Dcf Model
Wind-Alice/AliceMarket
Real DCF (Discounted Cash Flow) model creation for equity valuation.
Build professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers.
$ npx skills add w95/awesome-claude-corporate-skills --skill datapack-builder -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install w95/awesome-claude-corporate-skills datapack-builder --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/02-finance-accounting/datapack-builder .claude/skills/datapack-builder && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "datapack-builder" agent skill from https://github.com/w95/awesome-claude-corporate-skills/tree/main/02-finance-accounting/datapack-builder into .claude/skills/datapack-builder/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "datapack-builder", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/w95/awesome-claude-corporate-skills/tree/main/02-finance-accounting/datapack-builderType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add w95/awesome-claude-corporate-skills --skill datapack-builder -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install w95/awesome-claude-corporate-skills datapack-builder --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/02-finance-accounting/datapack-builder .agents/skills/datapack-builder && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "datapack-builder" agent skill from https://github.com/w95/awesome-claude-corporate-skills/tree/main/02-finance-accounting/datapack-builder into .agents/skills/datapack-builder/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "datapack-builder", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add w95/awesome-claude-corporate-skills --skill datapack-builder -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install w95/awesome-claude-corporate-skills datapack-builder --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/02-finance-accounting/datapack-builder .cursor/skills/datapack-builder && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "datapack-builder" agent skill from https://github.com/w95/awesome-claude-corporate-skills/tree/main/02-finance-accounting/datapack-builder into .cursor/skills/datapack-builder/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "datapack-builder", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/w95/awesome-claude-corporate-skills.git --path 02-finance-accounting/datapack-builder--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add w95/awesome-claude-corporate-skills --skill datapack-builder -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install w95/awesome-claude-corporate-skills datapack-builder --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/02-finance-accounting/datapack-builder .gemini/skills/datapack-builder && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "datapack-builder" agent skill from https://github.com/w95/awesome-claude-corporate-skills/tree/main/02-finance-accounting/datapack-builder into .gemini/skills/datapack-builder/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "datapack-builder", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install w95/awesome-claude-corporate-skills datapack-builderInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add w95/awesome-claude-corporate-skills --skill datapack-builder -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/02-finance-accounting/datapack-builder .github/skills/datapack-builder && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "datapack-builder" agent skill from https://github.com/w95/awesome-claude-corporate-skills/tree/main/02-finance-accounting/datapack-builder into .github/skills/datapack-builder/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "datapack-builder", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add w95/awesome-claude-corporate-skills --skill datapack-builder -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install w95/awesome-claude-corporate-skills datapack-builder --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/02-finance-accounting/datapack-builder .opencode/skills/datapack-builder && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "datapack-builder" agent skill from https://github.com/w95/awesome-claude-corporate-skills/tree/main/02-finance-accounting/datapack-builder into .opencode/skills/datapack-builder/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "datapack-builder", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
datapack-builderBuild professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers.
Datapack Builder is an agent skill from w95/awesome-claude-corporate-skills. Build professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers. Extract, normalize, and standardize financial data into investment committee-ready Excel workbooks with consistent structure, proper formatting, and documented assumptions. Use for M&A due diligence, private equity analysis, investment committee materials, and standardizing financial reporting across portfolio companies. Do not use for simple financial calculations…
Its SKILL.md is about 6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Business, Finance & HR, covering Financial analysis, Excel spreadsheets and Web search. It works with Microsoft Excel, Model Context Protocol and SEC EDGAR. The repository describes itself as: 166 production-ready Claude AI skills organized by corporate role — executive leadership, finance, HR, marketing, sales, legal, operations, engineering, product, data, customer…. The licence is MIT.
9 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 78dbc7c. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Datapack Builder loads about 6k tokens when it runs. Until then it costs about 145 tokens; SKILL.md has 2,824 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from w95/awesome-claude-corporate-skills at commit 78dbc7c, republished under its MIT licence (© w95). 2,824 words, ~6,007 tokens.
.claude/skills/datapack-builder/SKILL.md (or your agent's skills folder).Build professional, standardized financial data packs for private equity, investment banking, and asset management. Transform financial data from CIMs, offering memorandums, SEC filings, web search, or MCP server access into polished Excel workbooks ready for investment committee review.
Important: Use the xlsx skill for all Excel file creation and manipulation throughout this workflow.
Every data pack must achieve these standards. Failure on any point makes the deliverable unusable.
