Works with the AI tools you already use
LLM Cost and Token Economics Modeler
Model what your LLM app or agent will cost, find where the money goes, and get a plan to cut it. Per-request and monthly projections, ranked cost drivers, an optimization plan with estimated savings, and unit economics against your pricing — with the arithmetic shown.
$14
· or 70 creditsSecure checkout via Stripe
About this skill
Most teams ship an LLM feature and meet its true cost on the invoice. Token spend is knowable in advance and controllable after — but only if someone models the actual call pattern instead of eyeballing a per-token price. A single agent task can fan out into dozens of calls, each dragging a growing context; a feature that's cheap per request can be ruinous per user. LLM Cost and Token Economics Modeler builds the model. Give it your architecture — models and prices, prompt and context sizes, the call pattern per user action including the hidden calls (tool loops, retries, subagents, re-sent history), and your volume — and it produces a per-request and monthly cost projection with the formula and assumptions shown, a ranking of what actually drives the bill, an optimization plan applying model routing, prompt-context trimming, caching, call-count reduction, and output discipline (each lever with an estimated saving and the quality trade-off to test), and the unit economics: cost per user versus your pricing, gross margin, and the usage level where a flat plan loses money. The download includes three reference files: the cost-model worksheet, the optimization-levers guide, and a complete worked example. Every figure is an estimate you can calibrate — it does the economics, it does not access your billing or meter live traffic, and model prices are yours to supply since they change. Works with Claude Code, Cursor, Codex CLI, Gemini CLI, and any SKILL.md agent.
Details
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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Permissions
File Scopes
This skill only reads the architecture details you provide and writes cost-model, optimization, and unit-economics documents plus the three reference files under references/**. It performs no network access: it does not call model providers, connect to billing or analytics APIs, fetch live prices, or meter traffic. The auto-detected host pubsprotoolkit.com was removed because the skill makes no external connections.
Creator
PubsProToolkit builds rigor-first skills for AI agents — they write your docs and content properly, then adversarially review them to catch what's wrong before it ships. The result: cleaner output and a hard quality gate in one toolkit. Built by a CMPP-certified, PhD medical writer who brings regulated-industry standards to developer docs, content, compliance, and research integrity.
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