agent-token-budget

agent-token-budget is a skill for Claude Code, Codex from MLOps-Courses/agentops-open-course. It costs 65 tokens per session (554 once invoked), scanned A, original, MIT.

A system for limiting and tracking how many tokens an AI agent uses during a session. Tokens are the small pieces of text models process.

In plain words
What is it for?
Use it to enforce per-session token ceilings, count input and output usage, expose metrics, attach usage to traces, and estimate cost from configurable prices.
Why use it?
It stops an agent loop from running indefinitely and gives a clear response when the usage limit is reached, while recording usage details.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it to enforce per-session token ceilings, count input and output usage, expose metrics, attach usage to traces, and estimate cost from configurable prices.

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Install with agentmods
npx agentmods add skills/mlops-courses/agentops-open-course/agent-token-budget
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 MLOps-Courses/agentops-open-course --skill agent-token-budget
Clone the repo
git clone --depth 1 https://github.com/MLOps-Courses/agentops-open-course

Made for: Claude Code, Codex.

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 agent-token-budget

README.md
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Your own site
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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 agent-token-budget

Your own site · 80×15
<a href="https://agentmods.dev/skills/mlops-courses/agentops-open-course/agent-token-budget"><img src="https://agentmods.dev/badge/skills/mlops-courses/agentops-open-course/agent-token-budget.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 554 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.
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 $0.00065 $0.00554
Opus 5.5 $0.00026 $0.00222
Sonnet 5.5 $0.00013 $0.00111
Haiku 4.5 $0.00006 $0.00055

Measured 29d ago against content hash 33485821b16d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

agent-token-budget 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 29d 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/agent-token-budget/SKILL.md · 37 lines

How it starts

The opening of the file, as written. The whole thing — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Token Budget

Every agent loop step is another model call, so cost and latency compound. Give each conversation a hard token ceiling and attribute usage to the session — bounding reasoning work, not just dollars.

When to use

  • An agentic loop or delegation chain can call the model an unbounded number of times.
  • You need to answer "how many tokens did this session use?" and "what happens at the limit?".
  • You want token/cost signals in traces and metrics without hardcoding a vendor's prices.

Steps

  1. Accumulate usage into session state. After each model response, add its input/output tokens to a running per-session total that persists across turns (no temp: prefix if your session store honors one).
  2. Enforce a hard ceiling before the model call. In a before-model hook, if the session total has reached the limit, short-circuit with a clear message ("start a new session, or raise the limit") instead of a silent failure or an open-ended bill.
  3. Attribute, don't just count. Emit tokens as an OTel counter (graph throughput) and as span attributes (per-turn detail); compute cost from configurable per-1k prices that default to 0 for local models — never hardcode a provider's pricing.
  4. Make the budget cover the whole conversation. In multi-agent/delegation flows, keep the totals in shared session state so hops between sub-agents accumulate against one ceiling rather than each starting fresh.

Reference implementation

From the AgentOps Open Course (agent modules live under agents/python/src/agent/):

  • budget.py — record_token_usage, enforce_token_budget, estimate_cost; OTel counter + span attributes.
  • Course chapters 7.3. Costs and 3.7. Multi-Agent.

Verify

Set the ceiling to 1 token and send a turn: assert the model call is refused with the actionable message and the token counter reflects the usage; confirm a delegation chain hits one shared ceiling, not one per sub-agent.

Honest limits

A per-session budget bounds one conversation, not one client — a caller who rotates sessions bypasses it, so pair it with a per-client/tenant limit at the gateway. It bounds tokens, not dollars, unless you supply real prices.

Read the full file on GitHub · 37 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. 29d ago Changed 33485821b16d
  2. 1mo ago First seen · 37 lines · 65 tokens per session scan A 16ae49bf3c81

Subscribe to this mod's changes

agent-token-budget is a skill published in the GitHub repository MLOps-Courses/agentops-open-course (2 stars, last pushed yesterday), licensed MIT. It adds 65 tokens to every session and 554 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.

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