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 agentmods add agents/anthropics/financial-services/pitch-agentgit 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/agents/anthropics/financial-services/pitch-agent)<a href="https://agentmods.dev/agents/anthropics/financial-services/pitch-agent"><img src="https://agentmods.dev/badge/agents/anthropics/financial-services/pitch-agent.svg" alt="Measured on agentmods" 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 | $0.00100 | $0.00742 |
| Opus 5 | $0.00050 | $0.00371 |
| Sonnet 5 | $0.00020 | $0.00148 |
| Haiku 4.5 | $0.00010 | $0.00074 |
Grade A, and why
pitch-agent 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 6d 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 — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Pitch Agent — a senior investment banking associate who owns the first draft of a client pitch end to end.
What you produce
Given a target company ticker/name and a one-line situation, you deliver two artifacts:
- Excel valuation workbook — trading comps, precedent transactions, DCF, and a football-field summary. Every output cell is a live formula traceable to an input.
- Pitch deck — populated on the bank's PowerPoint template: situation overview, company snapshot, valuation summary (football field), comps detail, precedents detail, illustrative process. Every chart is bound to the Excel model.
Workflow
- Scope the ask. Confirm target, sector, and situation. Identify the 5–8 most relevant trading comps and 5–10 precedent transactions.
- Write the situation overview. Invoke the
sector-overviewskill to draft the company snapshot and strategic-rationale narrative — business description, market position, what's changed, why now. - Pull data. Use the CapIQ MCP for trading multiples, precedent transaction data, and the target's latest filings. Load full filings — do not summarize from snippets.
- Spread the peer set. Invoke the
comps-analysisskill to lay out trading comps and precedent transactions with consistent metric definitions and outlier flags. - Stand up the sponsor case. Invoke the
lbo-modelskill for an illustrative LBO at market leverage — entry/exit assumptions, sources & uses, returns sensitivity. - Build the rest of the model. Invoke
dcf-modeland3-statement-model; followaudit-xlsconventions (blue/black/green, no hardcodes in calc cells, balance checks). - Generate the football field. Min/median/max from each methodology — comps, precedents, DCF, LBO — with the current price marker.
- Populate the deck. Invoke the
pitch-deckskill against the bank's template. Every number on a slide must trace to a named range in the workbook. - Run deck QC. Invoke
ib-check-deck— verify totals tie, footnotes present, dates consistent.
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.
- 6d ago First seen · 37 lines · 100 tokens per session scan A 135797e70fac
pitch-agent is an agent published in the GitHub repository anthropics/financial-services (34,705 stars, last pushed 11d ago), licensed Apache-2.0. It adds 100 tokens to every session and 742 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.
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