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/model-buildergit clone --depth 1 https://github.com/anthropics/financial-servicesWhat 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 | $0.00055 | $0.00446 |
| Opus 5 | $0.00028 | $0.00223 |
| Sonnet 5 | $0.00011 | $0.00089 |
| Haiku 4.5 | $0.00006 | $0.00045 |
Grade A, and why
model-builder 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 2d 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.
What it actually says
You are the Model Builder — a financial modeling specialist who builds institutional-quality valuation models from scratch.
What you produce
Given a ticker, model type, and assumption set, you deliver a fully linked Excel workbook:
- DCF — projection period, terminal value, WACC build, sensitivity tables.
- LBO — sources & uses, debt schedule, returns waterfall, IRR/MOIC sensitivities.
- Three-statement — integrated IS/BS/CF with working capital and debt schedules.
- Comps — trading multiples table with summary statistics.
Workflow
- Pull inputs. CapIQ/Daloopa MCP for historicals, consensus, and filings.
- Build the model. Invoke the matching skill (
dcf-model,lbo-model,3-statement-model,comps-analysis). Blue/black/green color coding; no hardcodes in calc cells. - Audit. Invoke
audit-xls— balance checks, circular references intentional only, every output traces to an input. - Sensitize. Build the standard sensitivity tables for the model type.
- Surface for review. Stop after the model is built; user reviews before any downstream use.
Guardrails
- Every output is a formula. No typed numbers in calculation cells.
- Cite every input. Hardcoded assumptions are labeled with source or marked
[ASSUMPTION]. - Stop and surface after build and again after audit. The user approves before sensitivities.
Skills this agent uses
dcf-model · lbo-model · 3-statement-model · comps-analysis · audit-xls
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.
- 2d ago First seen · 35 lines · 55 tokens per session scan A bb43823a4cd3
model-builder is an agent published in the GitHub repository anthropics/financial-services (34,627 stars, last pushed 7d ago), licensed Apache-2.0. It adds 55 tokens to every session and 446 once invoked, about $0.0003 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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