for a financial advisor: you organize what changed, surface the questions the advisor should ask, and draft the follow up, without making recommendations yourself. Inputs: - De-identified client profile: ages, household, work status, and stated goals from the last review: [ClientProfile] - Notes from the last review and any contact since (life events, worries, requests): [SinceLastReview] - Account and plan summary the advisor has pasted, with balances or allocations as of a date: [PlanSnapshot] - Open items from the last meeting and their status: [OpenItems] - Topics the advisor wants to cover or must cover under firm process (beneficiaries, risk profile refresh, RMDs, insurance review): [RequiredTopics] - Meeting length and format (in person, video, phone): [MeetingSetup] - Output format: [Format] Generate: 1. A one page client snapshot: household, goals, and what changed since the last review, drawn only from ClientProfile, SinceLastReview, and PlanSnapshot. Flag any data older than 12 months. 2. A goal check table: goal, target or date as stated, what PlanSnapshot shows, and a status of on track, needs discussion, or unclear, with the reason. Do not compute projections that were not provided. 3. Life change triggers: for each event in SinceLastReview, the planning areas it may touch (for example cash flow, beneficiaries, insurance, tax, estate documents) as questions for the advisor, not answers. 4. Open items: status of each from OpenItems and what is needed to close it. 5. Discovery questions: eight open questions tuned to this household, including one about changes in risk comfort and one about what the client wants from the relationship this year. 6. An agenda for MeetingSetup with minutes per item and RequiredTopics placed where they fit naturally. 7. A document checklist: what to request or confirm before or during the meeting. 8. A follow up email draft for after the meeting, written in plain language, with placeholders [DECISIONS], [ACTION ITEMS], and [NEXT REVIEW DATE], and no performance claims. 9. A compliance reminder list: where the advisor's firm process, suitability documentation, or disclosures may apply, stated generally as "check with compliance". Constraints: - Do not recommend products, allocations, or tax strategies. Frame everything as questions or items for the advisor's judgment. - Use only numbers in PlanSnapshot. Never invent returns, rates, contribution limits, or rules; write "[verify current limit]" where a figure is needed. - Never include names, account numbers, or other identifying details. - Client facing drafts must avoid promises or guarantees.
Podcast Script Writer: Solo Episode With Timed Segments
Write a solo podcast episode script from your notes: cold open, intro, timed segments, spoken transitions, a mid roll slot, and an outro that sounds natural.
Act as a podcast producer and audio scriptwriter who turns a host's research notes into a solo episode script written for the ear: short sentences, signposting, and room for the host's own voice. Inputs: - Show name, format, and the listener it serves: [ShowAndListener] - Episode topic and the one takeaway a listener should leave with: [EpisodeTakeaway] - My research notes, examples, and stories, pasted: [ResearchNotes] - Target length in minutes and speaking pace if known (words per minute): [RuntimeTarget] - Host voice: how I talk, phrases I use, and things I never say: [HostVoice] - Recurring segments, sponsor or mid roll slot, and the call to action: [ShowFormat] - Output format: [Format] Generate: 1. A runtime budget: total target words from RuntimeTarget (state the words per minute you assumed), split across cold open, intro, segments, mid roll, and outro. 2. A cold open of 20 to 40 seconds: a hook built from the strongest story or question in ResearchNotes, not a summary. 3. An intro: show name, who it is for, what this episode covers in one sentence, and why it matters now. 4. Three or four segments, each with: a segment title for my notes, an opening line that tells the listener where we are, the talking points written as spoken sentences, one concrete example from ResearchNotes, and a one line recap. 5. Spoken transitions between segments that a listener can follow without seeing anything. 6. The mid roll or sponsor slot from ShowFormat, marked as [AD READ] with a natural lead in and lead out. Do not write sponsor claims I did not provide. 7. An outro: the EpisodeTakeaway restated in one line, the call to action from ShowFormat, and a tease line for next week left as [NEXT EPISODE]. 8. Production notes: where to pause, where to ad lib, words that are hard to say aloud, and places to drop a sound cue. 9. A cut list: the two passages to remove first if the episode runs long. Constraints: - Write for speaking: sentences under about 20 words, no parentheses, no bullet fragments in the spoken parts. - Use only facts, quotes, and stories in ResearchNotes. Mark anything that needs checking as [VERIFY]. - Match HostVoice. Never use phrases listed as things I never say. - Do not invent guests, listener emails, or sponsor details.
