Your AI Action Plan

Write a client message from these notes.
Client context: [CONTEXT]
Goal: [UPDATE / ASK / EXPLAIN / FOLLOW UP]
Notes: [PASTE NOTES]
Tone: professional, warm, and concise.
Include: clear answer, next step, owner, and deadline if relevant.

Create five client-message templates for my role: status update, request for missing info, delay explanation, decision explanation, and follow-up. Each template should include placeholders, tone guidance, and a checklist for facts I must verify before sending.

Use this client context and draft to prepare a final message.
Context: [PASTE]
Draft: [PASTE]
Check for: factual accuracy, unclear promises, missing deadlines, tone risks, and next step. Return the revised message plus a send/no-send checklist.

Build a client communication style guide for [ROLE / COMPANY]. Include: approved tone, banned phrases, claims that require review, escalation triggers, examples of good messages, and a checklist before sending AI-assisted messages.

Write a [TYPE - cold outreach / follow-up / proposal / status update] email.
From: [YOUR ROLE] at [COMPANY]
To: [RECIPIENT ROLE] at [THEIR COMPANY]
Context: [1-2 sentences of background]
Goal: [what you want them to do]
Tone: [professional / friendly / direct]
Length: [short = 3 sentences / medium = 1 short paragraph / full = structured email]

Write a weekly marketing performance report.
Period: [DATE RANGE]
Metrics to include: [list your KPIs]
Highlights: [what went well]
Issues: [what underperformed and brief reason]
Next week priorities: [3 bullet points]
Audience: [manager / team / client]
Tone: factual, no fluff. Use bullet points for metrics, short paragraphs for narrative.

Turn these rough notes into a clear [EMAIL / STATUS UPDATE / REPORT].
Audience: [WHO WILL READ IT]
Purpose: [DECISION, UPDATE, REQUEST, OR ESCALATION]
Raw notes:
[PASTE NOTES]

Return:
1. Suggested subject line
2. Short summary
3. Main message in my tone: [DIRECT / WARM / EXECUTIVE]
4. Action items with owners and dates
5. Risks or open questions

I'll share 3 examples of emails I've written. After reading them, identify:
1. My typical sentence length and structure
2. Words or phrases I use often
3. My tone (formal / casual / direct / warm)
4. Things I never say

[PASTE EMAIL 1]
[PASTE EMAIL 2]
[PASTE EMAIL 3]

Now write a [TYPE] email using my style. Here's the context: [CONTEXT]

Clean this data before I enter it into [SYSTEM]. Return a table with columns: [COLUMNS]. Standardize dates, names, categories, and phone/email formatting. Add a final column called Review needed for anything uncertain. Do not invent missing values.

Raw data:
[PASTE]

Map this incoming form to my database fields. Required destination fields: [FIELDS]. Validation rules: [RULES]. Return a field mapping, transformations needed, and exception cases that should stop for human review.

Extract records from this input and prepare them for [SYSTEM]. Return: 1. clean records table, 2. duplicate warnings, 3. missing required fields, 4. values that need human review, 5. a short change log.

Input:
[PASTE]

Create a data-entry QA playbook for [PROCESS]. Include: required fields, allowed formats, duplicate checks, sensitive-data warnings, examples of good records, examples of records to reject, and a final human review checklist.

Create a research brief on [TOPIC] for [AUDIENCE]. Include: current landscape, 5 key facts, 3 risks, 3 open questions, and source links for every claim that affects a decision.

Review this research draft. Split it into: source-backed facts, reasonable inferences, unsupported claims, and questions to verify. Then rewrite the summary so unsupported claims are removed or clearly caveated.
Draft: [PASTE DRAFT]

Research [OPTIONS / VENDORS / TOPIC], compare them against [CRITERIA], and produce a recommendation memo. Include a table, tradeoffs, risks, source links, and the decision I should make if the priority is [COST / SPEED / QUALITY / RISK].

Create a research intake template for [ROLE / TEAM]. It should capture: decision to support, scope, time period, must-use sources, sources to avoid, comparison criteria, output format, approval owner, and caveats required before sharing.

Summarize this meeting.
Notes or transcript: [PASTE]
Return: 1. short summary, 2. decisions made, 3. action items with owner and due date, 4. risks, 5. follow-up message draft.

Review this meeting transcript and create a follow-up note. Separate exact decisions from discussion points. Flag anything unclear. Transcript: [PASTE TRANSCRIPT].

Convert this meeting transcript into project tasks. For each task include owner, due date, dependency, priority, and a follow-up email paragraph. Transcript: [PASTE].

Create a meeting memory template for [TEAM / CLIENT]. For each meeting, capture decisions, action items, repeated themes, unresolved questions, stakeholder commitments, and items to revisit next time.

