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From financial-analysis
Reviews pitch decks and client presentations for number consistency, data-narrative alignment, language polish, and visual formatting QC. Use when checking, proofing, or doing a final pass on investment banking materials.
npx claudepluginhub anthropics/financial-services --plugin financial-analysisHow this skill is triggered — by the user, by Claude, or both
Slash command
/financial-analysis:ib-check-deckThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Perform comprehensive QC on the presentation across four dimensions. Read every slide, then report findings.
Reviews pitch decks and client presentations for number consistency, data-narrative alignment, language polish, and visual formatting QC. Use when checking, proofing, or doing a final pass on investment banking materials.
Audits PowerPoint decks for layout bugs, design inconsistencies, accessibility issues, AI-generation tells, and silent generator failures. Run after creating presentations or when reviewing uploaded .pptx files.
Audits PowerPoint presentations for layout issues, text overflow, visual hierarchy problems, and consistency gaps. Produces a slide-by-slide report with ranked issues and fixes.
Share bugs, ideas, or general feedback.
Perform comprehensive QC on the presentation across four dimensions. Read every slide, then report findings.
This skill works in both the PowerPoint add-in and chat. Identify which you're in before starting:
.pptx file.This is read-and-report only — no edits — so the workflow is identical in both.
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]
Run the extraction script on what you collected:
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:
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.
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.
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.
Use references/report-format.md as the structure. Categorize by severity:
Lead with criticals. If there aren't any, say so explicitly — "no number inconsistencies found" is a finding, not an absence of one.