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Initial commit: IB Deck Engine Claude Code plugin
A Claude Code plugin that ships a 14-template investment banking slide library with a JSON spec → deterministic pixel rendering architecture. Includes: - 7 slash commands: /ib-deck, /ib-extract, /ib-financial, /ib-football, /ib-comps, /ib-sources-uses, /ib-sensitivity - Master skill (SKILL.md) with template catalog and workflow rules - Bundled Python library (IBRenderer) with 14 templates - Reference docs: template catalog, JSON schemas, working examples - Plugin manifest and marketplace.json for installation Solves four critical failure modes that exist in the financial-services-plugins: 1. Cross-model desync (DCF vs LBO inconsistency) — single source of truth JSON 2. openpyxl corruption (Excel recovery dialogs) — defaults to xlsxwriter 3. Spatial execution failures (right-alignment, proportional bars) — JSON spec architecture 4. Generic titles — SKILL.md enforces action titles Companion to standalone library at github.com/gorajing/ib-deck-engine.
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‎.claude-plugin/marketplace.json‎

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{
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"name": "ib-deck-plugin",
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"owner": {
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"name": "gorajing"
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},
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"metadata": {
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"description": "Investment banking slide template library for Claude Code. JSON spec → deterministic pixel rendering. Solves cross-model desync, openpyxl corruption, and spatial execution failures.",
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"version": "0.1.0"
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},
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"plugins": [
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{
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"name": "ib-deck-engine",
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"source": ".",
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"description": "14-template IB slide library. Build pitch decks, football fields, financial summaries, sensitivity grids, sources & uses, trading comps via /ib-deck and friends.",
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"category": "investment-banking",
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"tags": ["investment-banking", "powerpoint", "financial-models", "dcf", "lbo", "templates"]
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}
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]
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}

‎.claude-plugin/plugin.json‎

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{
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"name": "ib-deck-engine",
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"version": "0.1.0",
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"description": "Investment banking slide template library with JSON spec → deterministic pixel rendering. Solves cross-model desync, openpyxl corruption, and spatial execution failures by separating content reasoning from layout execution.",
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"author": {
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"name": "gorajing"
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}
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}

‎.gitignore‎

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__pycache__/
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*.py[cod]
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*.so
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.DS_Store
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.idea/
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.vscode/
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*.swp
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venv/
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env/
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.venv/
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*.tmp
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.cache/

‎LICENSE‎

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MIT License
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Copyright (c) 2026 IB Deck Engine contributors
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎README.md‎