RULE 1: Financial data (measuring money) → Currency format with $ Triggers: Revenue, Sales, Income, EBITDA, Profit, Loss, Cost, Expense, Cash, Debt, Assets, Liabilities, Equity, Capex Format: $#,##0.0 for millions, $#,##0 for thousands Negatives: $(123.0) NOT -$123
RULE 2: Operational data (counting things) → Number format, NO $ Triggers: Units, Stores, Locations, Employees, Customers, Square Feet, Properties, Headcount Format: #,##0 with commas Negatives: (123) consistent with rest of table
RULE 3: Percentages (rates and ratios) → Percentage format Triggers: Margin, Growth, Rate, Percentage, Yield, Return, Utilization, Occupancy Format: 0.0% for one decimal place Display: 15.0% NOT 0.15
RULE 4: Years → Text format to prevent comma insertion Format: Text or custom to prevent 2,024 Display: 2020, 2021, 2022, 2023A, 2024E
RULE 5: When context is mixed, each metric gets its own appropriate format Example:
Segment Analysis, 2022, 2023, 2024
Retail Revenue, $50.0, $55.0, $60.0
Stores, 100, 110, 120
Revenue per Store, $0.5, $0.5, $0.5Revenue and per-store metrics use $, Store count uses number format.
RULE 6: Use formulas for all calculations → Never hardcode calculated values All subtotals, totals, ratios, and derived metrics must be formula-based, not hardcoded values. This ensures accuracy and allows for dynamic updates.
Formatting Standards:
Color Scheme - Two Layers:
Layer 1: Font Colors (MANDATORY from xlsx skill)
Layer 2: Fill Colors (Optional for enhanced presentation)
How the layers work together (if fill colors are used):
Font color tells you WHAT it is. Fill color tells you WHERE it is (if used).
IMPORTANT: Font colors from xlsx skill are mandatory. Fill colors are optional - default is white/no fill unless the user requests enhanced formatting or colors.
Always apply:
Never include:
Use the standard 8-tab structure unless explicitly instructed otherwise:
Purpose: One-page overview for busy executives
Contents:
Format: Clean, bold headers, minimal decoration, critical numbers emphasized
Purpose: Complete profit and loss history
Contents:
Format:
Purpose: Financial position at period end
Contents:
Format:
Purpose: Cash generation and use analysis
Contents:
Format:
Purpose: Non-financial KPIs and operational data
Contents (industry-dependent):
CRITICAL FORMAT NOTE: NO dollar signs on operational metrics. These are quantities, not currency.
Format:
Purpose: Detailed breakdown by business unit, property, or segment
Contents:
Format: Consistent with financial tabs for revenue/EBITDA, number format for operational metrics
Purpose: Industry context and competitive positioning
Contents:
Format: Mix of narrative text and tables, cite sources for market data
Purpose: Narrative summary of key investment thesis points
Contents:
Format: Clear headers, bullet points, concise paragraphs
Step 1.1: Analyze source data
Step 1.2: Extract financial statements
Step 1.3: Extract operating metrics
Step 1.4: Extract market and industry data
Step 1.5: Note key context
Step 2.1: Normalize accounting presentation
Step 2.2: Apply format detection logic For each data point, determine format based on full context:
Step 2.3: Identify normalization adjustments Common adjustments to document:
Step 2.4: Create adjustment schedule For every normalization:
Step 2.5: Verify data integrity
CRITICAL: Use xlsx skill for all Excel file manipulation. Read xlsx skill documentation before proceeding.
Step 3.1: Create standardized tab structure Create workbook with tabs:
Step 3.2: Build each tab with proper formatting Apply formatting rules systematically:
Step 3.3: Insert formulas for calculations
<correct_patterns>
Store row numbers when writing data, then reference them in formulas:
# ✅ CORRECT - Track row numbers as you write
revenue_row = row
write_data_row(ws, row, "Revenue", revenue_values)
row += 1
ebitda_row = row
write_data_row(ws, row, "EBITDA", ebitda_values)
row += 1
# Use stored row numbers in formulas
margin_row = row
for col in year_columns:
cell = ws.cell(row=margin_row, column=col)
cell.value = f"={get_column_letter(col)}{ebitda_row}/{get_column_letter(col)}{revenue_row}"For complex models, use a dictionary:
row_refs = {
'revenue': 5,
'cogs': 6,
'gross_profit': 7,
'ebitda': 12
}
# Later in formulas
margin_formula = f"=B{row_refs['ebitda']}/B{row_refs['revenue']}"</correct_patterns>
<common_mistakes>
Don't use relative offsets - they break when table structure changes:
# ❌ WRONG - Fragile offset-based references
formula = f"=B{row-15}/B{row-19}" # What is row-15? What is row-19?
