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 client-reviewgit 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/client-review)<a href="https://agentmods.dev/skills/anthropics/financial-services/client-review"><img src="https://agentmods.dev/badge/skills/anthropics/financial-services/client-review/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/client-review"><img src="https://agentmods.dev/badge/skills/anthropics/financial-services/client-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector 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 | $0.00082 | $0.00744 |
| Opus 5.5 | $0.00033 | $0.00298 |
| Sonnet 5.5 | $0.00016 | $0.00149 |
| Haiku 4.5 | $0.00008 | $0.00074 |
Grade A, and why
client-review 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
3 near-identical copies found in the catalogue:
- client-review — 100% identical, 0 lines differ
- client-review — 94% identical, 7 lines differ
- client-review — 94% identical, 7 lines differ
How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Client Review Prep
Workflow
Step 1: Client Context
Gather or look up:
- Client name and household members
- Account types: Taxable, IRA, Roth, 401(k), trust, etc.
- Total AUM across accounts
- Investment Policy Statement (IPS): Target allocation, risk tolerance, constraints
- Life stage: Accumulation, pre-retirement, retirement, legacy
- Last meeting date and any outstanding action items
Step 2: Portfolio Performance
For each account and the household aggregate:
| Metric | QTD | YTD | 1-Year | 3-Year | Since Inception |
|---|---|---|---|---|---|
| Portfolio return | |||||
| Benchmark return | |||||
| Alpha |
Performance Attribution:
- Which asset classes / positions drove returns?
- Top 3 contributors and top 3 detractors
- Any outsized single-position impact?
Step 3: Allocation Review
Current vs. target allocation:
| Asset Class | Target | Current | Drift | Action |
|---|---|---|---|---|
| US Large Cap | ||||
| US Mid/Small | ||||
| International Developed | ||||
| Emerging Markets | ||||
| Fixed Income | ||||
| Alternatives | ||||
| Cash |
Flag any drift exceeding the IPS rebalancing threshold (typically 3-5%).
Step 4: Talking Points
Generate a meeting agenda:
- Market overview (2-3 min): Brief macro context and outlook
- Portfolio performance (5 min): How did we do? Why?
- Allocation review (5 min): Any rebalancing needed?
- Planning updates (5-10 min):
- Life changes? (job, health, family, home, education)
- Income needs changing?
- Tax situation updates
- Estate planning updates
- Action items (5 min): What are we doing before next meeting?
Step 5: Proactive Recommendations
Based on the review, suggest:
- Rebalancing trades (if drift exceeds thresholds)
- Tax-loss harvesting opportunities
- Cash deployment or withdrawal planning
- Roth conversion opportunities (if applicable)
- Beneficiary updates or estate planning needs
- Insurance review (life, disability, LTC)
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 · 91 lines · 82 tokens per session scan A ad848eac4549
client-review is a skill published in the GitHub repository anthropics/financial-services (40,858 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 82 tokens to every session and 744 once invoked, about $0.0003 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 2026-08-30.
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