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 unit-economicsgit 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/unit-economics)<a href="https://agentmods.dev/skills/anthropics/financial-services/unit-economics"><img src="https://agentmods.dev/badge/skills/anthropics/financial-services/unit-economics/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/unit-economics"><img src="https://agentmods.dev/badge/skills/anthropics/financial-services/unit-economics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
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 | $0.00099 | $0.01070 |
| Opus 5 | $0.00049 | $0.00535 |
| Sonnet 5 | $0.00020 | $0.00214 |
| Haiku 4.5 | $0.00010 | $0.00107 |
Grade A, and why
unit-economics 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 today.
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
3 near-identical copies found in the catalogue:
- unit-economics — 100% identical, 0 lines differ
- unit-economics — 91% identical, 7 lines differ
- unit-economics — 91% identical, 7 lines differ
How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Unit Economics Analysis
Workflow
Step 1: Identify Business Model
Determine the revenue model to tailor the analysis:
- SaaS / Subscription: ARR, net retention, cohorts
- Recurring services: Contract value, renewal rates, upsell
- Transaction / usage-based: Revenue per transaction, volume trends, take rate
- Hybrid: Break down by revenue stream
Step 2: Core Metrics
ARR / Revenue Quality
- ARR bridge: Beginning ARR → New → Expansion → Contraction → Churn → Ending ARR
- ARR by cohort: Vintage analysis — how does each annual cohort retain and grow?
- Revenue concentration: Top 10/20/50 customers as % of total
- Revenue by type: Recurring vs. non-recurring vs. professional services
- Contract structure: ACV distribution, multi-year %, auto-renewal %
Customer Economics
- CAC (Customer Acquisition Cost): Total S&M spend / new customers acquired
- LTV (Lifetime Value): (ARPU × Gross Margin) / Churn Rate
- LTV:CAC ratio: Target >3x for healthy businesses
- CAC payback period: Months to recover acquisition cost
- Blended vs. segmented: Break down by customer segment (enterprise vs. SMB vs. mid-market)
Retention & Expansion
- Gross retention: % of beginning ARR retained (excludes expansion)
- Net retention (NDR): % of beginning ARR retained including expansion
- Logo churn: % of customers lost
- Dollar churn: % of revenue lost (often different from logo churn)
- Expansion rate: Upsell + cross-sell as % of beginning ARR
Cohort Analysis
Build a cohort matrix showing:
| Cohort | Year 0 | Year 1 | Year 2 | Year 3 | Year 4 |
|---|---|---|---|---|---|
| 2020 | $1.0M | $1.1M | $1.2M | $1.1M | |
| 2021 | $1.5M | $1.7M | $1.8M | ||
| 2022 | $2.0M | $2.3M | |||
| 2023 | $3.0M |
Show both absolute $ and indexed (Year 0 = 100%) views.
Margin Waterfall
- Revenue → Gross Profit → Contribution Margin → EBITDA
- Fully loaded unit economics: what does it cost to acquire, serve, and retain a customer?
- Gross margin by revenue stream (subscription vs. services vs. other)
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.
- today First seen · 96 lines · 99 tokens per session scan A e2d1493ca6d3
unit-economics is a skill published in the GitHub repository anthropics/financial-services (34,793 stars, last pushed today), licensed Apache-2.0. It adds 99 tokens to every session and 1,070 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 2026-09-12.
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