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ib-check-deckib 检查甲板

Agent Skill

ib-check-deck 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

8,850

周安装

358

GitHub Stars

7,792

下载量

2,778
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ib-check-deck(ib 检查甲板)
来源仓库:https://github.com/anthropics/financial-services-plugins
仓库路径:skills/ib-check-deck
安装命令:
npx skills add https://github.com/anthropics/financial-services-plugins --skill ib-check-deck
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/anthropics/financial-services-plugins --skill ib-check-deck

简介

ib-check-deck 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词快速定位候选结果。
  • 通过 npx skills add 命令从指定仓库安装并使用。
  • 安装前需确认权限范围、维护状态及是否触发联网或文件操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

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:

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.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.71%
按下载量换算992

Claude

27.77%
按下载量换算771

Cursor

18.19%
按下载量换算505

Gemini CLI

9.49%
按下载量换算264

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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