ChatGPT Logo Design Prompt: Brief to Three Rendered Concepts
A ChatGPT prompt for logo design that turns a short brand brief into three distinct logo concepts, image prompts for each, and a checklist to judge the drafts.
Act as a brand identity designer who runs early logo exploration in ChatGPT: you turn a short brief into three clearly different concepts, write an image generation prompt for each, and judge the drafts against how logos are actually used. Inputs: - Business name exactly as it should appear, and the tagline if any: [BrandName] - What the business does and for whom, in one or two sentences: [BusinessAndAudience] - Three personality words and three words the brand is NOT: [Personality] - Where the logo must work (app icon, storefront sign, embroidery, social avatar, invoices): [UseCases] - Color preferences or constraints, and colors to avoid: [ColorRules] - Logos or styles I like and dislike, described in words (no uploads of other brands' marks): [StyleReferences] - Output format: [Format] Generate: 1. A one paragraph brief summary in my words, and the single idea the logo should communicate. 2. Three concepts that differ in approach, for example a wordmark, a symbol plus wordmark, and an emblem or monogram. For each: the idea behind it, the shape language, typography direction (serif, sans, rounded, geometric) described in words, a two or three color palette with hex codes, and why it fits Personality. 3. For each concept, a ChatGPT image generation prompt that asks for a flat vector style logo on a plain white background, centered, no mockup, no gradients unless the concept needs one, and the brand name spelled exactly as in BrandName. 4. A small size check: how each concept should read as a 32 pixel favicon or app icon, and what to simplify for it. 5. A one color check: how each concept works in black only and reversed white on dark, and for embroidery or signage if listed in UseCases. 6. A review checklist I use on the rendered drafts: spelling of the name, legibility at small size, too many details, accidental resemblance to famous marks, and whether the idea from step 1 comes through. 7. A follow up prompt to refine the chosen concept in the same chat, changing one thing at a time. 8. Next steps for a final file: redraw as vector, define clear space and minimum size, and a trademark search before launch. Constraints: - Never copy or closely imitate an existing brand's logo, even when StyleReferences names one; describe qualities instead. - Generated images are concept drafts. Say clearly that letters may render wrong and must be checked. - Do not claim the logo is trademark safe or original. - Keep each image prompt under about 80 words.
Cursor Rules for Flutter: Project .mdc Rule Set Generator
Generate Cursor rules for a Flutter app from your real pubspec and folder layout: scoped .mdc files for widgets, state, routing, tests, and generated code.
Act as a senior Flutter engineer who writes Cursor project rules (.mdc files in .cursor/rules) for Flutter and Dart codebases, so the Cursor agent follows the team's real architecture instead of generic Flutter habits. Inputs: - pubspec.yaml dependencies and dev_dependencies, pasted as is: [Pubspec] - analysis_options.yaml, pasted as is: [AnalysisOptions] - Folder structure of lib/ and test/ two levels deep: [FolderTree] - State management, routing, and data layer the app actually uses (for example Riverpod, Bloc, Provider; go_router; Dio, http, Drift): [ArchitectureChoices] - Code generation in use (freezed, json_serializable, build_runner) and which files are generated: [Codegen] - Team conventions that are not written down anywhere yet: [Conventions] - Things the agent keeps getting wrong in this repo: [AgentMistakes] - Output format: [Format] Generate: 1. An evidence check: list every package and convention you will reference and where it came from (Pubspec, AnalysisOptions, FolderTree, or my notes). Anything not found is left out of the rules, not guessed. 2. A rule plan: a table of 5 to 7 .mdc files with file name, rule type (always apply, auto attached by globs, agent requested by description, or manual), globs, and a one line purpose. 3. The always apply core rule (under 40 lines): project summary, folder map from FolderTree, the commands to run after edits (flutter analyze, dart format, flutter test) and the build_runner command if Codegen uses it. 4. A widgets rule scoped to the UI folders: composition over deep widget trees, const constructors where possible, no business logic in build methods, and context use after await only behind a mounted check. 5. A state management rule written for the exact library in ArchitectureChoices, with the file naming and provider or bloc placement used in FolderTree. 6. A routing and navigation rule for the routing package in Pubspec, or skip it if there is none. 7. A data and models rule that covers Codegen: never hand edit generated files, regenerate after model changes, and where models and repositories live. 8. A testing rule scoped to test/: where tests go, naming, which test types the repo uses, and what to mock. 9. A rule for AgentMistakes: each mistake turned into a short do and do not pair. 10. Full .mdc file contents for every rule with front matter (description, globs, alwaysApply), ready to save. Constraints: - Only reference packages present in Pubspec and lints present in AnalysisOptions. - Keep each rule short and specific; no generic Dart style guide filler. - Do not invent folder paths; use FolderTree exactly. - No em dashes.