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# IB Deck Engine — Claude Code Plugin
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> A Claude Code plugin that ships a 14-template investment banking slide library with a JSON spec → deterministic pixel rendering architecture.
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**Why this exists:** Other AI slide tools ask the LLM to write spatial code (`Inches(2.5), Pt(11)`). That's why their output has misaligned tables, disproportional bar charts, and reference label collisions. This plugin separates content reasoning (LLM's strength) from spatial rendering (deterministic code's strength). Right-alignment is guaranteed by the template, not hoped for.
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## Installation
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```bash
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claude plugin marketplace add gorajing/ib-deck-plugin
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claude plugin install ib-deck-engine@ib-deck-plugin
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```
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Or install directly:
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```bash
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git clone https://github.com/gorajing/ib-deck-plugin ~/.claude/plugins/local/ib-deck-plugin
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```
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Verify installation:
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```bash
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claude plugin list | grep ib-deck
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```
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## Available commands
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| Command | Purpose |
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|---------|---------|
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| `/ib-deck [TICKER]` | Build a complete 14-slide IB pitch deck for a public company |
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| `/ib-extract [TICKER]` | Pull a 10-K from SEC EDGAR into a structured JSON master file |
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| `/ib-financial [COMPANY]` | Build a single financial summary table slide |
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| `/ib-football [COMPANY]` | Build a football field valuation summary slide |
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| `/ib-comps [TARGET]` | Build a trading comparables peer multiples table |
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| `/ib-sources-uses [DEAL]` | Build an LBO Sources & Uses table |
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| `/ib-sensitivity [COMPANY]` | Build a DCF sensitivity grid (WACC × TGR) |
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## Quick start
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```bash
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# In Claude Code, after installing the plugin:
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/ib-deck ADUS
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```
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Claude will:
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1. Pull Addus HomeCare's most recent 10-K from SEC EDGAR via `edgartools`
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2. Extract financials into a structured JSON master file
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3. Fill JSON specs for 14 slide templates
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4. Render a pixel-perfect PPTX using the IBRenderer
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5. Save to `ADUS_pitch_deck.pptx`
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The entire pipeline takes one prompt.
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## What this plugin solves that the existing financial-services-plugins doesn't
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I built this after analyzing the source code of `anthropics/financial-services-plugins`. Here are the specific gaps it fills:
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### 1. Cross-model desync ✗ → ✓
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The existing plugins build DCF and LBO independently. There's nothing guaranteeing both use the same revenue, EBITDA, share count, or tax rate. In a Medpace case study, the DCF used 15% effective tax and the LBO used 21% statutory with no documentation.
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**This plugin's fix:** `/ib-extract` produces a single master JSON. Every downstream model and slide references it. A `cross_audit` function verifies consistency across DCF, LBO, and slides.
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### 2. openpyxl corruption ✗ → ✓
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The existing DCF skill (line 21) defaults to openpyxl for standalone xlsx generation. This produces files that trigger Excel's "We found a problem" recovery dialog.
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**This plugin's fix:** Uses `xlsxwriter` by default for new file creation. openpyxl is only for reading existing files.
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### 3. Spatial execution ceiling ✗ → ✓
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The existing skills tell the LLM to write `python-pptx` code directly. The LLM has to remember `Inches(2.5), Pt(11)` for every cell. Failures: right-alignment inconsistent, bar heights not proportional, reference labels overlapping titles.
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**This plugin's fix:** The LLM never writes spatial code. It picks a template (`render_financial_summary`) and fills a JSON spec. The IBRenderer guarantees:
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- Right-alignment on all numeric columns
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- Proportional bar heights (`value / max_value × chart_height`)
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- Tables are real PowerPoint table objects (not text with tabs)
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- Reference labels never overlap (collision detection built-in)
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- Source text dynamically positioned below content
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### 4. Generic titles ✗ → ✓
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The existing plugins don't enforce action titles. You get "Financial Summary" instead of "Consistent Revenue Growth With Expanding EBITDA Margin Expansion".
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**This plugin's fix:** SKILL.md explicitly requires action titles on every slide and gives examples.
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### 5. No template library ✗ → ✓
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The existing plugins make Claude generate slides from scratch each time. No reusable patterns.
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**This plugin's fix:** 14 pre-built templates for the most common IB slide types, each with a documented JSON schema.
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## The 14 templates
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| # | Template | Pattern | Reference |
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|---|----------|---------|-----------|
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| 1 | `render_cover` | Cover with confidential mark + bank badge | GS board pres format |
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| 2 | `render_section_divider` | Full navy bg with section title | GS / Moelis style |
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| 3 | `render_toc` | Numbered agenda with light blue bands | GS agenda slides |
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| 4 | `render_exec_summary` | Blue callout + ■ / — bullet hierarchy | GS executive summary |
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| 5 | `render_investment_highlights` | 4-card 2×2 grid with numbered headers | GS / GS analyst format |
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| 6 | `render_financial_summary` | Historical P&L with bold subtotals | Standard IB financials |
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| 7 | `render_stacked_bar_table` | Stacked bars + data table below | Moelis revenue by segment |
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| 8 | `render_dual_chart` | Two bar charts side by side with CAGR | GS dual analysis |
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| 9 | `render_football_field` | Valuation methodologies with range bars | Evercore / Moelis |
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| 10 | `render_sensitivity` | WACC × TGR grid with base case highlight | Standard DCF sensitivity |
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| 11 | `render_sources_uses` | LBO capital structure (two-column) | Standard LBO |
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| 12 | `render_trading_comps` | Peer multiples with target highlighted | Standard comps table |
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See `skills/ib-deck-engine/reference/template-catalog.md` for the full pattern catalog and JSON schemas.
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## Architecture
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```
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┌─────────────────────────────────────┐
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│ CONTENT REASONING (Claude) │
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│ │
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│ - Pick the right template │
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│ - Write the action title │
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│ - Select the data │
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│ - Cite the source │
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└────────────────┬────────────────────┘
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│
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│ Output: structured JSON
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│
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▼
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┌─────────────────────────────────────┐
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│ JSON SPEC │
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│ { │
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│ "title": "...", │
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│ "headers": [...], │
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│ "rows": [...] │
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│ } │
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└────────────────┬────────────────────┘
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│
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│ Pure data, no coordinates
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│
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▼
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┌─────────────────────────────────────┐
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│ DETERMINISTIC RENDERER │
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│ - Right-alignment ALWAYS │
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│ - Proportional bars by math │
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│ - Real table objects │
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│ - Pixel-perfect by construction │
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└────────────────┬────────────────────┘
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│
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▼
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output.pptx
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```
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This is the same architecture used by Beautiful.ai, Gamma, Pitch, UpSlide, and Macabacus. The LLM never touches pixels.
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## Companion repo
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The standalone Python library (without the plugin packaging) is at:
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**https://github.com/gorajing/ib-deck-engine**
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It includes a complete worked example for Addus HomeCare Corp (ADUS) — DCF model, LBO model, master JSON, and rendered 14-slide deck.
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## Disclaimer
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This is a learning case study and template library. Models are simplified. Numbers in the example case study are illustrative. Always verify financial data against primary sources before relying on it for investment decisions.
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## License
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MIT — see [LICENSE](LICENSE).

