# Check Deck

QC an investment deck (a .pptx) before it circulates: number consistency, chart and...

- Repository: https://github.com/ginlix-ai/LangAlpha (2232 stars)
- Category: Documents
- License: Apache-2.0
- Last updated: 2026-11-01
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add ginlix-ai/LangAlpha --skill check-deck -g -a claude-code -y`
Codex: `npx skills add ginlix-ai/LangAlpha --skill check-deck -g -a codex -y`
Cursor: `npx skills add ginlix-ai/LangAlpha --skill check-deck -g -a cursor -y`
Gemini CLI: `npx skills add ginlix-ai/LangAlpha --skill check-deck -g -a gemini-cli -y`

## Description

QC an investment deck (a .pptx) before it circulates: number consistency, chart and narrative alignment, source coverage, language, then a circulation verdict. Triggers on check this deck, deck QC, review my presentation, is this ready to send, proofread the pitch book.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Deck Check

QC that ends in a decision. Finding a discrepancy is the easy half; the work is saying what it proves, how confident we are, and whether the deck can go out. Every consequential finding carries a confidence label, and the pass ends in one readiness posture for the whole document.

Evidence labels, source tiers, staleness, the readiness posture and the intake limits: `.agents/skills/research-conventions/SKILL.md`, read before the first finding.

## Step 1: Establish the artifact set and the evidence rules

Name the **controlling artifact** (the deck under review) and list every **supporting artifact** with its role: the model the numbers tie to, the filings behind the market claims, the prior version, the data pulls. A finding's confidence depends on which artifact it came from, so this classification happens before any checking.

The controlling model is the subject under test, and the deck is checked against it: a deck figure that does not match the model is a finding about the deck. Where the model and a source disagree, the sources resolve down the tiers in `.agents/skills/research-conventions/references/evidence.md`, the filing first, then the data tools, then company materials labelled as such, then third-party summaries. Two conflicting sources are never averaged and never silently resolved in favour of the flattering one.

Read the deck out with the `pptx` skill's extractor, which keeps the slide structure the
checks depend on:

```bash
python .agents/skills/pptx/scripts/extract.py presentation.pptx > deck.json
```

The rest: https://github.com/ginlix-ai/LangAlpha/blob/HEAD/plugins/langalpha_research/skills/check-deck/SKILL.md