Llm usage normalizer

Name: Llm usage normalizer
Author: @agentcosts

@agentcosts/llm-usage-normalizer

Convert Anthropic and OpenAI usage exports, or your own app's token logs, into one usage schema with customers, tasks, cached and uncached tokens, and cost from a price table you edit. Fixes the classic mistake of counting cached tokens twice, and lists unmapped keys and unpriced models.

SkillDatav1.0.0 (latest)Tested

Use in Claude Save Like Clone Comment

Activity: New: be the first to try it
Installs: 0 installs
Likes: 0 likes
Clones: 0 clones

1start_time,end_time,model,project_id,api_key_id,batch,num_model_requests,input_tokens,input_cached_tokens,output_tokens
21790812800,1790899200,gpt-5-2025-08-07,proj-bluepeak,key-bluepeak-prod,false,58,612000,180000,98000
31790812800,1790899200,gpt-5-mini-2025-08-07,proj-bluepeak,key-bluepeak-prod,false,140,420000,0,61000
41790899200,1790985600,gpt-5-2025-08-07,proj-bluepeak,key-bluepeak-prod,false,61,640000,220000,101000
51790899200,1790985600,gpt-5-mini-2025-08-07,proj-internal,key-evals,true,900,2400000,0,300000

Use in Claude

Claude Code

/kit add @agentcosts/llm-usage-normalizer

CLI

slashclone add @agentcosts/llm-usage-normalizer

Codex

slashclone add @agentcosts/llm-usage-normalizer --agent codex

Not enforced. Codex does not enforce the permissions this kit declares.

Cursor

slashclone add @agentcosts/llm-usage-normalizer --agent cursor

Not enforced. Cursor does not enforce the permissions this kit declares.

claude.ai and the desktop app

Download for Claude

Not enforced. claude.ai and the Claude desktop app do not enforce the permissions this kit declares. How to upload it

As a file

Download .kit

One file with everything in it. slashclone add ./file.kit checks it against this page before installing.

Review before installing

Set up SlashClone in Claude

Health

No keep-alive checks yet

Checks run weekly once someone keeps the kit installed.

Run reports are off

Safety

Scan passed
Not reviewed yet
Tests pass (2 of 2)

This kit reads ./data/**, writes to ./data/llm-prices.csv, ./data/customer-map.csv, ./out/usage-normalized* and runs node scripts/normalize.mjs. Install it?

Full scan and review

Similar kits

Agent cost dashboard
@agentcosts
Turn LLM usage logs into one self-contained HTML cost dashboard for an agentic product: cost per customer, per task, per successful outcome, model mix, cache hit rate, and gross margin when you add revenue by customer. Prices blank costs from an editable price table.
Gross margin by customer
@agentcosts
Gross margin per customer for an AI product: revenue minus LLM cost minus allocated hosting and other cost of revenue. Flags negative and below-target customers, names the task driving their cost, and gives the price each one would need to hit your target margin.
Usage pricing simulator
@agentcosts
Test pricing models for an AI product on your real usage before you change a price: per seat, per task, credits, and hybrid (platform fee plus included credits plus overage). Shows revenue, gross margin after LLM cost, and which customers' bills would jump or drop under each model.
Consumption guardrails
@agentcosts
Set and check consumption guardrails for an AI product: per-customer daily and monthly spend caps, month-end forecasts, spend spike rules, runaway agent runs, and failure rate spikes, plus a runbook for what to do when each alert fires. Runs on usage files; exit code 2 on critical alerts for cron or CI.

Link

https://slashclone.dev/@agentcosts/llm-usage-normalizer

README badge

[![Install with SlashClone](https://slashclone.dev/badge/agentcosts/llm-usage-normalizer.svg)](https://slashclone.dev/@agentcosts/llm-usage-normalizer)

Embed

<iframe src="https://slashclone.dev/embed/agentcosts/llm-usage-normalizer" width="480" height="200" title="@agentcosts/llm-usage-normalizer" loading="lazy"></iframe>

Share card image

More from @agentcosts

Usage pricing simulator
Test pricing models for an AI product on your real usage before you change a price: per seat, per task, credits, and hybrid (platform fee plus included credits plus overage). Shows revenue, gross margin after LLM cost, and which customers' bills would jump or drop under each model.
Gross margin by customer
Gross margin per customer for an AI product: revenue minus LLM cost minus allocated hosting and other cost of revenue. Flags negative and below-target customers, names the task driving their cost, and gives the price each one would need to hit your target margin.
Consumption guardrails
Set and check consumption guardrails for an AI product: per-customer daily and monthly spend caps, month-end forecasts, spend spike rules, runaway agent runs, and failure rate spikes, plus a runbook for what to do when each alert fires. Runs on usage files; exit code 2 on critical alerts for cron or CI.
Agent cost dashboard
Turn LLM usage logs into one self-contained HTML cost dashboard for an agentic product: cost per customer, per task, per successful outcome, model mix, cache hit rate, and gross margin when you add revenue by customer. Prices blank costs from an editable price table.

See all of @agentcosts's kits

Report this kit