token-accountant

token-accountant is a skill for Claude Code from alebgl77/claude-inc. It costs 74 tokens per session (762 once invoked), scanned A, original, MIT.

An internal accounting process for tracking the cost of AI work, measured in tokens—the units used to process model input and output. It records spending by mission and department, labels estimates separately from exact usage, and produces budget reports.

In plain words
What is it for?
Recording token usage from telemetry, invoices, or pasted cost data; estimating costs when necessary; tracking monthly totals; allocating costs to departments; and writing a monthly cost memo.
Why use it?
It shows where AI usage costs come from and prevents estimated figures from being presented as measured charges. It gives finance a way to spot trends, set alerts, and identify recurring expensive work.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents; mentions Claude Code.

Part of the claude-inc plugin — 50 skills, 3 commands, 8 agents shipped together

Good fit Recording token usage from telemetry, invoices, or pasted cost data; estimating costs when necessary; tracking monthly totals; allocating costs to departments; and writing a monthly cost memo.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alebgl77/claude-inc/token-accountant
Install

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.

Any agent
npx skills add alebgl77/claude-inc --skill token-accountant
Clone the repo
git clone --depth 1 https://github.com/alebgl77/claude-inc

Made for: Claude Code.

Or install claude-inc, the plugin that ships this one along with the rest of its 50 skills, 3 commands, 8 agents.

Wrote 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.

agentmods badge for token-accountant

README.md
[![agentmods](https://agentmods.dev/badge/skills/alebgl77/claude-inc/token-accountant/github.svg)](https://agentmods.dev/skills/alebgl77/claude-inc/token-accountant)
Your own site
<a href="https://agentmods.dev/skills/alebgl77/claude-inc/token-accountant"><img src="https://agentmods.dev/badge/skills/alebgl77/claude-inc/token-accountant/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.

agentmods 80×15 button for token-accountant

Your own site · 80×15
<a href="https://agentmods.dev/skills/alebgl77/claude-inc/token-accountant"><img src="https://agentmods.dev/badge/skills/alebgl77/claude-inc/token-accountant.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 762 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00074 $0.00762
Opus 5 $0.00037 $0.00381
Sonnet 5 $0.00015 $0.00152
Haiku 4.5 $0.00007 $0.00076

Measured 9d ago against content hash 245655576335, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

token-accountant 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 9d 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.

skills/token-accountant/SKILL.md · 56 lines

How it starts

The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Token Accountant — The Bean Counter

"The first company whose payroll is measured in tokens."

Staff position — reports to the CFO. Audits everyone, including the CEO.

When to use

  • "How much did this mission cost?"
  • "Track my token spend by department"
  • "Set a monthly AI budget and warn me"
  • "Write the monthly cost memo"
  • Works with whatever is available: /cost output pasted by the user, Claude Code telemetry (OTel), API invoices, or honest estimation from transcript volume — always labels which

Workflow

  1. Establish the data source and label the confidence: EXACT (telemetry/invoice//cost pasted), ESTIMATED (transcript length × model rates), or MIXED. Never present estimates as measurements.
  2. Maintain the books at token-ledger.md: date, mission, department(s), input/output tokens (or estimate), model, cost, cumulative month-to-date.
  3. Attribute by department: tag each mission's cost to the departments the CEO engaged (a /company mission fans out — attribute per subagent when known, else split with a stated rule).
  4. Compute the vitals: cost per mission, cost per department (month), trend vs. last period, and the "expensive habit" (the recurring pattern that burns the most, e.g. unscoped /company briefs).
  5. Budget watch: if the user set a budget, compute burn rate and projected month-end; alert at 70% and 90% with the specific behaviour to change.
  6. Monthly memo: one page — spend, top 3 cost centers, efficiency win of the month, one recommendation (e.g. "route single-department tasks directly, skip the CEO fan-out: −30%").
  7. Optional export: emit a CSV of the ledger for spreadsheets or Grafana/observability pipelines if the user has one.

Output format

## Token books — {period} · source: EXACT/ESTIMATED/MIXED
Month-to-date: {$X} ({Y}M tokens) · Budget: {$Z} → {%} used, projected {$W}

| Mission | Dept(s) | Tokens in/out | Model | Cost |
|---------|---------|---------------|-------|------|

**Cost per department**: dev {$} · marketing {$} · ...
**Expensive habit**: ...
**Action**: {one behavioural change, quantified}

Read the full file on GitHub · 56 lines

Changes

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.

  1. 9d ago First seen · 56 lines · 74 tokens per session scan A 245655576335

Subscribe to this mod's changes

token-accountant is a skill published in the GitHub repository alebgl77/claude-inc (14 stars, last pushed 6d ago), licensed MIT. It adds 74 tokens to every session and 762 once invoked, about $0.0004 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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