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.
git 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/commands/anthropics/financial-services/dcf)<a href="https://agentmods.dev/commands/anthropics/financial-services/dcf"><img src="https://agentmods.dev/badge/commands/anthropics/financial-services/dcf/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/commands/anthropics/financial-services/dcf"><img src="https://agentmods.dev/badge/commands/anthropics/financial-services/dcf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00011 | $0.00874 |
| Opus 5 | $0.00005 | $0.00437 |
| Sonnet 5 | $0.00002 | $0.00175 |
| Haiku 4.5 | $0.00001 | $0.00087 |
Grade A, and why
dcf 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
1 near-identical copy found in the catalogue:
- dcf — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DCF Valuation Command
Build an institutional-quality DCF model that uses comparable company analysis to inform valuation ranges.
Workflow
Step 1: Gather Company Information
If a company name or ticker is provided, use it. Otherwise ask:
- "What company would you like to value?"
Step 2: Run Comparable Company Analysis
First, load the comps-analysis skill to build trading comps:
Use skill: "comps-analysis" to:
- Identify 4-6 comparable public companies
- Pull operating metrics (Revenue, EBITDA, margins, growth)
- Pull valuation multiples (EV/Revenue, EV/EBITDA, P/E)
- Calculate statistical summary (median, 25th/75th percentiles)
Key outputs to capture from comps:
- Median EV/EBITDA multiple → informs terminal value exit multiple
- Median EV/Revenue multiple → sanity check on DCF output
- Peer growth rates → benchmark for revenue projections
- Peer margins → benchmark for margin assumptions
Step 3: Build DCF Model
Load the dcf-model skill to construct the valuation:
Use skill: "dcf-model" to:
- Gather historical financials and market data
- Build revenue projections (Bear/Base/Bull cases)
- Model operating expenses and FCF
- Calculate WACC using CAPM
- Discount cash flows and calculate terminal value
- Bridge to equity value and implied share price
Use comps to inform DCF assumptions:
| Comps Output | DCF Input |
|---|---|
| Peer median EV/EBITDA | Terminal exit multiple range |
| Peer 25th-75th EV/EBITDA | Sensitivity analysis range |
| Peer median growth rate | Benchmark for revenue assumptions |
| Peer median EBITDA margin | Target margin in terminal year |
| Peer median P/E | Cross-check implied P/E from DCF |
Step 4: Cross-Check Valuation
After DCF is complete, validate:
- Implied EV/EBITDA from DCF vs peer median
- If DCF implies 25x but peers trade at 12x, investigate why
- Implied P/E from DCF vs peer median
- Terminal value as % of EV (should be 50-70%)
- Implied growth embedded in valuation vs peer growth rates
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 · 103 lines · 11 tokens per session scan A ba4c3e0a2f6b
dcf is a command published in the GitHub repository anthropics/financial-services (34,793 stars, last pushed today), licensed Apache-2.0. It adds 11 tokens to every session and 874 once invoked, about $0.0001 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.
Other commands, from other repositories
valuation-methods
Valuation methods analysis — multiples, DCF inputs, PEG integration, valuation assumption extraction.
merit-reconcile
Preview or check the status of Stripe → Merit payout reconciliation (read-only).
audit-checklist
Perform an internal audit, review controls, or prepare for an external financial audit.
scan
Scan AWS account for cost optimization.
audit
Scan for non-kernel money math. Rebuild critical flows as JournalEntrys. Replay and prove. Complements /ledger-verify.
finops-status
Orientation — say where an opportunity or assignment sits in the five-step FinOps lifecycle and what unlocks next. Useful when a record has no active stage: an opportunity while its assignments do the work, an assignment whose plan has not been approved yet, or a rejected or archived assignment. Read-only; mutates…