{"kind":"Skill","metadata":{"namespace":"community","name":"ib-check-deck","version":"0.1.0"},"spec":{"description":"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\".","files":{"SKILL.md":"---\nname: ib-check-deck\ndescription: 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\".\n---\n\n# IB Deck Checker\n\nPerform comprehensive QC on the presentation across four dimensions. Read every slide, then report findings.\n\n## Environment check\n\nThis skill works in both the PowerPoint add-in and chat. Identify which you're in before starting:\n\n- **Add-in** — read from the live open deck.\n- **Chat** — read from the uploaded `.pptx` file.\n\nThis is read-and-report only — no edits — so the workflow is identical in both.\n\n## Workflow\n\n### Read the deck\n\nPull 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.\n\nThe script expects markdown-ish input with slide markers. Format as:\n\n```\n## Slide 1\n[slide 1 text content]\n\n## Slide 2\n[slide 2 text content]\n```\n\n### 1. Number consistency\n\nRun the extraction script on what you collected:\n\n```bash\npython scripts/extract_numbers.py /tmp/deck_content.md --check\n```\n\nIt 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.\n\nBeyond what the script flags, verify:\n- Calculations are correct (totals sum, percentages add up, growth rates match the endpoints)\n- Unit style is consistent — the deck should pick one of $M or $MM and stick with it\n- Time periods are aligned — FY vs LTM vs quarterly, explicitly labeled\n\n### 2. Data-narrative alignment\n\nMap 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.\n\n- Trend statements (\"declining margins\") → does the chart actually go that direction?\n- Market position claims (\"#1 player\") → revenue and share data support it?\n- Plausibility — \"#1 in a $100B market\" with $200M revenue is 0.2% share; that's not #1\n\n### 3. Language polish\n\nIB 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.\n\nSee `references/ib-terminology.md` for replacement patterns.\n\n### 4. Visual and formatting QC\n\nRun 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.\n\nVisual 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.\n\n## Output\n\nUse `references/report-format.md` as the structure. Categorize by severity:\n\n- **Critical** — number mismatches, factual errors, data contradicting narrative. These block client delivery.\n- **Important** — language, missing sources, terminology drift. Should fix.\n- **Minor** — font sizes, spacing, date formats. Polish.\n\nLead with criticals. If there aren't any, say so explicitly — \"no number inconsistencies found\" is a finding, not an absence of one.\n","references/ib-terminology.md":"# IB Terminology Reference\n\n## Casual to Professional Replacements\n\n| Casual/Informal | IB Standard |\n|-----------------|-------------|\n| \"a lot of growth\" | \"significant growth\" or \"X% growth\" |\n| \"pretty good margins\" | \"attractive margins\" or \"margins of X%\" |\n| \"they bought the company\" | \"the company was acquired\" |\n| \"big deal\" | \"transformative transaction\" |\n| \"cheap valuation\" | \"attractive valuation\" or \"valuation discount\" |\n| \"expensive\" | \"premium valuation\" |\n| \"make more money\" | \"enhance profitability\" or \"drive margin expansion\" |\n| \"getting bigger\" | \"pursuing growth\" or \"expanding operations\" |\n| \"cut costs\" | \"implement cost optimization\" or \"drive operational efficiencies\" |\n| \"good fit\" | \"strategic fit\" or \"compelling strategic rationale\" |\n| \"help with\" | \"support\" or \"facilitate\" |\n| \"a bunch of\" | \"multiple\" or \"numerous\" |\n| \"kind of\" / \"sort of\" | [remove or be specific] |\n| \"really\" / \"very\" | [remove or quantify] |\n| \"tons of\" | \"substantial\" or quantify |\n| \"huge\" | \"significant\" or quantify |\n| \"pretty much\" | [remove or be precise] |\n| \"basically\" | [remove or clarify] |\n\n## Language Patterns to Avoid\n\n- **Contractions**: Don't → Do not, won't → will not\n- **Exclamation points**: Generally inappropriate for IB materials\n- **First-person**: \"We think...\" → \"Management believes...\" or passive voice\n- **Superlatives without evidence**: \"best-in-class\" requires supporting data\n- **Vague quantifiers**: \"some\", \"many\", \"several\" → specific numbers\n\n## Preferred Phrasing Patterns\n\n**Growth narratives**:\n- \"Demonstrated track record of X% revenue CAGR\"\n- \"Consistent margin expansion over [period]\"\n- \"Proven ability to generate organic growth\"\n\n**Market position**:\n- \"#X player in [specific segment]\"\n- \"Leading provider of [specific offering]\"\n- \"Differentiated positioning through [specific attribute]\"\n\n**Strategic rationale**:\n- \"Compelling strategic fit driven by...