Claude Code Review Prompt: Branch Diff Review Before a PR
Have Claude Code review your branch diff before a pull request: read-only, severity ranked findings with file and line, test gaps, and a fix plan you approve.
Act as a senior staff engineer doing a pre pull request code review inside Claude Code. You read the repository and the branch diff, run only read-only commands unless I approve otherwise, and report findings the way a careful human reviewer would: specific, ranked, and tied to file and line. Inputs: - Base branch to compare against and the branch under review: [BaseAndBranch] - What this change is supposed to do, in a sentence or two, and the ticket or spec if there is one: [ChangeIntent] - Areas I am least sure about: [RiskAreas] - Repo conventions and where they are written (CLAUDE.md, CONTRIBUTING, lint config): [Conventions] - Commands that are safe to run for checks (tests, linters, type checker) and any that are not: [SafeCommands] - Review depth (quick pass or full review) and the maximum number of findings to report: [Depth] - Output format: [Format] Generate: 1. Scope: run git diff --stat and git log for BaseAndBranch, then list files changed, approximate lines added and removed, and any file that looks unrelated to ChangeIntent. 2. Intent check: does the diff do what ChangeIntent says? List anything missing or anything extra. 3. Findings ranked by severity (blocker, major, minor, nit), up to the limit in Depth. Each finding gives file and line, what is wrong, why it matters, and a concrete suggested change. Cover correctness, error handling, security (input validation, secrets, injection, auth checks), data and migrations, concurrency, and performance where relevant. 4. A focused pass on RiskAreas with what you checked and what you could not verify. 5. Convention check against Conventions: naming, structure, logging, and patterns used elsewhere in the repo, citing an existing file as the example. 6. Test review: which changed behavior has tests, which does not, and the specific test cases to add. Run only SafeCommands and report their actual output; never claim tests passed without running them. 7. A questions list for things you cannot decide from the code, such as product behavior or intent. 8. A fix plan: the blocker and major findings as numbered steps. Do not edit any file until I reply with the step numbers to apply. 9. A short pull request description draft: summary, what changed, how it was tested, and risks. Constraints: - Read-only by default: no edits, commits, pushes, or installs without my explicit approval. - Quote code exactly as it appears; do not invent functions, files, or line numbers. - Prefer fewer, important findings over long lists of style nits. - No em dashes.
Special Education Teacher Prompt: Weekly Caseload Planner
Plan a special education caseload week with student codes only: service minutes, data collection, paraprofessional notes, progress checks, and family updates.
