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 skills/anthropics/financial-services/comps-analysisnpx skills add anthropics/financial-services --skill comps-analysisgit 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/comps-analysis)<a href="https://agentmods.dev/skills/anthropics/financial-services/comps-analysis"><img src="https://agentmods.dev/badge/skills/anthropics/financial-services/comps-analysis.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 | $0.00126 | $0.07256 |
| Opus 5 | $0.00063 | $0.03628 |
| Sonnet 5 | $0.00025 | $0.01451 |
| Haiku 4.5 | $0.00013 | $0.00726 |
Grade A, and why
comps-analysis 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 5d 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.
This is a copy
78% identical to comps-analysis — 63 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 662 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Comparable Company Analysis
⚠️ CRITICAL: Data Source Priority (READ FIRST)
ALWAYS follow this data source hierarchy:
- FIRST: Check for MCP data sources - If S&P Kensho MCP, FactSet MCP, or Daloopa MCP are available, use them exclusively for financial and trading information
- DO NOT use web search if the above MCP data sources are available
- ONLY if MCPs are unavailable: Then use Bloomberg Terminal, SEC EDGAR filings, or other institutional sources
- NEVER use web search as a primary data source - it lacks the accuracy, audit trails, and reliability required for institutional-grade analysis
Why this matters: MCP sources provide verified, institutional-grade data with proper citations. Web search results can be outdated, inaccurate, or unreliable for financial analysis.
Overview
This skill teaches Claude to build institutional-grade comparable company analyses that combine operating metrics, valuation multiples, and statistical benchmarking. The output is a structured Excel/spreadsheet that enables informed investment decisions through peer comparison.
Reference Material & Contextualization:
An example comparable company analysis is provided in examples/comps_example.xlsx. When using this or other example files in this skill directory, use them intelligently:
DO use examples for:
- Understanding structural hierarchy (how sections flow)
- Grasping the level of rigor expected (statistical depth, documentation standards)
- Learning principles (clear headers, transparent formulas, audit trails)
DO NOT use examples for:
- Exact reproduction of format or metrics
- Copying layout without considering context
- Applying the same visual style regardless of audience
ALWAYS ask yourself first:
- "Do you have a preferred format or should I adapt the template style?"
- "Who is the audience?" (Investment committee, board presentation, quick reference, detailed memo)
- "What's the key question?" (Valuation, growth analysis, competitive positioning, efficiency)
- "What's the context?" (M&A evaluation, investment decision, sector benchmarking, performance review)
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.
- 5d ago First seen · 662 lines · 126 tokens per session scan A 2d49d9d69429
comps-analysis is a skill published in the GitHub repository anthropics/financial-services (34,627 stars, last pushed 10d ago), licensed Apache-2.0. It adds 126 tokens to every session and 7,256 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 78% identical to comps-analysis, differing in 63 lines, and is treated as a copy.
Other skills, from other repositories
dcf-model
Build discounted cash flow valuation workbooks in Excel.
comps-analysis
Build comparable-company valuation workbooks in Excel.
lbo-model
Build leveraged buyout workbooks with IRR/MOIC in Excel.
excel-author
Build auditable financial workbooks headless via openpyxl.
3-statement-model
Build integrated IS/BS/CF financial workbooks in Excel.
merger-model
Build M&A accretion/dilution workbooks in Excel.