\"\n- \"Attractive value creation opportunity through...\"\n- \"Synergy potential of $Xm from [specific sources]\"\n","references/report-format.md":"# Deck Check Report Format\n\n## Report Template\n\n```markdown\n# Deck Check Report: [Presentation Name]\n\n## Summary\n- Total issues: X\n- Critical: X (number mismatches, factual errors)\n- Important: X (narrative-data alignment, language)\n- Minor: X (formatting)\n\n## Critical Issues\n\n### Number Consistency\n1. **[Issue name]** (Slides X, Y)\n   - Slide X: [value]\n   - Slide Y: [value]\n   - Action: [recommendation]\n\n### Data-Narrative Alignment\n1. **[Issue name]** (Slides X, Y)\n   - Claim: \"[quoted text]\"\n   - Data shows: [contradiction]\n   - Action: [recommendation]\n\n## Important Issues\n\n### Language Polish\n1. **[Issue type]** (Slide X)\n   - Current: \"[quoted text]\"\n   - Suggested: \"[replacement]\"\n\n## Minor Issues\n\n### Formatting\n1. **[Issue type]** (Slide X)\n   - [Description and fix]\n\n## Final Checklist\n- [ ] Numbers reconciled\n- [ ] Narrative matches data\n- [ ] Language meets IB standards\n- [ ] Charts sourced\n- [ ] Formatting consistent\n```\n\n## Issue Severity Classification\n\n**Critical** (must fix before client delivery):\n- Number mismatches across slides\n- Calculation errors\n- Factual inaccuracies (names, titles, dates)\n- Data contradicting narrative\n\n**Important** (should fix):\n- Casual/informal language\n- Vague claims without specificity\n- Terminology inconsistency\n- Missing chart sources\n\n**Minor** (polish items):\n- Font/color inconsistencies\n- Date format variations\n- Spacing/alignment issues\n- Orphaned text\n","scripts/extract_numbers.py":"#!/usr/bin/env python3\n\"\"\"\nExtract numerical values from presentation content for consistency checking.\n\nUsage:\n    python extract_numbers.py presentation-content.md\n    python extract_numbers.py presentation-content.md --output numbers.json\n\nThis script parses markdown-formatted presentation content (from markitdown)\nand extracts all numerical values with their context and slide references.\n\"\"\"\n\nimport argparse\nimport json\nimport re\nimport sys\nfrom collections import defaultdict\nfrom dataclasses import dataclass, asdict\nfrom pathlib import Path\nfrom typing import Optional\n\n\n@dataclass\nclass NumberInstance:\n    \"\"\"A numerical value found in the presentation.\"\"\"\n    value: str           # Original string representation\n    normalized: float    # Normalized numeric value\n    unit: str           # Detected unit (M, B, K, %, bps, x, etc.)\n    slide: int          # Slide number (0 if unknown)\n    context: str        # Surrounding text for context\n    line_number: int    # Line number in source file\n    category: str       # Detected category (revenue, margin, multiple, etc.)\n\n\ndef normalize_number(value_str: str, unit: str) -\u003e float:\n    \"\"\"Convert a number string with unit to a normalized float value.\"\"\"\n    # Remove commas and spaces\n    clean = re.sub(r'[,\\s]', '', value_str)\n\n    try:\n        base_value = float(clean)\n    except ValueError:\n        return 0.0\n\n    # Apply unit multipliers\n    multipliers = {\n        'T': 1e12,\n        'B': 1e9,\n        'bn': 1e9,\n        'billion': 1e9,\n        'M': 1e6,\n        'mm': 1e6,\n        'mn': 1e6,\n        'million': 1e6,\n        'K': 1e3,\n        'k': 1e3,\n        'thousand': 1e3,\n    }\n\n    for unit_key in sorted(multipliers.keys(), key=len, reverse=True):\n        if unit_key.lower() in unit.lower():\n            return base_value * multipliers[unit_key]\n\n    return base_value\n\n\ndef detect_category(context: str, unit: str) -\u003e str:\n    \"\"\"Detect the category of a number based on context and unit.\"\"\"\n    context_lower = context.lower()\n\n    # Revenue-related\n    if any(term in context_lower for term in ['revenue', 'sales', 'top line', 'topline']):\n        return 'revenue'\n\n    # EBITDA-related\n    if 'ebitda' in context_lower:\n        if any(term in context_lower for term in ['margin', '%', 'percent']):\n            return 'ebitda_margin'\n        return 'ebitda'\n\n    # Margin-related\n    if any(term in context_lower for term in ['margin', 'profit']):\n        return 'margin'\n\n    # Growth-related\n    if any(term in context_lower for term in ['growth', 'cagr', 'yoy', 'y/y']):\n        return 'growth'\n\n    # Valuation multiples\n    if any(term in context_lower for term in ['multiple', 'ev/', 'p/e', 'ev/ebitda', 'ev/revenue']):\n        return 'multiple'\n\n    # Enterprise value / market cap\n    if any(term in context_lower for term in ['enterprise value', 'ev ', 'market cap']):\n        return 'valuation'\n\n    # Percentage (generic)\n    if unit in ['%', 'bps', 'percent']:\n        return 'percentage'\n\n    # Multiple indicator\n    if unit == 'x':\n        return 'multiple'\n\n    return 'other'\n\n\ndef extract_numbers(content: str) -\u003e list[NumberInstance]:\n    \"\"\"Extract all numbers from presentation content.