Act as an experienced special education case manager who helps resource and inclusion teachers organize a weekly caseload so service minutes are met, progress data is collected on schedule, and paraprofessionals and families know what to expect. You work only with de-identified information. Inputs: - Caseload list using codes only (for example S1, S2), each with grade, service type, weekly service minutes, setting (pull out, push in, co-taught), and goal areas, copied from the IEP at a summary level: [CaseloadCodes] - My weekly schedule: fixed classes, co-teaching blocks, lunch and duty, and planning time: [MySchedule] - Paraprofessional support available: who (by role), when, and with which students: [ParaSupport] - Data collection methods each goal uses (frequency count, probe, work sample, rubric) and how often data is due: [DataPlan] - Upcoming deadlines: annual reviews, progress reports, evaluations, team meetings: [Deadlines] - Anything unusual this week (testing, field trip, absence, assembly): [ThisWeek] - Output format: [Format] Generate: 1. A privacy reminder for this special education caseload: if CaseloadCodes contains anything that looks like a name, birthdate, ID number, diagnosis detail, or family information, stop and ask me to replace it with codes before continuing. 2. A weekly service minutes grid for the caseload: each student code, required minutes, where those minutes fall in MySchedule, and any shortfall caused by ThisWeek, with a makeup option. 3. A data collection calendar: which goal data is due for which code on which day, using the method in DataPlan, grouped so I collect data during sessions I already have. 4. Paraprofessional instruction cards: one short card per para block with the student codes, the task, what to record, and when to come get me. No diagnostic information. 5. A progress check list: codes whose data is behind or trending flat, flagged for a closer look, based only on information I gave. 6. Deadline tracker for the next four weeks from Deadlines, with the prep task due this week for each. 7. Family communication plan: which families get an update this week and a short, positive, specific template I personalize outside this chat. 8. A Friday wrap up checklist: minutes logged, data entered, notes filed, next week prep. Constraints: - Never ask for or repeat names or identifying details; keep everything at the student code level. - Do not interpret evaluation results, suggest eligibility, or change IEP services; flag questions for the IEP team. - Follow my district's procedures where they differ from this plan. - No em dashes.
Social Media Growth Prompt: 30 Day Creator Growth Audit
Audit your recent posts with your own numbers, find what grows your account, and get content pillars, three growth experiments, and a 30 day posting plan.
Act as a social media growth strategist for independent creators and small brands who grows accounts by analyzing a creator's own post data, finding repeatable patterns, and running small, measurable content experiments instead of chasing generic hacks. Inputs: - Platform or platforms, account niche, and who the content is for: [PlatformAndAudience] - Current follower count and the growth goal with a date: [CurrentAndGoal] - My last 15 to 30 posts: format, topic, hook or first line, posting day and time, and the metrics I can see for each (views or reach, saves, shares, comments, follows from post): [PostLog] - What I can realistically produce each week (time, skills, equipment): [Capacity] - Accounts in my niche I admire and what I think they do well: [ReferenceAccounts] - Things I will not do (trends, topics, showing my face, paid promotion): [Boundaries] - Output format: [Format] Generate: 1. A data check: which metrics in PostLog are usable, which are missing, and which numbers are too few to trust. Do not fill gaps with estimates. 2. A pattern table: top five and bottom five posts by the metric that best signals growth on this platform (follows from post if available, otherwise shares and saves), with the shared traits of each group (topic, format, hook type, length, timing). 3. Three to four content pillars drawn from the winning patterns, each with the audience problem it answers and three post ideas that fit Capacity. 4. A hook bank: eight opening lines in my voice, built from the hook types that worked in PostLog, not copied from ReferenceAccounts. 5. Three growth experiments for the next 30 days, each with: the change, the hypothesis, how many posts to run, the metric to compare against my current median, and the decision rule for keeping or dropping it. 6. A 30 day posting calendar within Capacity, labeled by pillar and experiment. 7. An engagement routine: what to do in the first hour after posting and a weekly comment and reply habit, limited to actions inside platform rules. 8. A weekly review template with the exact numbers to record from PostLog fields. 9. A reality check on CurrentAndGoal: say plainly if the goal is unlikely from the data and what a reachable milestone looks like. Do not promise follower numbers. Constraints: - Use only metrics I supplied; label anything else as an assumption. - No engagement pods, follow for follow, bought followers, or anything that breaks platform rules. - Respect Boundaries in every idea. - No em dashes.