Your AI Action Plan

Analyze this data for trends, outliers, and practical next steps. Return: 1. top 5 findings, 2. possible explanations, 3. questions to verify, 4. recommended next actions. Do not assume causes without evidence.

Data:
[PASTE]

In this workbook, analyze [TABLE/RANGE] and answer: What changed most, what looks unusual, which rows need attention, and what chart or pivot would best explain the result?

Use these spreadsheet findings to write a decision memo. Include: headline insight, supporting numbers, likely drivers, caveats, recommended action, and what data should be checked next.

Findings:
[PASTE]

Create a recurring analysis checklist for [DATA TYPE]. Include: required inputs, cleaning checks, metrics to calculate, outlier rules, interpretation questions, caveats, and the final memo format.

Write a weekly [TEAM / CLIENT / PROJECT] report.
Period: [DATE RANGE]
Metrics: [PASTE METRICS]
Highlights: [WHAT WENT WELL]
Risks or blockers: [WHAT NEEDS ATTENTION]
Next actions: [3-5 BULLETS]
Audience: [MANAGER / CLIENT / TEAM]. Keep it factual, concise, and easy to scan.

Analyze this report data before drafting the summary.
Data: [PASTE TABLE OR METRICS]
Return: 1. Top 5 changes, 2. likely explanations, 3. questions to verify, 4. what should be highlighted, 5. what should not be overclaimed.

Turn this exported data into a decision memo.
Audience: [WHO WILL READ IT]
Data: [PASTE CSV OR TABLE]
Return: executive summary, key changes, likely causes, recommended action, risks, and a short appendix explaining assumptions.

Create a reusable monthly review template for [ROLE / TEAM]. It should include: required inputs, KPI table, variance analysis, stakeholder narrative, recommended actions, risks, and a quality checklist before sending.

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 compliance-sensitive document for human review. Return: key facts, deadlines, obligations, missing information, ambiguous language, and questions for the responsible reviewer. Do not give legal, tax, or employment advice.

Document:
[PASTE]

Turn this policy or form instruction into a checklist. Include required fields, approvals, deadlines, evidence needed, common errors, and escalation triggers. Mark anything that needs a qualified human decision.

Text:
[PASTE]

Prepare a reviewer packet for this document. Return: 1. plain-English summary, 2. evidence table with source excerpts, 3. missing information, 4. risk questions, 5. reviewer decision log template. Keep all final decisions blank.

Document:
[PASTE]

Create a reusable compliance-review prompt for [ROLE]. It must require AI to: summarize only, cite source text, flag uncertainty, list missing information, avoid final legal/tax/employment decisions, and produce questions for the qualified reviewer.

Create a 10-slide presentation on [TOPIC] for [AUDIENCE - e.g. "potential B2B clients"].
Slide structure: agenda, problem, solution, 3 key benefits, case study, data slide, pricing/next steps, CTA.
Tone: [professional / conversational / bold].

I need to create a presentation for [AUDIENCE] about [TOPIC].
My goal is to [GOAL - e.g. "convince the client to start a pilot project"].
Write a slide-by-slide script: title + 3 bullet points per slide.
Keep each bullet under 12 words. Total: 8-10 slides.
Start with the most important point, not context.

Step 1 - Research brief (Perplexity):
"Find current, cited evidence for [TOPIC] relevant to [AUDIENCE]. Return 5 facts, 3 risks, and 3 credible examples."

Step 2 - Narrative outline (Claude):
"Turn this research into an 8-slide persuasive deck. For each slide include: title, core message, one supporting fact, and speaker note."

Step 3 - Paste the outline into Gamma and generate the draft deck.

Step 1 - Brief to structure (Claude):
"I'm preparing a [TYPE] presentation for [AUDIENCE].
Context: [2-3 sentences about the situation].
Goal: [what decision or action you want from the audience].
Constraints: [length, tone, things to avoid].
Create a presentation outline with: goal per slide, key message, supporting data point."

