Claude for Financial Services is a collection of agents, skills, commands, plugins, and data connectors for investment banking, equity research, private equity, and wealth-management workflows. Financial professionals use it to draft models, memos, research notes, and reconciliations for review by qualified people. The catalogue contains components from these workflows, including agents, skills, plugins, commands, and instructions.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add anthropics/financial-services --skill datapack-buildergit clone --depth 1 https://github.com/anthropics/financial-servicesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/anthropics/financial-services/datapack-builder)<a href="https://agentmods.dev/skills/anthropics/financial-services/datapack-builder"><img src="https://agentmods.dev/badge/skills/anthropics/financial-services/datapack-builder/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/anthropics/financial-services/datapack-builder"><img src="https://agentmods.dev/badge/skills/anthropics/financial-services/datapack-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00100 | $0.05330 |
| Opus 5.5 | $0.00040 | $0.02132 |
| Sonnet 5.5 | $0.00020 | $0.01066 |
| Haiku 4.5 | $0.00010 | $0.00533 |
Grade A, and why
datapack-builder scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
4 near-identical copies found in the catalogue:
- datapack-builder — 100% identical, 0 lines differ
- datapack-builder — 100% identical, 0 lines differ
- datapack-builder — 100% identical, 0 lines differ
- datapack-builder — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 657 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Financial Data Pack Builder
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.
CRITICAL SUCCESS FACTORS
Every data pack must achieve these standards. Failure on any point makes the deliverable unusable.
1. Data Accuracy (Zero Tolerance for Errors)
- Trace every number to source document with page reference
- Use formula-based calculations exclusively (no hardcoded values)
- Cross-check subtotals and totals for internal consistency
- Verify balance sheet balances: Assets = Liabilities + Equity
- Confirm cash flow ties to balance sheet changes
2. ESSENTIAL RULES
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, $0.5
Revenue and per-store metrics use $, Store count uses number format.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 657 lines · 100 tokens per session scan A eb5e83d1a166
datapack-builder is a skill published in the GitHub repository anthropics/financial-services (40,858 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 100 tokens to every session and 5,330 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-12.
Other skills, from other repositories
dcf-model
Build discounted cash flow valuation workbooks in Excel.
comps-analysis
Build comparable-company valuation workbooks in Excel.
investor-materials
Create and update pitch decks, one-pagers, investor memos, accelerator applications, financial models, and fundraising materials. Use when the user needs investor-facing documents, projections, use-of-funds tables, milestone plans, or materials that must stay internally consistent across multiple fundraising assets.
budget-planner
Turn a business plan into an annual or project budget with account lines, monthly spread, summaries and a separate assumptions sheet, delivered as an Excel workbook.
company-profile
One-page company profile slide, four quadrants of overview, financial summary, share price chart and key facts. Also the compact profile paragraph when it has to sit inside a memo, a deck or a chat reply. Triggers on one-page profile, tear sheet, company snapshot, profile slide, quick profile of [company].
check-model
Audit a model somebody already built, and report on it without editing it: structure, formulas, integrity identities, source tie-out and reasonableness, ending in a routed issue log. Triggers on check my formulas, QA this spreadsheet, audit model, model review, something is off in my model, why does my balance sheet…