Borrowing it
Nothing to install: this file belongs to LeanOS-Technologies/strategy-os. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/LeanOS-Technologies/strategy-os/main/.claude/skills/stg-calculating-economics/SKILL.mdgit clone --depth 1 https://github.com/LeanOS-Technologies/strategy-osWrote 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/leanos-technologies/strategy-os/stg-calculating-economics)<a href="https://agentmods.dev/skills/leanos-technologies/strategy-os/stg-calculating-economics"><img src="https://agentmods.dev/badge/skills/leanos-technologies/strategy-os/stg-calculating-economics/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/skills/leanos-technologies/strategy-os/stg-calculating-economics"><img src="https://agentmods.dev/badge/skills/leanos-technologies/strategy-os/stg-calculating-economics.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 | $0.00048 | $0.02293 |
| Opus 5 | $0.00024 | $0.01146 |
| Sonnet 5 | $0.00010 | $0.00459 |
| Haiku 4.5 | $0.00005 | $0.00229 |
Grade A, and why
stg-calculating-economics 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 11d 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 — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Economics Calculation
Calculate unit economics with range-based estimates, integrated cost structure, and scenario analysis. Every input carries tier label; output inherits highest (weakest) tier. Merged from old str-calculating-economics and str-structuring-costs.
Procedure
Step 1: Gather Inputs with Tier Labels [S]
Read: pricing inputs (from stg-designing-pricing), market sizing (from stg-sizing-markets), competitive data (from stg-analyzing-competition), solution design (growth architecture).
Assemble input table:
| Input | Source | Tier | Value |
|---|---|---|---|
| ARPU | Pricing tiers | T2 (hypothesis) | {range} |
| Gross margin | Category benchmark, adjusted for COGS | T2 | {range} |
| Churn rate | Benchmark for category + ACV range | T2 (no customer data) | {range} |
| S&M spend | Channel strategy (stg-designing-channels) or cost structure estimate | T2 | {range} |
| Growth model | Solution design | T1 (a choice, not a prediction) | {model} |
Produce: input table with tier labels and source citations.
If channel strategy outputs are available (from stg-designing-channels), use per-channel CAC estimates and investment splits as the primary source for S&M spend and blended CAC inputs. This provides more rigorous CAC decomposition than freestanding S&M estimation.
Gate: inputs_gathered: bool -- all 5 inputs have values, tier labels, and sources.
- Pass: Step 2.
- Fail: For missing inputs, use category benchmarks with T2 label. If no benchmarks available, use SaaS median with T3 label and wide range.
Step 2: Calculate Core Metrics as Ranges [S]
Calculate for optimistic, base, and pessimistic input sets:
LTV = ARPU x Gross Margin x (1 / Monthly Churn Rate)
CAC = (S&M Spend + Allocated Overhead) / New Customers Acquired
LTV:CAC = LTV / CAC
Payback = CAC / (ARPU x Gross Margin)
Output tier = max(input tiers). If any input is T3, output is T3. If all inputs are T2, output is T2.
Produce: metric ranges across three scenarios.
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.
- 11d ago First seen · 198 lines · 48 tokens per session scan A 53ec2553b4a2
stg-calculating-economics is a skill published in the GitHub repository LeanOS-Technologies/strategy-os (37 stars, last pushed 4mo ago), licensed MIT. It adds 48 tokens to every session and 2,293 once invoked, about $0.0002 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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