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 commands/brainbytes-dev/everything-claude-finance/earnings-modelgit clone --depth 1 https://github.com/brainbytes-dev/everything-claude-financeWrote 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/brainbytes-dev/everything-claude-finance/earnings-model)<a href="https://agentmods.dev/commands/brainbytes-dev/everything-claude-finance/earnings-model"><img src="https://agentmods.dev/badge/commands/brainbytes-dev/everything-claude-finance/earnings-model.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 | $0.00009 | $0.01493 |
| Opus 5 | $0.00005 | $0.00746 |
| Sonnet 5 | $0.00002 | $0.00299 |
| Haiku 4.5 | $0.00001 | $0.00149 |
Grade A, and why
earnings-model 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 4d 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/earnings-model — Build Earnings Model
What This Command Does
Constructs a detailed earnings model for a public or pre-IPO company with revenue segment build-up, margin analysis, EPS estimates, and comparison to consensus expectations. Identifies key earnings drivers and models upside/downside scenarios relative to market expectations.
When to Use
- Pre-earnings analysis and estimate revision
- Initiating coverage on a new stock
- Quarterly model updates after earnings release
- Identifying earnings surprise potential
- Revenue and margin trend analysis
- Investor presentation preparation
How It Works
- Revenue Build-Up: Segment-level revenue modeling with volume/price/mix decomposition
- Margin Framework: Gross margin bridge, operating leverage analysis, cost structure mapping
- Below-the-Line: Interest, tax rate, share count (diluted), non-recurring items
- EPS Calculation: GAAP and adjusted EPS with clear reconciliation
- Consensus Comparison: Maps estimates against street consensus, identifies variance drivers
- Scenario Matrix: Bull/base/bear cases with probability weighting
Example Usage
Input:
/earnings-model company:"CloudMetrics Inc (CMET)" depth:standard periods:"8 quarters"
Output:
# Earnings Model — CloudMetrics Inc. (CMET)
## Model Depth: Standard | Periods: Q1'26–Q4'27 | Currency: USD
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
## Revenue Model — Segment Build-Up
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
| USD M | Q1'26E| Q2'26E| Q3'26E| Q4'26E| FY26E | FY27E |
|---------------|-------|-------|-------|-------|-------|--------|
| SaaS ARR | 142 | 150 | 159 | 168 | 619 | 780 |
| Growth YoY | 28% | 26% | 25% | 24% | 26% | 26% |
| Services | 18 | 19 | 20 | 22 | 79 | 95 |
| Growth YoY | 12% | 10% | 11% | 15% | 12% | 20% |
| **Total Rev** |**160**|**169**|**179**|**190**|**698**|**875** |
| **Growth** |**26%**|**24%**|**23%**|**23%**|**24%**|**25%** |
Key driver: Net revenue retention 118% (assumption: stable, slight expansion)
New logo adds: ~120/quarter (stable pipeline)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
## P&L Model
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
| USD M | FY25A | FY26E | FY27E | YoY Δ |
|--------------------|-------|--------|--------|-------|
| Revenue | 563 | 698 | 875 | +25% |
| Gross Profit | 410 | 523 | 672 | |
| Gross Margin | 72.8% | 74.9% | 76.8% | +190bp|
| S&M | (186) | (216) | (253) | |
| R&D | (124) | (146) | (175) | |
| G&A | (52) | (59) | (70) | |
| **Operating Income**|**48**|**102** |**174** | |
| Op. Margin | 8.5% | 14.6% | 19.9% | +530bp|
| Interest (net) | (5) | (3) | (1) | |
| Tax (22%) | (9) | (22) | (38) | |
| **Net Income** |**34** |**77** |**135** | |
| Per Share | FY25A | FY26E | FY27E |
|---------------------|-------|--------|--------|
| Diluted shares (M) | 210 | 215 | 218 |
| GAAP EPS | $0.16 | $0.36 | $0.62 |
| SBC adjustment | $0.28 | $0.25 | $0.23 |
| **Adjusted EPS** |**$0.44**|**$0.61**|**$0.85**|
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
## vs. Consensus
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
| Metric | Our Est. | Consensus | Delta | Likely Driver |
|---------------|----------|-----------|--------|------------------------|
| FY26 Revenue | $698M | $685M | +1.9% | Higher NRR assumption |
| FY26 Adj. EPS | $0.61 | $0.57 | +7.0% | Better op. leverage |
| FY27 Revenue | $875M | $852M | +2.7% | Services acceleration |
| FY27 Adj. EPS | $0.85 | $0.78 | +9.0% | Margin expansion |
Conclusion: Street underestimates operating leverage. Positive surprise likely.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
## Scenario Analysis
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
| Scenario | FY26 Rev | FY26 EPS | Probability | Key Assumption |
|----------|----------|----------|-------------|------------------------|
| Bull | $720M | $0.68 | 25% | NRR > 120%, faster wins|
| Base | $698M | $0.61 | 55% | NRR 118%, steady growth|
| Bear | $665M | $0.48 | 20% | NRR drops to 112%, churn|
Probability-weighted EPS: $0.60
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.
- 4d ago First seen · 124 lines · 9 tokens per session scan A e20f8166b1e7
earnings-model is a command published in the GitHub repository brainbytes-dev/everything-claude-finance (5 stars, last pushed 5mo ago), licensed MIT. It adds 9 tokens to every session and 1,493 once invoked, about $0.0000 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 2026-08-31.
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