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 audit-xlsgit 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/audit-xls)<a href="https://agentmods.dev/skills/anthropics/financial-services/audit-xls"><img src="https://agentmods.dev/badge/skills/anthropics/financial-services/audit-xls/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/audit-xls"><img src="https://agentmods.dev/badge/skills/anthropics/financial-services/audit-xls.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
- medium Excessive Agency · line 147 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00104 | $0.01545 |
| Opus 5 | $0.00052 | $0.00772 |
| Sonnet 5 | $0.00021 | $0.00309 |
| Haiku 4.5 | $0.00010 | $0.00154 |
Grade A, and why
audit-xls 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit Spreadsheet
Audit formulas and data for accuracy and mistakes. Scope determines depth — from quick formula checks on a selection up to full financial-model integrity audits.
Step 1: Determine scope
If the user already gave a scope, use it. Otherwise ask them:
What scope do you want me to audit?
- selection — just the currently selected range
- sheet — the current active sheet only
- model — the whole workbook, including financial-model integrity checks (BS balance, cash tie-out, roll-forwards, logic sanity)
The model scope is the deepest — use it for DCF, LBO, 3-statement, merger, comps, or any integrated financial model before sending to a client or IC.
Step 2: Formula-level checks (ALL scopes)
Run these regardless of scope:
| Check | What to look for |
|---|---|
| Formula errors | #REF!, #VALUE!, #N/A, #DIV/0!, #NAME? |
| Hardcodes inside formulas | =A1*1.05 — the 1.05 should be a cell reference |
| Inconsistent formulas | A formula that breaks the pattern of its neighbors in a row/column |
| Off-by-one ranges | SUM/AVERAGE that misses the first or last row |
| Pasted-over formulas | Cell that looks like a formula but is actually a hardcoded value |
| Circular references | Intentional or accidental |
| Broken cross-sheet links | References to cells that moved or were deleted |
| Unit/scale mismatches | Thousands mixed with millions, % stored as whole numbers |
| Hidden rows/tabs | Could contain overrides or stale calculations |
Step 3: Model-integrity checks (MODEL scope only)
If scope is model, identify the model type (DCF / LBO / 3-statement / merger / comps / custom) and run the appropriate integrity checks below.
3a. Structural review
| Check | What to look for |
|---|---|
| Input/formula separation | Are inputs clearly separated from calculations? |
| Color convention | Blue=input, black=formula, green=link — or whatever the model uses, applied consistently? |
| Tab flow | Logical order (Assumptions → IS → BS → CF → Valuation)? |
| Date headers | Consistent across all tabs? |
| Units | Consistent (thousands vs millions vs actuals)? |
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.
- 9d ago First seen · 157 lines · 104 tokens per session scan A df771f6b90fc
audit-xls is a skill published in the GitHub repository anthropics/financial-services (34,762 stars, last pushed 14d ago), licensed Apache-2.0. It adds 104 tokens to every session and 1,545 once invoked, about $0.0005 per session on Opus 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 2026-08-30.
Other skills, from other repositories
dcf-model
Build discounted cash flow valuation workbooks in Excel.
comps-analysis
Build comparable-company valuation workbooks in Excel.
lbo-model
Build leveraged buyout workbooks with IRR/MOIC in Excel.
excel-author
Build auditable financial workbooks headless via openpyxl.
3-statement-model
Build integrated IS/BS/CF financial workbooks in Excel.
officecli-financial-model
Use this skill when the user wants to build a financial model — 3-statement model, DCF valuation, LBO, SaaS unit economics, sensitivity / scenario analysis, debt schedule, or fundraising projections — in Excel. Trigger on: 'financial model', '3-statement model', 'P&L + BS + CF', 'DCF', 'WACC', 'NPV', 'terminal value'…