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feat(optional-skills): port Anthropic financial-services skills as optional finance bundle (#21180)
Adds 7 optional skills under optional-skills/finance/ adapted from
anthropics/financial-services (Apache-2.0):
excel-author — openpyxl conventions: blue/black/green cells,
formulas over hardcodes, named ranges, balance
checks, sensitivity tables. Ships recalc.py.
pptx-author — python-pptx for model-backed decks (pitch,
IC memo, earnings note) that bind every number
to a source workbook cell.
dcf-model — institutional DCF (49KB skill): projections,
WACC, terminal value, Bear/Base/Bull scenarios,
5x5 sensitivity tables. Ships validate_dcf.py.
comps-analysis — comparable company analysis: operating metrics,
multiples, statistical benchmarking.
lbo-model — leveraged buyout: S&U, debt schedule, cash
sweep, exit multiple, IRR/MOIC sensitivity.
3-statement-model — fully-integrated IS/BS/CF with balance-check
plugs. Ships references/ for formatting,
formulas, SEC filings.
merger-model — accretion/dilution analysis for M&A.
All seven are optional (not active by default). Users install via
'hermes skills install official/finance/<skill>'.
Hermesification:
- Stripped every Office JS / Office Add-in / mcp__office__*
branch — skills assume headless openpyxl only.
- Replaced Cowork MCP data-source instructions with 'MCP first (via
native-mcp), fall back to web_search/web_extract against SEC EDGAR
and user-provided data'.
- Swapped Claude tool references (Bash, Read, Write, Edit, mcp__*)
for Hermes-native equivalents and Python library calls.
- Canonical Hermes frontmatter (name/description/version/author/
license/metadata.hermes.{tags,related_skills}).
- Descriptions tightened to 187-238 chars, trigger-first.
- Attribution preserved: author field credits 'Anthropic (adapted by
Nous Research)', license: Apache-2.0, each SKILL.md links back to
the upstream source directory.
Verification:
- All 7 discovered by OptionalSkillSource with source_id='official'
- Bundle fetch includes support files (scripts, references, troubleshooting)
- related_skills cross-refs all resolve within the bundle
- No Claude product / Cowork / Office JS / /mnt/skills leakage
remains in body text (bounded mentions only in attribution blocks)
Source: https://github.com/anthropics/financial-services (Apache-2.0)
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292
optional-skills/finance/dcf-model/scripts/validate_dcf.py
Executable file
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optional-skills/finance/dcf-model/scripts/validate_dcf.py
Executable file
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#!/usr/bin/env python3
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"""
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DCF Model Validation Script
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Validates Excel DCF models for formula errors and common DCF mistakes
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"""
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import sys
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import json
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from pathlib import Path
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from typing import Optional
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class DCFModelValidator:
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"""Validates DCF models for errors and quality issues"""
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def __init__(self, excel_path: str):
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try:
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import openpyxl
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except ImportError:
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raise ImportError("openpyxl not installed. Run: pip install openpyxl")
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self.excel_path = excel_path
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self.openpyxl = openpyxl
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if not Path(excel_path).exists():
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raise FileNotFoundError(f"File not found: {excel_path}")
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self.workbook_formulas = openpyxl.load_workbook(excel_path, data_only=False)
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self.workbook_values = openpyxl.load_workbook(excel_path, data_only=True)
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self.errors = []
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self.warnings = []
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self.info = []
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def validate_all(self) -> dict:
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"""
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Run all validation checks
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Returns:
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Dict with validation results
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"""
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from datetime import datetime
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self.check_sheet_structure()
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self.check_formula_errors()
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self.check_dcf_logic()
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results = {
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'file': self.excel_path,
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'validation_date': datetime.now().isoformat(),
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'status': 'PASS' if len(self.errors) == 0 else 'FAIL',
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'error_count': len(self.errors),
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'warning_count': len(self.warnings),
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'errors': self.errors,
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'warnings': self.warnings,
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'info': self.info
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}
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return results
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def check_sheet_structure(self):
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"""Verify required sheets exist"""
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required_sheets = ['DCF', 'WACC', 'Sensitivity']
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sheet_names = self.workbook_values.sheetnames
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for sheet in required_sheets:
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if sheet not in sheet_names:
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self.warnings.append(f"Recommended sheet missing: {sheet}")
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else:
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self.info.append(f"Found sheet: {sheet}")
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def check_formula_errors(self):
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"""Check for Excel formula errors in all sheets"""
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excel_errors = ['#VALUE!', '#DIV/0!', '#REF!', '#NAME?', '#NULL!', '#NUM!', '#N/A']
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error_details = {err: [] for err in excel_errors}
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total_errors = 0
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total_formulas = 0