Draft a calm, professional reply to this customer complaint.
Customer message: [PASTE MESSAGE]
Known facts: [ORDER / ACCOUNT / TIMELINE]
Policy I can offer: [REFUND / CREDIT / REPLACEMENT / ESCALATION]
Return: short acknowledgement, what went wrong from their view, what I will do next, one clear next step, and a note if this should be escalated to a supervisor before sending.

Here are 20 resolved customer complaints and the reply that worked.
Data: [PASTE TICKETS]
Return: 5 complaint types, one reply frame per type (tone, structure, placeholders), and notes about which type must always escalate to a supervisor.

Act as a customer service drafting assistant. For this support ticket, return: summary, customer sentiment, policy options that apply, draft reply, risk flags (legal, refund threshold, churn signal), and whether this needs supervisor approval before sending.
Ticket: [PASTE TICKET]

Build a de-escalation playbook for [BUSINESS / PRODUCT]. Include: complaint categories, allowed remedies, tone rules, phrases to avoid for legal reasons, escalation triggers with owners, 3 reply templates per category, and a supervisor review checklist.

Classify these support tickets.
Tickets: [PASTE BATCH]
Return per ticket: category (billing / technical / policy / shipping / other), priority (urgent / standard / low), suggested team or owner, one-sentence reason, and any ticket that looks like a legal or safety risk.

Here are 50 support tickets and the team each was correctly routed to.
Data: [PASTE TICKETS + TEAM]
Return: routing rules as if-then statements, ambiguous cases that need supervisor judgment, and cases where the rule might be wrong.

Turn this ticket export into an assignment queue.
Data: [PASTE EXPORT]
Return: priority, suggested owner, reason, risk flag, and cases that must go to a supervisor before being assigned. Keep original ticket IDs unchanged.

Create an escalation map for [TEAM]. Include: ticket types, first-response SLA, owner team, escalation path with names, supervisor-approval triggers, after-hours rules, and a weekly audit checklist.

Help me respond to a billing dispute.
Customer message: [PASTE]
Invoice / charge history: [PASTE]
Policy I can offer: [REFUND / PARTIAL / CREDIT / NONE]
Return: plain-language summary of what they dispute, whether the math checks out, which policy applies, a draft reply, and whether a supervisor or finance should approve before sending.

Draft a refund-decision memo.
Request: [PASTE]
FAQ / policy text: [PASTE]
Return: whether the request fits policy, exact clause it relies on, exceptions the supervisor could approve, numbers involved, and a customer-facing reply that matches the decision.

Here is today's disputed-charge export.
Data: [PASTE]
Return: dispute type, amount, account tier, likely outcome, recommended owner (rep / supervisor / finance), and any case that must be frozen before reply.

Create a refund and billing-dispute playbook for [BUSINESS]. Include: dispute categories, allowed remedies per tier, approval matrix (who signs off for what amount), required evidence, customer-message templates per outcome, legal or finance escalation triggers, and a weekly review checklist.

Turn this resolved ticket into a knowledge base article.
Ticket: [PASTE]
Return: title, customer-friendly summary, steps to resolve, related questions, and a note about what a supervisor should review before publishing.

Given this knowledge base article, produce three canned replies: short acknowledgement with link, fuller walkthrough, and apology-plus-workaround. Keep placeholders for name, order ID, and ticket number. Article: [PASTE ARTICLE].

Here are the last 100 support tickets.
Data: [PASTE]
Return: top 10 recurring questions, whether each already has a knowledge base article, draft titles for the missing ones, and a deflection-priority score based on ticket volume.

Create a monthly knowledge base maintenance system for [PRODUCT]. Include: ticket-to-article pipeline, review owner, tone and reading-level guide, publish checklist, stale-article retirement rules, and a quarterly audit.

Tag the themes in these tickets.
Tickets: [PASTE]
Return: top 5 themes with frequency, example ticket IDs, likely root cause, and questions to ask a product or ops owner before changing anything.

Write a weekly complaint report for the service manager.
Theme data: [PASTE]
Include: top 5 themes by volume, change vs previous week, likely causes, actions already taken, open questions, and a single recommendation the manager can approve or reject.

Use this ticket export to write a root-cause memo.
Data: [PASTE]
Return: issue description, affected segments, impact estimate, likely root causes ranked by evidence, options to fix or mitigate, and risks of doing nothing. Separate facts from hypotheses.

Build a quarterly voice-of-customer review for [BUSINESS]. Include: data sources, segmentation, top 10 themes, notable quotes, product and policy recommendations, owner per action, and metrics to monitor next quarter.