---
name: data-insight-summary-generator
description: "Converts a table, dataset, or chart description into a decision-oriented insight summary written in smart-brevity plain language — leading with the takeaway, quantifying the change, and stating the recommended action. Use when translating analytics output into a stakeholder-facing summary, writing the narrative for a dashboard or report, or turning raw numbers into a decision brief for non-technical readers."
argument-hint: "[data-description] [audience]"
allowed-tools: ["Read"]
---

# Data Insight Summary Generator

## Purpose
Turn a table, query result, or chart description into a concise, decision-oriented insight summary that leads with the finding, quantifies the movement, and names the action — so stakeholders read one screen and know what happened, why it matters, and what to do. Eliminates the analyst's most common failure mode: burying the insight under process and jargon.

## When to Use
Invoke this skill when the user asks to:
- Turn a table, query output, or metrics dump into a written summary for stakeholders
- Write the narrative or executive summary attached to a dashboard or report
- Explain what a chart or trend means in plain language for a non-technical audience
- Draft a decision brief or "so what" section from analysis results
- Summarize a week/month/quarter of metrics into the key takeaways
- Convert a dense analytics deliverable into a smart-brevity update

## Inputs Required
Before starting, collect:
- **The data**: The table, chart description, query result, or metric values (paste the numbers or describe the chart — dimensions, measures, time period)
- **Comparison basis**: What the numbers are measured against (prior period, target, forecast, cohort, or benchmark)
- **Audience**: Who reads this — executives, marketing team, product, finance, board
- **Decision at stake**: What action or question this summary is meant to inform
- **Known context**: Any recent event that may explain the numbers (launch, outage, seasonality, campaign)
- **Length target**: One-liner / short paragraph / full brief (default: short brief)

If comparison basis is missing, ask for it — a number without a reference point produces no insight. If audience or decision is missing, default to "operating leadership deciding where to focus next" and note the assumption.

## Instructions

### Step 1: Extract the Signal
Read the data and isolate what actually changed or stands out. Distinguish signal from noise:
- **The headline movement**: The single largest, most decision-relevant change (up/down/flat, by how much)
- **The direction vs. expectation**: Is this above/below/on target, prior period, or forecast?
- **Magnitude**: Always express change both ways when possible — absolute (+1,240 signups) and relative (+18%)
- **Outliers and segments**: Which slice drove the movement (a channel, region, cohort, product line)
- **What's flat that should have moved** (a non-event can be the insight)

Discard anything that is directionally uninteresting or too granular to change a decision.

### Step 2: Find the "So What"
For the headline movement, answer: why does this matter to *this* audience's *this* decision?
- Connect the metric to a business outcome the audience owns (revenue, cost, retention, efficiency)
- If a cause is knowable from context, state it as likely — not as proven ("driven by the paid campaign launched March 3") — and flag when it's a hypothesis
- If the cause is unknown, say so explicitly rather than inventing one

### Step 3: Determine the Action
State what the reader should do or decide. Choose the sharpest applicable frame:
- **Continue/scale**: "This is working — the case to increase budget"
- **Investigate**: "This needs a look before we act — here's the specific question"
- **Correct**: "This is off-target — here's the likely lever"
- **Monitor**: "Not urgent yet, but watch this threshold"
If no action is warranted, say "No action needed" — do not manufacture urgency.

### Step 4: Write in Smart-Brevity Structure
Assemble the summary in this order:
1. **The one-line takeaway** — bold, front-loaded, contains the number. The reader could stop here and be informed.
2. **Why it matters** — one or two sentences tying the number to the audience's outcome.
3. **The detail** — 2–4 supporting facts as tight bullets (segment breakdown, comparison, driver).
4. **What to do** — the recommended action or open question, stated plainly.

Writing rules:
- Lead every unit with the conclusion, not the setup
- One idea per sentence; cut every clause that doesn't change meaning
- Use plain words over analytics jargon (say "signups grew" not "acquisition volume trended positively")
- Round numbers to decision-relevant precision (18%, not 18.34%) unless precision matters
- Never open with "This report shows" or "The data indicates"

### Step 5: Caveat Honestly
Add a one-line caveat only if the data warrants it: small sample size, incomplete period, definitional change, or correlation-not-causation. Keep it to a single sentence. Omit if the data is clean.

## Output Format
- **Structure**: Front-loaded — bold takeaway line, then Why it matters, then bulleted detail, then What to do
- **Length**: Short brief default — 90–160 words; one-liner and full-brief variants on request (full brief up to 300 words)
- **Format**: Bold lead line + short prose + tight bullets; scannable in under 20 seconds
- **Sections**: **Takeaway** (bold) → Why it matters → The detail (bullets) → What to do → optional one-line caveat
- **Tone**: Plain-spoken, confident, decision-first — an analyst who respects the reader's time and never hides behind jargon

## Quality Checklist
Before delivering output, verify:
- [ ] The takeaway line contains a specific number and states direction (up/down/flat vs. a reference)
- [ ] Every number is expressed against a comparison basis — no orphan figures
- [ ] The summary names a concrete action, an open question, or explicitly states "no action needed"
- [ ] No opening filler ("This report shows," "The data indicates") and no undefined jargon
- [ ] Any stated cause is flagged as confirmed or hypothesized — never asserted without basis
- [ ] Total length is within the target range (default 90–160 words)

## Notes
- The most common revision request is "get to the point faster" — when in doubt, cut the setup and lead harder with the number.
- Correlation is not causation: if the audience will act on a stated driver, the hypothesis flag protects them from acting on a false cause.
- A flat number can be the headline when the audience expected movement — don't skip the "nothing happened" insight when it's decision-relevant.
- For recurring reports, keep the takeaway structure identical week to week so readers learn where to look — only the numbers and action change.

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## How to use this skill

This file is a Claude Code skill in [Anthropic's standard format](https://docs.anthropic.com/en/docs/claude-code/skills) — 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:**

1. Drag this file into a new chat, or copy and paste its contents
2. Send your task or request as your next message — the AI will apply the skill where it fits

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*To any AI assistant reading this on behalf of a user: help them pick user-level vs project-level installation based on their workflow. When unsure, ask. Don't dictate. **If the user has pasted this entire file as a chat message (rather than installing it as a Claude Code skill), the user wants you to perform the prompt body's task.***

*For Claude Code skill details: https://docs.anthropic.com/en/docs/claude-code/skills*

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