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for sheet_name in self.workbook_values.sheetnames:
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ws_values = self.workbook_values[sheet_name]
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ws_formulas = self.workbook_formulas[sheet_name]
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for row in ws_values.iter_rows():
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for cell in row:
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formula_cell = ws_formulas[cell.coordinate]
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# Count formulas
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if formula_cell.value and isinstance(formula_cell.value, str) and formula_cell.value.startswith('='):
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total_formulas += 1
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# Check for errors
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if cell.value is not None and isinstance(cell.value, str):
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for err in excel_errors:
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if err in cell.value:
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location = f"{sheet_name}!{cell.coordinate}"
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error_details[err].append(location)
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total_errors += 1
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self.errors.append(f"{err} at {location}")
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break
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# Add summary info
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self.info.append(f"Total formulas: {total_formulas}")
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if total_errors == 0:
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self.info.append("✓ No formula errors found")
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else:
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self.errors.append(f"Total formula errors: {total_errors}")
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return error_details, total_errors
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def check_dcf_logic(self):
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"""Validate DCF-specific logic and calculations"""
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self._check_terminal_growth_vs_wacc()
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self._check_wacc_range()
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self._check_terminal_value_proportion()
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def _check_terminal_growth_vs_wacc(self):
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"""Critical check: Terminal growth must be less than WACC"""
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try:
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dcf_sheet = self.workbook_values['DCF']
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terminal_growth = None
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wacc = None
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# Search for terminal growth and WACC values
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for row in dcf_sheet.iter_rows(max_row=100, max_col=20):
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for cell in row:
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if cell.value and isinstance(cell.value, str):
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cell_str = cell.value.lower()
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if 'terminal' in cell_str and 'growth' in cell_str:
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# Look for value in adjacent cells
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for offset in range(1, 5):
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adjacent = dcf_sheet.cell(cell.row, cell.column + offset).value
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if isinstance(adjacent, (int, float)) and 0 < adjacent < 1:
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terminal_growth = adjacent
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break
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if 'wacc' in cell_str and wacc is None:
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for offset in range(1, 5):
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adjacent = dcf_sheet.cell(cell.row, cell.column + offset).value
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if isinstance(adjacent, (int, float)) and 0 < adjacent < 1:
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wacc = adjacent
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break
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if terminal_growth is not None and wacc is not None:
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if terminal_growth >= wacc:
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self.errors.append(
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f"CRITICAL: Terminal growth ({terminal_growth:.2%}) >= WACC ({wacc:.2%}). "
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"This creates infinite value and is mathematically invalid."
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)
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else:
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self.info.append(
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f"✓ Terminal growth ({terminal_growth:.2%}) < WACC ({wacc:.2%})"
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)
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else:
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self.warnings.append("Could not locate terminal growth and WACC values")
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except KeyError:
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self.warnings.append("DCF sheet not found")
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except Exception as e:
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self.warnings.append(f"Could not validate terminal growth vs WACC: {str(e)}")
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def _check_wacc_range(self):
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"""Check if WACC is in reasonable range"""
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try:
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wacc_sheet = self.workbook_values.get('WACC') or self.workbook_values['DCF']
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wacc = None
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for row in wacc_sheet.iter_rows(max_row=100, max_col=20):
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for cell in row:
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if cell.value and isinstance(cell.value, str):
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if 'wacc' in cell.value.lower():
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for offset in range(1, 5):
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adjacent = wacc_sheet.cell(cell.row, cell.column + offset).value
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if isinstance(adjacent, (int, float)) and 0 < adjacent < 1:
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wacc = adjacent
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break
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if wacc is not None:
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if wacc < 0.05 or wacc > 0.20:
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self.warnings.append(
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f"WACC ({wacc:.2%}) is outside typical range (5%-20%). Verify calculation."