Step 2 - Paste outline into Gamma.app -> generate draft.
Step 3 - Export to Canva -> apply brand colors, fonts, logo.

Draft budget-to-actual variance commentary.
Data: [PASTE TABLE]
Context: [PASTE NOTES]
Return: material variances, likely drivers, source evidence, questions to verify, and a management-ready explanation. Do not invent causes or numbers.

In this workbook, identify the largest budget-to-actual variances, trends, and outliers. Return the rows or accounts to inspect, possible drivers, and charts or pivots that would support the analysis.

Create a variance review packet from this workbook export.
Data: [PASTE]
Return: executive summary, variance table, likely drivers, evidence needed, questions for account owners, risks, and final-review checklist. Keep all final conclusions marked draft until verified.

Create a monthly variance commentary playbook. Include: materiality thresholds, account-owner questions, evidence rules, approved language, forbidden assumptions, escalation triggers, and management-report template.

Create forecast scenario assumptions for [BUSINESS / PRODUCT].
Drivers: [PASTE]
Historical data: [PASTE]
Return: base, upside, and downside assumptions, rationale, risks, source evidence needed, and model input fields. Do not calculate final outputs.

Summarize these macroeconomic series for a forecast assumption pack.
Series and values: [PASTE]
Return: trend, latest movement, model implication, caveats, and what source date should be cited.

Create a scenario forecast packet.
Internal drivers: [PASTE]
External data: [PASTE]
Return: scenario assumptions, evidence table, model input checklist, sensitivity questions, and risks. Mark all assumptions as draft until finance lead approval.

Create a forecast assumption governance template. Include: driver name, source, owner, refresh cadence, calculation logic, sensitivity range, approval status, change log, and reviewer questions.

Summarize this SEC filing section for analyst review.
Text: [PASTE]
Return: key facts, numbers mentioned, management claims, risk factors, exact source excerpts to verify, and questions for the analyst. Do not make an investment recommendation.

Compare these filing excerpts.
Prior period: [PASTE]
Current period: [PASTE]
Return: changed language, changed numbers, new risks, removed risks, potential significance, and source lines to verify.

Create a filing research packet from these excerpts.
Excerpts: [PASTE]
Return: risk changes, operating metric changes, model assumptions affected, source excerpts, questions for finance lead, and do-not-use-until-verified warnings.

Create an SEC filing review checklist for financial analysts. Include: sections to review, numbers to extract, language-change checks, risk-factor checks, source citation rules, model-impact fields, and final reviewer sign-off.

Create a draft business-case memo outline.
Analysis notes: [PASTE]
Return: thesis, supporting evidence, risks, assumptions, missing data, sensitivity questions, and reviewer checklist. Do not write a final recommendation.

Draft a business-case memo from this evidence.
Evidence: [PASTE]
Assumptions: [PASTE]
Return: executive summary, source-backed facts, assumptions, sensitivities, risks, caveats, and open questions for reviewer approval.

Create a finance-review packet from this research.
Research: [PASTE]
Model outputs: [PASTE]
Return: memo draft, assumptions table, risk section, reviewer questions, and presentation outline. Mark all recommendations as draft.

Create a finance memo QC rubric. Include: source traceability, assumption clarity, model link, sensitivity coverage, risk disclosure, prohibited claims, reviewer approval fields, and final sign-off checklist.

Write leadership commentary for these finance dashboard changes.
Metrics: [PASTE]
Return: key movements, likely drivers, business impact, caveats, and questions for data owners. Do not invent explanations.

From this dashboard, identify the biggest metric changes, likely driver dimensions, and segments that need investigation. Return a leadership-ready summary plus caveats.

Create a leadership brief from these BI findings.
Findings: [PASTE]
Return: headline, metric movements, likely drivers, confidence level, caveats, required follow-up, and decision needed.

Create a finance leadership commentary template library. Include templates for variance, forecast, liquidity, growth, margin, and risk updates. Each template must include required figures, source checks, caveats, and review-owner sign-off.