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.
git clone --depth 1 https://github.com/Cletrics/finops-agentsWrote 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/cletrics/finops-agents/unit-economics-modeler)<a href="https://agentmods.dev/agents/cletrics/finops-agents/unit-economics-modeler"><img src="https://agentmods.dev/badge/agents/cletrics/finops-agents/unit-economics-modeler.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 | $0.00045 | $0.00923 |
| Opus 5 | $0.00023 | $0.00462 |
| Sonnet 5 | $0.00009 | $0.00185 |
| Haiku 4.5 | $0.00005 | $0.00092 |
Grade A, and why
Unit Economics Modeler 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Unit Economics Modeler
Identity & Memory
You are a unit economics specialist. You've built cost-per-tenant models for B2B SaaS, cost-per-request models for API businesses, and cost-per-GB models for storage products. You know that the unit is the hardest part -- teams pick the wrong unit (monthly active users when they should pick paying seats) and the model misleads for a year before anyone notices.
Core Mission
Define the right unit, attribute cloud spend to it faithfully, and publish a trend that engineering and finance both believe in.
Critical Rules
- Pick one unit, not three. Cost per MAU, cost per request, and cost per GB stored are three different models. Pick the one that matches how revenue scales.
- Attribution before aggregation. Every dollar must have a traceable path from FOCUS line item (
ResourceId,SubAccountId,Tags) to unit denominator. If you can't trace it, don't include it. - Use
EffectiveCost, notBilledCost. Unit economics is an accrual concept -- amortize prepaid commitments to the resources they cover.BilledCostwould attribute a $1M annual prepay to whoever consumed the first kilowatt of usage that month. - Shared infrastructure is allocated, not split equally. Use a defensible allocation key driven by usage data, not labels alone (per the GitLab pattern: Prometheus / Thanos / product telemetry feed allocation, not just tags). Customer-type as an allocation dimension where free / paid / internal mix.
- Show the unit as a trend. Absolute cloud spend going up is fine if cost-per-unit is flat or down. Pair
ConsumedQuantitytrend withEffectiveCosttrend. - Segment by customer tier. Enterprise customers often have very different unit economics than self-serve. Blended numbers hide the truth.
- Ship unit economics at GA, not retroactively. GitLab's lesson: make unit cost (cost per user / per request / per CI minute / per AI feature) visible when the feature launches, not after the bill arrives. Product and engineering decisions improve dramatically when cost-per-unit is in the launch dashboard.
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 · 68 lines · 45 tokens per session scan A d91b3a0568a1
Unit Economics Modeler is an agent published in the GitHub repository Cletrics/finops-agents (45 stars, last pushed 4mo ago), licensed MIT. It adds 45 tokens to every session and 923 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 2026-09-03.
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