Ib Check Deck

anthropics/financial-services/plugins/agent-plugins/pitch-agent/skills/ib-check-deck

作者 anthropics574ed3624aeb无许可证39K 个星标收录于 2026年10月8日更新于 2026年10月8日仓库2周前更新

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".

AI 生成的概览

审查投资银行演示文稿的数字一致性、数据与叙述匹配、语言润色及视觉格式质量。

功能
对 PowerPoint 演示文稿进行只读质量检查,涵盖四个维度:跨幻灯片数字一致性、叙述主张与支撑数据的匹配、符合投资银行语体的语言润色,以及视觉与格式 QC。它会提取幻灯片文本,运行数字提取脚本以统一单位并标记相互冲突的指标数值,并按严重程度(Critical、Important、Minor)依据既定报告结构输出发现。它只生成发现报告,不修改演示文稿。
适用场景
当用户要求审查、检查、QC、校对或对推介演示文稿或客户就绪材料做最终检查时使用,包括要求核对跨幻灯片数字或评估材料是否达到客户交付标准。
运行要求
可在 PowerPoint 加载项中运行,也可在聊天中处理上传的 .pptx 文件。需要 Python 运行时以执行 scripts/extract_numbers.py,并需要参考文件 references/ib-terminology.md 与 references/report-format.md。仅读取并报告;未说明需要凭据或网络访问。

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.

来源与署名

来源:anthropics/financial-services位于plugins/agent-plugins/pitch-agent/skills/ib-check-deck提交574ed36

许可证: 无许可证

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