\"\"\"\n    numbers = []\n    current_slide = 0\n\n    # Pattern for slide markers (from markitdown format)\n    slide_pattern = re.compile(r'^#+\\s*Slide\\s*(\\d+)|^\u003c!-- Slide (\\d+)')\n\n    # Pattern for numbers with various formats\n    # Matches: $500M, 500M, $500 million, 25%, 25.5%, 2.5x, 150bps, $1,234.56, etc.\n    number_pattern = re.compile(\n        r'(?P\u003ccurrency\u003e[$€£¥])?'  # Optional currency symbol\n        r'(?P\u003cnumber\u003e[\\d,]+(?:\\.\\d+)?)'  # The number itself\n        r'\\s*'\n        r'(?P\u003cunit\u003e%|bps|x|'  # Common units\n        r'[Tt]rillion|[Bb]illion|[Mm]illion|[Tt]housand|'  # Full words\n        r'[TBMKtbmk]n?|mm|MM)?'  # Abbreviations\n        r'(?!\\d)'  # Negative lookahead to avoid partial matches\n    )\n\n    lines = content.split('\\n')\n\n    for line_num, line in enumerate(lines, 1):\n        # Check for slide marker\n        slide_match = slide_pattern.match(line)\n        if slide_match:\n            current_slide = int(slide_match.group(1) or slide_match.group(2))\n            continue\n\n        # Find all numbers in the line\n        for match in number_pattern.finditer(line):\n            value_str = match.group('number')\n            currency = match.group('currency') or ''\n            unit = match.group('unit') or ''\n\n            # Skip very short numbers without context (likely not financial)\n            if len(value_str.replace(',', '').replace('.', '')) \u003c 2 and not unit:\n                continue\n\n            # Skip year-like numbers (1900-2099) unless they have units\n            try:\n                num_val = float(value_str.replace(',', ''))\n                if 1900 \u003c= num_val \u003c= 2099 and not unit and not currency:\n                    continue\n            except ValueError:\n                pass\n\n            # Build full value string\n            full_value = f\"{currency}{value_str}{unit}\"\n\n            # Get context (surrounding words)\n            start = max(0, match.start() - 50)\n            end = min(len(line), match.end() + 50)\n            context = line[start:end].strip()\n\n            # Normalize unit\n            if currency:\n                if not unit:\n                    unit = 'USD'  # Assume USD for $ without unit\n                else:\n                    unit = f\"USD_{unit}\"\n\n            normalized = normalize_number(value_str, unit)\n            category = detect_category(context, unit)\n\n            numbers.append(NumberInstance(\n                value=full_value,\n                normalized=normalized,\n                unit=unit or 'none',\n                slide=current_slide,\n                context=context,\n                line_number=line_num,\n                category=category\n            ))\n\n    return numbers\n\n\ndef find_inconsistencies(numbers: list[NumberInstance]) -\u003e list[dict]:\n    \"\"\"Find potential inconsistencies in extracted numbers.\"\"\"\n    inconsistencies = []\n\n    # Group numbers by category\n    by_category = defaultdict(list)\n    for num in numbers:\n        if num.category != 'other':\n            by_category[num.category].append(num)\n\n    # Check each category for mismatches\n    for category, instances in by_category.items():\n        if len(instances) \u003c 2:\n            continue\n\n        # Group by approximate value (within 5% tolerance)\n        value_groups = []\n        for inst in instances:\n            placed = False\n            for group in value_groups:\n                ref_value = group[0].normalized\n                if ref_value \u003e 0:\n                    diff_pct = abs(inst.normalized - ref_value) / ref_value\n                    if diff_pct \u003c 0.05:  # 5% tolerance\n                        group.append(inst)\n                        placed = True\n                        break\n            if not placed:\n                value_groups.append([inst])\n\n        # If we have multiple groups, there might be inconsistencies\n        if len(value_groups) \u003e 1:\n            # Sort groups by size (largest first)\n            value_groups.sort(key=len, reverse=True)\n\n            # The largest group is likely \"correct\", others are potential issues\n            main_group = value_groups[0]\n            for other_group in value_groups[1:]:\n                