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 deal-sourcinggit 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/deal-sourcing)<a href="https://agentmods.dev/skills/anthropics/financial-services/deal-sourcing"><img src="https://agentmods.dev/badge/skills/anthropics/financial-services/deal-sourcing/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/deal-sourcing"><img src="https://agentmods.dev/badge/skills/anthropics/financial-services/deal-sourcing.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 | $0.00076 | $0.00816 |
| Opus 5.5 | $0.00030 | $0.00326 |
| Sonnet 5.5 | $0.00015 | $0.00163 |
| Haiku 4.5 | $0.00008 | $0.00082 |
Grade A, and why
deal-sourcing 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:
- deal-sourcing — 100% identical, 0 lines differ
- deal-sourcing — 95% identical, 7 lines differ
- deal-sourcing — 95% identical, 7 lines differ
How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deal Sourcing
Workflow
This skill follows a 3-step sourcing pipeline:
Step 1: Discover Companies
Research and identify potential target companies based on the user's criteria:
- Sector/industry focus: Ask the user what space they're looking in (e.g., "B2B SaaS in healthcare", "industrial services in the Southeast")
- Deal parameters: Revenue range, EBITDA range, growth profile, geography, ownership type (founder-owned, PE-backed, corporate carve-out)
- Sources: Use web search to find companies matching criteria. Look at industry reports, conference attendee lists, trade publications, and competitor landscapes
- Output: A shortlist of companies with: name, description, estimated revenue/size, location, founder/CEO name, website, and why they fit the thesis
Step 2: CRM Check
Before outreach, check if the company or founder already exists in the firm's CRM:
- Search the user's email (Gmail) for prior correspondence with the company or founder
- Search Slack for any internal mentions or prior discussions about the target
- Ask the user: "Have you or your team had any prior contact with [Company]?"
- Flag any existing relationships, prior passes, or known context
- Output: For each company, note: "New" (no prior contact), "Existing" (prior correspondence found — summarize), or "Previously Passed" (if evidence of a prior pass)
Step 3: Draft Founder Outreach
Draft personalized cold emails to founders/CEOs:
- Tone: Professional but warm. Not overly formal — founders respond better to genuine, concise outreach
- Structure:
- Brief intro — who you are and your firm (ask user for their firm intro if not known)
- Why this company caught your attention — reference something specific (product, market position, growth)
- What you're looking for — partnership, not just a transaction
- Soft ask — "Would you be open to a brief conversation?"
- Personalization: Reference the company's specific product, recent news, or market position. Never use generic templates
- Length: 4-6 sentences max. Founders are busy
- Voice matching: If the user has sent prior outreach emails, study them to match their tone and style. Search Gmail for "sent" emails with keywords like "reaching out", "introduction", "partnership" to find examples
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 · 69 lines · 76 tokens per session scan A 47429d5cb480
deal-sourcing is a skill published in the GitHub repository anthropics/financial-services (40,817 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 76 tokens to every session and 816 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 2026-09-12.
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