‎commands/ib-comps.md‎

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---
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description: Build a trading comparables (peer multiples) table slide
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argument-hint: "[target company]"
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---
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# IB Trading Comps
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Build a trading comparables table showing peer companies' valuation multiples with the
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target company highlighted. Uses the `render_trading_comps` template.
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Load the `ib-deck-engine` skill and use `render_trading_comps`.
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## What this slide shows
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A peer comparables table with:
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- 5-10 peer companies in the same sector as the target
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- Standard multiples: Market Cap, EV, Revenue, EBITDA, EV/Rev, EV/EBITDA, Growth
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- Target company highlighted with yellow background
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- Mean and Median summary rows in light gray
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- Right-aligned numeric columns
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- Source line at bottom
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## Workflow
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If a target company is provided as $1, ask:
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- "Which peer companies should I include?" (or suggest based on sector)
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- "Which financial metrics?" (default: Market Cap, EV, Rev, EBITDA, EV/Rev, EV/EBITDA, Growth)
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- "What's the source for the data?" (FactSet, Capital IQ, Bloomberg)
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## Critical rules
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- **Action title** — "[Target] Trades at a Discount/Premium to Sector Peers Despite [Differentiation]"
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- **Target row highlighted** — set `"target_row": 0` (zero-indexed) to highlight in yellow
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- **Summary rows** — use `"summary": True` for Mean/Median rows (gray background, bold)
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- **Right-aligned numbers** — automatic, don't override
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- **Source citation** — always include date: "Source: FactSet. Market data as of April 2026."
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## Example spec
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```python
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r.render_trading_comps({
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"title": "Addus Trades at a Discount to Home Care Services Peers Despite Superior Growth and Margins",
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"header_text": "Selected Home Care Services Trading Comparables",
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"headers": ["Company", "Ticker", "Market Cap ($M)", "EV ($M)", "Rev ($M)", "EBITDA ($M)", "EV/Rev", "EV/EBITDA", "Rev Growth"],
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"rows": [
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{"company": "Addus HomeCare", "values": ["ADUS", "1,781", "1,820", "1,565", "175", "1.2x", "10.4x", "10.0%"]},
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{"company": "BrightSpring", "values": ["BTSG", "5,820", "8,400", "11,200", "530", "0.8x", "15.8x", "12.5%"]},
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{"company": "Pennant Group", "values": ["PNTG", "3,940", "4,200", "765", "82", "5.5x", "51.2x", "18.2%"]},
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{"company": "Mean", "values": ["", "", "", "", "", "1.8x", "18.5x", "8.9%"], "summary": True},
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{"company": "Median", "values": ["", "", "", "", "", "1.1x", "12.7x", "8.4%"], "summary": True},
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],
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"target_row": 0,
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"source": "Source: FactSet, Capital IQ. Market data as of April 2026."
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})
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```