# ❌ WRONG - Magic numbers
formula = f"=B{current_row-10}*C{current_row-20}"Why this fails:
</common_mistakes>
Step 3.4: Apply professional presentation
Management Case: Present company's projections as provided in source materials:
Base Case (Risk-Adjusted): Apply conservative adjustments to management projections based on company-specific risk factors:
Downside Case (optional but recommended for LBO analysis): Stress test scenario based on industry cyclicality and company vulnerabilities:
Documentation requirements for scenarios: Create assumptions schedule showing:
Step 5.1: Data accuracy checks Validate:
Step 5.2: Format consistency checks Verify:
Step 5.3: Structure and completeness checks Confirm:
Step 5.4: Professional presentation checks Review:
Step 5.5: Documentation and assumptions checks Ensure:
Step 6.1: Create executive summary Write concise, impactful summary including:
Step 6.2: Final file preparation
1. Restructuring charges
2. Stock-based compensation
3. Acquisition-related costs
4. Legal settlements and litigation
5. Asset sales or impairments
6. Related party adjustments
Management Case:
Base Case (Recommended for investment decisions):
Key metrics to capture:
Format notes: ARR is currency ($), customer count is number (no $), rates are %
Key metrics to capture:
Format notes: Units, capacity are numbers (no $), utilization is %, revenue/costs are currency
Key metrics to capture:
Format notes: Rooms/sqft are numbers, occupancy is %, ADR/RevPAR are currency
Key metrics to capture:
Format notes: Locations/visits are numbers, revenue per visit is currency, rates are %
Complete this checklist before delivering the data pack:
Structure:
Data Accuracy:
Formatting - Years and Numbers:
Formatting - Professional Standards:
Content Completeness:
Documentation:
Final Output:
© w95, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in 02-finance-accounting/datapack-builder of w95/awesome-claude-corporate-skills.
Open the folder on GitHubat commit 78dbc7c
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in w95/awesome-claude-corporate-skills, which our catalogue first saw on October 7, 2026.
Datapack Builder next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Datapack Builder this skillw95/awesome-claude-corporate-skills | 235 | 1 repos | ~6k | Automated safety check: Pass | MIT | |
| Dcf ModelWind-Alice/AliceMarket | 128 | 3 repos | ~12k | Automated safety check: Pass | None | |
| Sec Footnotes AnalysisOctagonAI/skills | 127 | — | ~1.9k | Automated safety check: Pass | MIT | |
| MCP Gatewaytmustier/pi-for-excel | 434 | — | ~241 | Automated safety check: Pass | MIT | |
| Bilig Workpapersickn33/agentic-awesome-skills | 47k | 1 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Officecli Document Workflowskuramatata/my-pi-agent | 114 | — | ~1k | Automated safety check: Pass | None |
Wind-Alice/AliceMarket
Real DCF (Discounted Cash Flow) model creation for equity valuation.
OctagonAI/skills
Analyze footnotes and accounting policies from SEC filings using Octagon MCP.
tmustier/pi-for-excel
Discover and call tools from configured MCP servers. An agent skill from tmustier/pi-for-excel.
sickn33/agentic-awesome-skills
Use formula-backed WorkPaper JSON and MCP tools for agent spreadsheet tasks without driving Excel or a browser UI.
skuramatata/my-pi-agent
A skill your agent uses when my-pi-agent needs to create, inspect, beautify, restyle, validate, or modify Office files through the official OfficeCLI MCP.
mohitagw15856/pm-claude-skills
Cash runway as a distribution, not a number — Monte Carlo simulated.
w95/awesome-claude-corporate-skills
Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts.
w95/awesome-claude-corporate-skills
Framework for competitive landscape analysis across any industry.
w95/awesome-claude-corporate-skills
Research a company using Common Room data. An agent skill from w95/awesome-claude-corporate-skills.
w95/awesome-claude-corporate-skills
Prepare for a customer or prospect call using Common Room signals.
w95/awesome-claude-corporate-skills
Generate personalized outreach messages using Common Room signals.
w95/awesome-claude-corporate-skills
Write correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.).
Categories
Build professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers. Datapack Builder is an agent skill from w95/awesome-claude-corporate-skills. Build professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers.
Datapack Builder fits situations like: M&A due diligence; private equity analysis; investment committee materials; standardizing financial reporting across portfolio companies.
Run `npx skills add w95/awesome-claude-corporate-skills --skill datapack-builder -a claude-code`. Or copy the skill folder (02-finance-accounting/datapack-builder in w95/awesome-claude-corporate-skills) into .claude/skills/datapack-builder in your project. Claude Code loads it when a task matches its description.
Run `npx skills add w95/awesome-claude-corporate-skills --skill datapack-builder -a codex`. Or copy the skill folder (02-finance-accounting/datapack-builder in w95/awesome-claude-corporate-skills) into .agents/skills/datapack-builder in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add w95/awesome-claude-corporate-skills --skill datapack-builder -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/datapack-builder, .gemini/skills/datapack-builder, .github/skills/datapack-builder and .opencode/skills/datapack-builder in your project.
SKILL.md names no scripts, command-line tools or credentials: Datapack Builder is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Datapack Builder is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 6k tokens (SKILL.md is roughly 24k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Datapack Builder: Dcf Model (Wind-Alice/AliceMarket, 128 stars), Sec Footnotes Analysis (OctagonAI/skills, 127 stars), MCP Gateway (tmustier/pi-for-excel, 434 stars) and Bilig Workpaper (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
w95 (a GitHub user) maintains it in w95/awesome-claude-corporate-skills, which has 235 GitHub stars. The repository holds 43 skills in this directory. The repository was last updated on February 26, 2026.
Source: w95/awesome-claude-corporate-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.