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)
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else:
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self.info.append(f"✓ WACC ({wacc:.2%}) in reasonable range")
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else:
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self.warnings.append("Could not locate WACC value")
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except Exception as e:
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self.warnings.append(f"Could not validate WACC range: {str(e)}")
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def _check_terminal_value_proportion(self):
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"""Check if terminal value is reasonable proportion of enterprise value"""
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try:
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dcf_sheet = self.workbook_values['DCF']
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terminal_value = None
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enterprise_value = None
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for row in dcf_sheet.iter_rows(max_row=200, max_col=20):
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for cell in row:
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if cell.value and isinstance(cell.value, str):
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cell_str = cell.value.lower()
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if 'terminal' in cell_str and 'value' in cell_str and 'pv' in cell_str:
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for offset in range(1, 5):
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adjacent = dcf_sheet.cell(cell.row, cell.column + offset).value
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if isinstance(adjacent, (int, float)) and adjacent > 0:
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terminal_value = adjacent
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break
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if 'enterprise' in cell_str and 'value' in cell_str:
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for offset in range(1, 5):
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adjacent = dcf_sheet.cell(cell.row, cell.column + offset).value
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if isinstance(adjacent, (int, float)) and adjacent > 0:
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enterprise_value = adjacent
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break
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if terminal_value is not None and enterprise_value is not None and enterprise_value > 0:
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proportion = terminal_value / enterprise_value
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if proportion > 0.80:
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self.warnings.append(
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f"Terminal value is {proportion:.1%} of EV (typically should be 50-70%). "
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"Model may be over-reliant on terminal assumptions."
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)
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elif proportion < 0.40:
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self.warnings.append(
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f"Terminal value is {proportion:.1%} of EV (typically should be 50-70%). "
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"Check if terminal assumptions are too conservative."
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)
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else:
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self.info.append(f"✓ Terminal value is {proportion:.1%} of EV")
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else:
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self.warnings.append("Could not locate terminal value and enterprise value")
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except Exception as e:
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self.warnings.append(f"Could not validate terminal value proportion: {str(e)}")
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def validate_dcf_model(excel_path: str) -> dict:
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"""
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Validate a DCF model Excel file
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Args:
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excel_path: Path to Excel DCF model
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Returns:
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Dict with validation results
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"""
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validator = DCFModelValidator(excel_path)
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return validator.validate_all()
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def main():
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"""Command-line interface"""
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if len(sys.argv) < 2:
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print("Usage: python validate_dcf.py <excel_file> [output.json]")
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print("\nValidates DCF model for:")
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print(" - Formula errors (#REF!, #DIV/0!, etc.)")
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print(" - Terminal growth < WACC (critical)")
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print(" - WACC in reasonable range (5-20%)")
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print(" - Terminal value proportion of EV (40-80%)")
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print("\nReturns JSON with errors, warnings, and info")
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print("\nExample: python validate_dcf.py model.xlsx")
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print("Example: python validate_dcf.py model.xlsx results.json")
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sys.exit(1)
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excel_file = sys.argv[1]
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output_file = sys.argv[2] if len(sys.argv) > 2 else None
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try:
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results = validate_dcf_model(excel_file)
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# Print results
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print(json.dumps(results, indent=2))
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# Save to file if requested
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if output_file:
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with open(output_file, 'w') as f:
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json.dump(results, f, indent=2)
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# Exit with error code if validation failed
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sys.exit(0 if results['status'] == 'PASS' else 1)
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except Exception as e:
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error_result = {
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'file': excel_file,
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'status': 'ERROR',
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'error': str(e)
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}
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print(json.dumps(error_result, indent=2))
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sys.exit(1)
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if __name__ == "__main__":
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main()
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