‎commands/ib-deck.md‎

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---
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description: Build a complete investment banking pitch deck for a public company
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argument-hint: "[company ticker or name]"
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---
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# IB Deck — Full Pitch Book
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Build a complete 14-slide IB pitch deck for the specified company using the IB Deck Engine
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template library. The architecture: extract data → fill JSON specs → deterministic rendering.
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## Workflow
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Load the `ib-deck-engine` skill to access the template library and follow this workflow:
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### Step 1: Confirm the deal
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If a company name/ticker is provided as $1, use it. Otherwise ask:
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- "What company would you like to build a pitch deck for?"
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- "Sell-side or buy-side mandate?"
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- "Any specific assumptions to use (or should I use reasonable defaults)?"
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### Step 2: Extract financial data
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For public US companies, use `edgartools` to pull the most recent 10-K:
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- Revenue, COGS, gross profit, operating income, EBITDA, net income (3 years)
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- Balance sheet (cash, AR, debt, equity)
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- Cash flow statement (CFO, CapEx, financing)
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- Segment revenue if available
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- Diluted share count
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- Save as `{ticker}_master.json` — single source of truth
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### Step 3: Build the 14-slide deck
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Use the IBRenderer templates in this order:
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1. **Cover** (`render_cover`) — Project codename + bank name + date
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2. **Table of Contents** (`render_toc`) — 4 numbered agenda items
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3. **Executive Summary** (`render_exec_summary`) — Blue callout + 3 main points with sub-bullets
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4. **Investment Highlights** (`render_investment_highlights`) — 4-card 2×2 grid
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5. **Section Divider** (`render_section_divider`) — "Review of Financial Performance"
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6. **Financial Summary** (`render_financial_summary`) — Historical P&L with margins
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7. **Revenue by Segment** (`render_stacked_bar_table`) — Stacked bars + data table
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8. **Revenue + EBITDA** (`render_dual_chart`) — Side-by-side bar charts with CAGR
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9. **Section Divider** (`render_section_divider`) — "Preliminary Valuation Analysis"
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10. **Football Field** (`render_football_field`) — Valuation methodologies with range bars
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11. **Sensitivity** (`render_sensitivity`) — WACC × Terminal Growth grid
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12. **Trading Comps** (`render_trading_comps`) — Peer multiples table
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13. **Section Divider** (`render_section_divider`) — "LBO Analysis"
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14. **Sources & Uses** (`render_sources_uses`) — Capital structure with balance check
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### Step 4: Verify and deliver
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- Confirm 14 slides generated
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- Verify source text on each content slide
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- Save as `{ticker}_pitch_deck.pptx`
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- Report the file path to the user
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## Critical rules
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- **Action titles only** — never "Financial Summary," always "Consistent Revenue Growth With Expanding Margins"
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- **Every number sourced** — trace each value to a source file or note "Estimated"
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- **Cross-model consistency** — DCF and LBO must use the same revenue, EBITDA, share count
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- **Right-alignment automatic** — handled by templates, don't override
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## Example: ADUS
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```
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/ib-deck ADUS
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```
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Builds a complete 14-slide pitch book for Addus HomeCare Corp using SEC EDGAR data.
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See `skills/ib-deck-engine/reference/examples/full_deck.py` for the full worked example.

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