inconsistencies.append({\n                    'category': category,\n                    'expected': {\n                        'value': main_group[0].value,\n                        'slides': sorted(set(n.slide for n in main_group)),\n                        'count': len(main_group)\n                    },\n                    'found': {\n                        'value': other_group[0].value,\n                        'slides': sorted(set(n.slide for n in other_group)),\n                        'count': len(other_group)\n                    },\n                    'severity': 'high' if category in ['revenue', 'ebitda', 'valuation'] else 'medium'\n                })\n\n    return inconsistencies\n\n\ndef main():\n    parser = argparse.ArgumentParser(\n        description='Extract numbers from presentation content for consistency checking'\n    )\n    parser.add_argument('input_file', help='Markdown file with presentation content')\n    parser.add_argument('--output', '-o', help='Output JSON file (default: stdout)')\n    parser.add_argument('--check', '-c', action='store_true',\n                       help='Check for inconsistencies and report')\n\n    args = parser.parse_args()\n\n    # Read input\n    input_path = Path(args.input_file)\n    if not input_path.exists():\n        print(f\"Error: File not found: {args.input_file}\", file=sys.stderr)\n        sys.exit(1)\n\n    content = input_path.read_text()\n\n    # Extract numbers\n    numbers = extract_numbers(content)\n\n    # Prepare output\n    output = {\n        'total_numbers': len(numbers),\n        'by_category': defaultdict(list),\n        'numbers': [asdict(n) for n in numbers]\n    }\n\n    for num in numbers:\n        output['by_category'][num.category].append({\n            'value': num.value,\n            'slide': num.slide,\n            'context': num.context[:100]\n        })\n\n    output['by_category'] = dict(output['by_category'])\n\n    # Check for inconsistencies if requested\n    if args.check:\n        inconsistencies = find_inconsistencies(numbers)\n        output['inconsistencies'] = inconsistencies\n\n        if inconsistencies:\n            print(\"\\n=== POTENTIAL INCONSISTENCIES DETECTED ===\\n\", file=sys.stderr)\n            for inc in inconsistencies:\n                print(f\"Category: {inc['category'].upper()}\", file=sys.stderr)\n                print(f\"  Expected: {inc['expected']['value']} (Slides: {inc['expected']['slides']}, Count: {inc['expected']['count']})\", file=sys.stderr)\n                print(f\"  Found:    {inc['found']['value']} (Slides: {inc['found']['slides']}, Count: {inc['found']['count']})\", file=sys.stderr)\n                print(f\"  Severity: {inc['severity']}\", file=sys.stderr)\n                print(file=sys.stderr)\n\n    # Output results\n    json_output = json.dumps(output, indent=2)\n\n    if args.output:\n        Path(args.output).write_text(json_output)\n        print(f\"Output written to {args.output}\", file=sys.stderr)\n    else:\n        print(json_output)\n\n\nif __name__ == '__main__':\n    main()\n"},"import":{"commit_sha":"9affc6e683bbaf66361058117027cf5a50bf1861","imported_at":"2026-05-18T20:09:40Z","license_text":"\n                                 Apache License\n                           Version 2.0, January 2004\n                        http://www.apache.org/licenses/\n\n   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\n\n   1. 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We also recommend that a\n      file or class name and description of purpose be included on the\n      same \"printed page\" as the copyright notice for easier\n      identification within third-party archives.\n\n   Copyright [yyyy] [name of copyright owner]\n\n   Licensed under the Apache License, Version 2.0 (the \"License\");\n   you may not use this file except in compliance with the License.\n   You may obtain a copy of the License at\n\n       http://www.apache.org/licenses/LICENSE-2.0\n\n   Unless required by applicable law or agreed to in writing, software\n   distributed under the License is distributed on an \"AS IS\" BASIS,\n   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n   See the License for the specific language governing permissions and\n   limitations under the License.\n","owner":"anthropics","repo":"anthropics/financial-services","source_url":"https://github.com/anthropics/financial-services/tree/9affc6e683bbaf66361058117027cf5a50bf1861/plugins/agent-plugins/pitch-agent/skills/ib-check-deck"}},"content_hash":[0,185,143,23,75,175,180,87,132,223,222,231,29,218,46,59,110,197,71,167,85,172,54,63,162,150,157,230,158,210,234,91],"trust_level":"unsigned","yanked":false}