Per-task budget, loop detection, and kill-switch middleware for agent LLM calls. v0, deterministic and dependency-free.
Project description
BudgetGuard
Per-task budget, loop detection, and kill-switch middleware for agent LLM calls. Deterministic, dependency-free, fail-closed. v0.
An agent with a payment credential and a vague instruction is a budget incident waiting to happen. BudgetGuard sits between your agent and its model calls and refuses the next call the moment it would cross a limit you set, before the spend happens, not after.
It is one of three small primitives from Major Labs:
MandateKit says what an agent may do. BudgetGuard caps what it spends. WitnessKit proves what it did.
What it does
Three controls, all enforced before the call runs:
- Budgets — cap a task by USD, total tokens, input/output tokens, or call count. The next call is refused if it would cross the cap.
- Loop detection — catch runaway agents that repeat the same call. If one signature repeats past a threshold within a sliding window, the call is denied.
- Kill switch — halt a single task, or everything, immediately.
BudgetGuard never makes the model call itself. You ask it whether the next call is allowed (check), make the call, then tell it what actually happened (record).
Install
pip install budget-guard # Python 3.8+
npm install budget-guard # Node 22.6+
Token and call budgets work with zero configuration. USD budgets need a pricing table (see below).
Quickstart (Python)
from budgetguard import BudgetGuard, BudgetPolicy, Pricing
guard = BudgetGuard(pricing=Pricing()) # pricing only needed for USD budgets
with guard.task("research-job", BudgetPolicy(max_usd=0.50, max_calls=20, max_repeats=3)):
sig = "search(query='...')"
# BEFORE the model call: raises BudgetExceeded / LoopDetected / KillSwitched
guard.check("research-job", model="claude-sonnet-4-6",
est_input_tokens=1200, est_output_tokens=600, signature=sig)
response = call_your_model(...) # you make the call
# AFTER: record the real usage
guard.record("research-job", model="claude-sonnet-4-6",
input_tokens=response.usage.input_tokens,
output_tokens=response.usage.output_tokens, signature=sig)
Prefer not to use exceptions? guard.check(..., enforce=False) returns a Decision(allowed=False, reason=...) instead of raising.
Quickstart (TypeScript)
import { BudgetGuard, Pricing } from "budget-guard";
const guard = new BudgetGuard(new Pricing());
guard.open("research-job", { maxUsd: 0.5, maxCalls: 20, maxRepeats: 3 });
guard.check("research-job", { model: "claude-sonnet-4-6", estInputTokens: 1200, estOutputTokens: 600, signature: sig });
const res = await callYourModel();
guard.record("research-job", { model: "claude-sonnet-4-6", inputTokens: res.usage.input, outputTokens: res.usage.output, signature: sig });
guard.close("research-job");
Run the demo: python3 demo.py (Python) or npm run demo (TypeScript).
Pricing
USD budgets need to convert tokens to dollars. The built-in price table is illustrative and will drift — do not trust it for billing. Supply your own verified prices (per 1,000 tokens):
from budgetguard import Pricing, ModelPrice
pricing = Pricing({"my-model": ModelPrice(input_per_1k=0.003, output_per_1k=0.015)})
If you only use token or call budgets, you do not need pricing at all.
Honest limitations (v0)
- Concurrency is check-then-act.
checkandrecordare individually safe, but the model call happens between them. Two calls running concurrently under the same task can both passcheckbefore either records, and overshoot the cap. For now, run one guarded call per task at a time, or treat the cap as a soft ceiling under concurrency. A reserve/commit API is planned. - USD enforcement carries float drift. Costs are floating point; the cap may be honored to within a fraction of a cent, not exactly.
- Loop detection is signature-based. It only catches loops you give it a stable signature for (e.g. a hash of the prompt and tool arguments). It does not infer loops on its own.
- In-memory only. State lives in the process. A kill switch or ledger does not survive a restart and is not shared across machines. A pluggable store is planned.
License
MIT. Built by Major Labs · github.com/major-matters
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