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ib-check-deck — Claude Code skill: what it does, how to install

A skill that reviews pitch decks for number mismatches across slides, narrative-data gaps, IB language polish, and visual QC.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add anthropics/financial-services --skill ib-check-deck -a claude-code
Open on GitHub

What ib-check-deck does

The skill reads every slide of a deck and checks four things: number consistency across slides, whether narrative claims match the underlying data, language that breaks the investment-banking register, and visual or formatting issues like missing source citations.

For number checking it writes slide text to a file with ## Slide N markers and runs python scripts/extract_numbers.py /tmp/deck_content.md --check, which normalizes units ($500M vs $500MM) and flags slides where the same metric shows conflicting values. Language fixes draw on references/ib-terminology.md, and the final report follows the structure in references/report-format.md.

It's read-and-report only, no edits: in the PowerPoint add-in it reads the live deck, in chat it reads an uploaded .pptx file. Findings are grouped by severity — critical issues block client delivery, important ones should get fixed, minor ones are polish.

What it helps with

  • catch number mismatches across pitch deck slides
  • check that charts and narrative claims line up
  • flag casual phrasing against IB language standards
  • verify source citations, axis labels and formatting consistency
  • produce a severity-ranked QC report before sending a deck to a client

Example prompts for the agent

  • Check my numbers in this pitch deck before I send it to the client
  • Reconcile figures across slides in deck.pptx
  • Do a final pass on this deck and tell me what I'm missing

How to install ib-check-deck

1Skills CLI (Vercel)

npx skills add anthropics/financial-services --skill ib-check-deck -a claude-code

2Manually: put the files in place

~/.claude/skills/ib-check-deck/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/ib-check-deck/

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Questions about ib-check-deck

How do I install ib-check-deck in Claude Code?

Run npx skills add anthropics/financial-services --skill ib-check-deck -a claude-code; the skill then lives at ~/.claude/skills/ib-check-deck/SKILL.md.

What does ib-check-deck do?

It checks a pitch deck across four dimensions: number consistency across slides, data-narrative alignment, language polish against IB standards, and visual or formatting QC, then returns a severity-ranked report.

Does ib-check-deck need Python?

Yes, it runs scripts/extract_numbers.py with Python to normalize units and flag slides where the same metric shows conflicting values.

Source text

SKILL.md · Apache-2.0
---
name: ib-check-deck
description: Investment banking presentation quality checker. Reviews a pitch deck or client-ready presentation for (1) number consistency across slides, (2) data-narrative alignment, (3) language polish against IB standards, (4) visual and formatting QC. Use whenever the user asks to review, check, QC, proof, or do a final pass on a deck, pitch, or client materials — including requests like "check my numbers", "reconcile figures across slides", "is this client-ready", or "what am I missing before I send this out".
---

# IB Deck Checker

Perform comprehensive QC on the presentation across four dimensions. Read every slide, then report findings.

## Environment check

This skill works in both the PowerPoint add-in and chat. Identify which you're in before starting:

- **Add-in** — read from the live open deck.
- **Chat** — read from the uploaded `.pptx` file.

This is read-and-report only — no edits — so the workflow is identical in both.

## Workflow

### Read the deck

Pull text from every slide, keeping track of which slide each line came from. You'll need slide-level attribution for every finding ("$500M appears on slides 3 and 8, but slide 15 shows $485M"). A deck with 30 slides is too much to hold in working memory reliably — write the extracted text to a file so the number-checking script can process it.

The script expects markdown-ish input with slide markers. Format as:

```
## Slide 1
[slide 1 text content]

## Slide 2
[slide 2 text content]
```

### 1. Number consistency

Run the extraction script on what you collected:

```bash
python scripts/extract_numbers.py /tmp/deck_content.md --check
```

It normalizes units ($500M vs $500MM vs $500,000,000 → same number), categorizes values (revenue, EBITDA, multiples, margins), and flags when the same metric category shows conflicting values on different slides. This is the part most likely to catch something a human missed on the fifth read-through.

Beyond what the script flags, verify:
- Calculations are correct (totals sum, percentages add up, growth rates match the endpoints)
- Unit style is consistent — the deck should pick one of $M or $MM and stick with it
- Time periods are aligned — FY vs LTM vs quarterly, explicitly labeled

### 2. Data-narrative alignment

Map claims to the data that's supposed to support them. This is where decks go wrong quietly — someone edits the chart on slide 7 and forgets the narrative on slide 4.

- Trend statements ("declining margins") → does the chart actually go that direction?
- Market position claims ("#1 player") → revenue and share data support it?
- Plausibility — "#1 in a $100B market" with $200M revenue is 0.2% share; that's not #1

### 3. Language polish

IB decks have a register. Scan for anything that breaks it: casual phrasing ("pretty good", "a lot of"), contractions, exclamation points, vague quantifiers without numbers, inconsistent terminology for the same concept.

See `references/ib-terminology.md` for replacement patterns.

### 4. Visual and formatting QC

Run standard visual verification checks on each slide. You're looking for: missing chart source citations, missing axis labels, typography inconsistencies, number formatting drift (1,000 vs 1K within the same deck), date format drift, footnote and disclaimer gaps.

Visual verification catches overlaps, overflow, and contrast issues that don't show up in text extraction. Don't skip it — a chart with no source citation looks the same as a properly sourced one in the text dump.

## Output

Use `references/report-format.md` as the structure. Categorize by severity:

- **Critical** — number mismatches, factual errors, data contradicting narrative. These block client delivery.
- **Important** — language, missing sources, terminology drift. Should fix.
- **Minor** — font sizes, spacing, date formats. Polish.

Lead with criticals. If there aren't any, say so explicitly — "no number inconsistencies found" is a finding, not an absence of one.

© anthropics · Apache-2.0 · anthropics/financial-services

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