Purpose
Turn raw financial output into a concise, decision-ready narrative that tells business stakeholders what happened, why it happened, what it means, and what to do next — replacing "here are the numbers" with a story that drives action. Solves the recurring FP&A problem of having accurate data that fails to land because it isn't translated into causes, implications, and recommendations.
When to Use
Invoke this skill when the user asks to:
- Write commentary or narrative for a monthly/quarterly business review
- Explain budget-vs-actual or forecast variances to a non-finance audience
- Turn a financial spreadsheet or dashboard into board-deck talking points
- Summarize P&L, cash flow, or KPI trends into key takeaways
- Identify the real drivers behind a revenue miss or margin change
- Produce recommended actions from a set of financial results
Inputs Required
Before starting, collect:
- Financial data: The actuals, budget/forecast, and prior-period figures — pasted table, key line items, or dashboard summary
- Reporting period: The month, quarter, or range being analyzed
- Comparison basis: What actuals are measured against (budget, forecast, prior year, prior period)
- Audience: Who reads this (CFO, CEO, board, department head, non-finance operators)
- Business context: Any known events affecting the numbers (launch, price change, seasonality, one-time item)
- Key metrics of focus: The 3–5 metrics stakeholders care most about (e.g., revenue, gross margin, EBITDA, cash runway, CAC)
- Decision at hand: What choice or discussion this analysis is meant to inform, if any
If comparison basis or audience is not specified, default to budget-vs-actual for the reporting period and a mixed finance-plus-operator audience; note the assumption.
Instructions
Step 1: Establish the Baseline and Materiality Threshold
Before interpreting anything, frame the numbers.
- Restate the headline results for the focus metrics: actual, comparison figure, variance in absolute terms and percentage
- Set a materiality threshold appropriate to the business — flag variances greater than the larger of 5% or a meaningful dollar amount for this entity; ignore noise below it
- Note the direction of each material variance (favorable / unfavorable) using business logic, not just sign (lower cost = favorable; lower revenue = unfavorable)
Step 2: Decompose the Variances into Drivers
Do not stop at "revenue was down 8%." Break each material variance into its underlying components.
- Volume vs. rate vs. mix: For revenue, separate unit/volume changes from price/rate changes from product-mix shifts
- Fixed vs. variable: For costs, distinguish structural spend from spend that scales with activity
- Timing vs. structural: Determine whether a variance is a permanent trend or a timing shift that will reverse
- One-time vs. recurring: Isolate any non-repeating items so the underlying run-rate is clear
- Attribute each driver to a plausible business cause using the context provided; where cause is uncertain, state it as a hypothesis to validate, not a fact
Step 3: Read the Trend, Not Just the Snapshot
Place the period in motion.
- Identify direction over the available periods (accelerating, decelerating, stabilizing, reversing)
- Call out any inflection points or trend breaks
- Distinguish a genuine trend from a single anomalous period
- Where a metric is trending toward a threshold (covenant, runway, target), quantify the trajectory and expected timing
Step 4: Rank Risks and Opportunities
Convert the analysis into forward-looking implications.
- List the material risks — where current trends threaten targets, cash, or margins — ranked by potential impact and likelihood
- List the material opportunities — where favorable drivers could be extended or reinforced — ranked the same way
- For each, state the "so what": the consequence if nothing changes
Step 5: Produce Recommended Actions
Each recommendation must be specific, owned, and tied to a driver identified above.
- State the action, the metric it moves, and the expected direction of impact
- Assign a suggested owner or function where inferable
- Sequence by urgency: what to do this period vs. what to monitor
- Avoid generic advice ("reduce costs") — anchor to the actual driver ("renegotiate the shipping contract driving the 12% logistics overage")
Step 6: Write the Executive Narrative
Assemble the findings into prose calibrated to the audience.
- Lead with the single most important takeaway in one sentence
- Follow the "what happened → why → what it means → what we recommend" arc
- Translate finance terminology for non-finance readers when the audience requires it
- Keep numbers in the narrative to the ones that matter; push detail to the supporting bullets
Output Format
- Structure: Executive summary paragraph, then labeled sections for drivers, trends, risks/opportunities, and recommendations
- Length: 700–1,000 words
- Format: Narrative prose for the summary; structured bullets and a compact variance table for the analytical sections
- Sections: Executive Summary → Headline Results (variance table) → Variance Drivers → Trend Signals → Ranked Risks & Opportunities → Recommended Actions
- Tone: FP&A business partner — precise, plain-spoken, confident about causes when the data supports them and explicit about hypotheses when it doesn't; zero jargon padding
Quality Checklist
Before delivering output, verify:
- [ ] Every material variance is decomposed into at least one named driver — not left as a raw number
- [ ] Variances are labeled favorable/unfavorable using business logic, not arithmetic sign
- [ ] The variance table shows actual, comparison, absolute variance, and percentage for each focus metric
- [ ] Each recommended action names the specific driver it addresses and the metric it moves
- [ ] Risks and opportunities are ranked, not listed in arbitrary order
- [ ] Uncertain causes are flagged as hypotheses rather than stated as established facts
- [ ] The executive summary leads with one clear headline takeaway
Notes
- The value of this skill is causation, not description — a summary that only restates the numbers has failed
- When the data lacks the granularity to decompose a variance (e.g., no volume/price split available), state the limitation and give the most likely driver as a labeled hypothesis rather than guessing silently
- Calibrate depth to audience: a board summary favors the takeaway and top three actions; a CFO review can carry the full driver decomposition
- One-time items should always be isolated so stakeholders can see the true underlying run-rate
- If the decision at hand is provided, ensure at least one recommendation directly informs that decision
How to use this skill
This file is a Claude Code skill in Anthropic's standard format — markdown with YAML frontmatter at the top.
Installing in Claude Code:
~/.claude/skills/<folder-name>/SKILL.md— auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)<your-project>/.claude/skills/<folder-name>/SKILL.md— auto-loads only when working in that project (recommended for project-specific skills)
Restart Claude Code or open a new session to register.
Using in Claude.ai, ChatGPT, Gemini, or other AI tools:
- Drag this file into a new chat, or copy and paste its contents
- Send your task or request as your next message — the AI will apply the skill where it fits
For Claude Code skill details: https://docs.anthropic.com/en/docs/claude-code/skills