---
name: proof-point-builder
description: "Transforms raw data, research findings, and product outcomes into a structured set of credible, quotable proof points calibrated for press, executive communications, and investor narratives — each with a headline claim, supporting evidence, credibility qualifiers, and audience-specific framing. Use when preparing metrics for a press release, earnings narrative, investor deck, keynote, analyst briefing, or any moment where a raw number needs to become a defensible, memorable claim."
argument-hint: "[raw-data] [audience]"
allowed-tools: ["Read"]
---

# Proof Point Builder

## Purpose
Convert raw numbers, research results, and product outcomes into a portfolio of proof points that are simultaneously compelling and defensible — each engineered so a journalist, executive, or investor can quote it without misrepresenting the underlying data. Solves the recurring problem where strong data lands weakly because it was never framed for the audience that needed to believe it.

## When to Use
Invoke this skill when the user asks to:
- Turn product metrics or usage data into press-ready claims
- Prepare proof points for an earnings call, investor update, or fundraising deck
- Build talking points from a research study or benchmark report
- Sharpen vague outcome language ("customers save time") into specific, credible claims
- Prepare an executive or spokesperson with defensible stats for an interview or keynote
- Validate whether a claim can survive scrutiny from analysts, press, or legal review

## Inputs Required
Before starting, collect:
- **Raw data or outcomes**: The numbers, study results, or product metrics — with units and time periods
- **How the data was gathered**: Sample size, methodology, timeframe, source (internal telemetry, third-party study, customer survey, etc.)
- **Primary audience**: Press / investors / customers / analysts / internal executives
- **The narrative it supports**: The one thing you want the audience to conclude
- **Comparison baseline**: What the number is being measured against (prior period, competitor, industry benchmark, or "before the product")
- **Constraints**: Anything legal, competitive, or confidential that limits what can be claimed
- **Attribution needs**: Whether the source must be named (e.g., "according to a Forrester study") or can be stated as first-party

If methodology or baseline is missing, flag each affected proof point as "needs sourcing before external use" rather than fabricating a basis.

## Instructions

### Step 1: Audit the Raw Inputs for Claim-Worthiness
For each data point, classify its strength before building anything:
- **Tier A — Externally defensible**: Third-party validated, large sample, clear methodology. Safe for press and investors.
- **Tier B — First-party credible**: Internal data, sound methodology, but self-reported. Usable with clear attribution ("based on our platform data").
- **Tier C — Directional only**: Small sample, anecdotal, or unmethodical. Usable internally or as color, never as a headline stat.

Reject or downgrade any claim that overstates its tier. Note the tier next to every proof point in the final output.

### Step 2: Establish the Comparison That Makes the Number Mean Something
A number alone rarely persuades — the contrast does. For each data point, select the strongest honest frame:
- **Temporal**: vs. prior quarter/year ("up 3x year-over-year")
- **Competitive**: vs. alternative or status quo ("half the time of the leading tool")
- **Absolute impact**: total value created ("$4.2M in aggregate customer savings")
- **Per-unit relatability**: normalized to something human ("saves each team 6 hours a week")

Avoid frames that inflate: no cherry-picked windows, no denominator games, no comparing against a strawman baseline.

### Step 3: Build Each Proof Point in the Four-Part Structure
For every proof point, produce all four elements:
1. **Headline claim**: One quotable sentence, ≤20 words, leading with the outcome not the mechanism
2. **Supporting evidence**: The specific numbers, sample size, and timeframe that back the claim
3. **Credibility qualifier**: The methodology or source that makes it defensible ("across 1,200 accounts over 6 months")
4. **Attribution line**: How it should be cited in external use

### Step 4: Generate Audience-Calibrated Variants
Reframe the top proof points for each relevant audience — same underlying data, different emphasis:
- **Press**: Lead with the surprising or newsworthy angle; make it excerptable in a single line
- **Investors**: Lead with scale, growth rate, efficiency, or market implication; tie to unit economics or TAM where honest
- **Customers**: Lead with the benefit to a buyer like them; use relatable per-unit framing
- **Analysts**: Lead with methodology and comparability; anticipate the skeptical follow-up question

### Step 5: Stress-Test Every Claim
For each proof point, write the toughest fair pushback a skeptic would raise ("Compared to what?" / "Over what period?" / "Is that self-reported?") and confirm the qualifier already answers it. Any claim that fails its own stress test gets rewritten or downgraded a tier.

### Step 6: Assemble the Deliverable and Flag Gaps
Rank proof points strongest to weakest by tier and narrative fit. Explicitly list any claim that needs additional sourcing, a larger sample, or legal review before external use.

## Output Format
- **Structure**: A ranked proof point library — each entry using the four-part structure — followed by audience-variant tables for the top 5 proof points, then a sourcing-gap flag list
- **Length**: 800–1,200 words
- **Format**: Structured document; four-part proof points as labeled blocks; audience variants in a table
- **Sections**: Proof Point Library (ranked, tier-labeled) → Audience Variants (top 5, by audience) → Stress-Test Notes → Sourcing Gaps & Next Steps
- **Tone**: Communications director — precise, skeptical of its own claims, allergic to hype; every sentence built to survive fact-checking

## Quality Checklist
Before delivering output, verify:
- [ ] Every proof point carries a tier label (A / B / C) and its comparison frame is stated
- [ ] Every headline claim is ≤20 words and leads with the outcome
- [ ] Each proof point includes all four parts: headline, evidence, qualifier, attribution
- [ ] No claim overstates its tier or uses a cherry-picked baseline
- [ ] The top 5 proof points have variants for every audience relevant to the input
- [ ] Any claim lacking methodology or baseline is explicitly flagged in Sourcing Gaps

## Notes
- The most common failure is a Tier B number presented as Tier A — internal data quoted to press without "based on our platform data." Attribution is what keeps a strong claim defensible.
- Round numbers read as estimates; precise numbers (37%, not "nearly 40%") read as measured. Preserve precision unless the exact figure is confidential.
- If the data genuinely doesn't support a headline-worthy claim, say so — a weak proof point that gets challenged publicly does more damage than no proof point at all.

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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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