Budget exhaustion
The second paid action is blocked before exceeding budget.
Local calculation / simulationLocal educational experiment. No external API calls. Synthetic fixtures are not production measurements.
Study guide & lesson outline
LEARNING CONTRACTUnderstand → implement → investigate
Goal: explain the mechanism in this lesson, reproduce one example and test a failure case. Reading alone does not mark mastery.
- Understand: state assumptions, shapes/units and a counterexample.
- Implement: reproduce a numerical example and inspect boundaries.
- Investigate: compare one alternative under a matched budget.
02 · Predict & configure
Technical scenario notes, parameter names and reference answers are currently in English.
03 · Inspect the evidence
Methods & references
A deterministic state machine executes your plan against mock tools, not an autonomous language model. Each executed tool costs a synthetic $0.01. The write action never changes external data. Each mock result is truncated to 1,000 characters to bound memory. Guards are illustrative policy rules, not a complete security system.
Text / 原始公式
Plan → allowlist → approval → budget → mock tool → FIFO memory → next step
A tool allowlist alone cannot prevent data exfiltration or prompt injection in a real agent.
ReAct · reasoning and tool actions ↗Practice questions
agent-4 / 01What does “Budget exhaustion” test?
The second paid action is blocked before exceeding budget.
Original teaching answer / local derivation. Method reference: ReAct · reasoning and tool actions ↗
Open lab →agent-4 / 02Which computation produces the result in “Budget exhaustion”?
Plan → allowlist → approval → budget → mock tool → FIFO memory → next step
Original teaching answer / local derivation. Method reference: ReAct · reasoning and tool actions ↗
Open lab →agent-4 / 03What is the baseline configuration for “Budget exhaustion”?
{"plan":"search,calculator,recall,write","allowed":"search,calculator,recall,write","steps":6,"budget":0.01,"memory":3,"approval":0}
Original teaching answer / local derivation. Method reference: ReAct · reasoning and tool actions ↗
Open lab →agent-4 / 04What numerical result should you check for “Budget exhaustion”?
{"Executed / observed steps":1,"Simulated cost (USD)":0.01,"Memory entries":1}
Original teaching answer / local derivation. Method reference: ReAct · reasoning and tool actions ↗
Open lab →agent-4 / 05How would you run a controlled comparison for “Budget exhaustion”?
Keep the supplied fixture and other settings fixed; change steps. Inspect the trace, stopping reason, simulated spend and retained memory.
Original teaching answer / local derivation. Method reference: ReAct · reasoning and tool actions ↗
Open lab →agent-4 / 06What failure could invalidate a conclusion from “Budget exhaustion”?
A tool allowlist alone cannot prevent data exfiltration or prompt injection in a real agent.
Original teaching answer / local derivation. Method reference: ReAct · reasoning and tool actions ↗
Open lab →agent-4 / 07Is “Budget exhaustion” a benchmark of a deployed language model?
No. A deterministic state machine executes your plan against mock tools, not an autonomous language model. Each executed tool costs a synthetic $0.01. The write action never changes external data. Each mock result is truncated to 1,000 characters to bound memory. Guards are illustrative policy rules, not a complete security system.
Original teaching answer / local derivation. Method reference: ReAct · reasoning and tool actions ↗
Open lab →agent-4 / 08Which evidence should you report for “Budget exhaustion”?
Inspect the trace, stopping reason, simulated spend and retained memory. Export inputs, engine, result and method; distinguish synthetic fixtures from observed production data.
Original teaching answer / local derivation. Method reference: ReAct · reasoning and tool actions ↗
Open lab →agent-4 / 09How can another researcher reproduce “Budget exhaustion”?
Open agent-4, reset the preset, retain the exact inputs and run. The calculation is deterministic for identical inputs.
Original teaching answer / local derivation. Method reference: ReAct · reasoning and tool actions ↗
Open lab →agent-4 / 10What is the next validation step after “Budget exhaustion”?
A tool allowlist alone cannot prevent data exfiltration or prompt injection in a real agent. Test the hypothesis on a representative held-out workload and document a baseline, success metric and stopping rule before claiming deployment readiness.
Original teaching answer / local derivation. Method reference: ReAct · reasoning and tool actions ↗
Open lab →Assumptions, implementation & acceptance
Tool budgets are nonnegative integers. Allowlist checks precede execution; exhausted budgets stop the loop. This deterministic mock tests orchestration, not an LLM’s planning competence.
Engine formulas, scenario presets and numerical safeguards reviewed. Seeded synthetic inputs are not a production benchmark.
Before running: predict a boundary case
The second paid action is blocked before exceeding budget.
Hint: isolate the assumption
Keep the baseline input fixed, change one parameter or boundary, and compare both the numerical result and the claimed units. A passing example verifies this fixture only.
Minimal executable example
Save the example and linked modules in one folder. Use Node.js 22 or newer, then run node agent-4.mjs. No third-party runtime dependencies.
import {calculate,network} from './academy-core.mjs';
const params={
"plan": "search,calculator,recall,write",
"allowed": "search,calculator,recall,write",
"steps": 6,
"budget": 0.01,
"memory": 3,
"approval": 0
};
const result=calculate('agent',params);
console.log(result.metrics);Test and transfer
The second paid action is blocked before exceeding budget.
Record input, code version, expected result and observed result in the notebook below. Then construct a counterexample that violates the assumption above and explain why the original conclusion no longer follows.
Download complete kit (.tar.gz) · Complete reference kit and regression checksPredict, test and keep evidence
Before revealing an answer, predict one result. After the exercise, record the discrepancy and a transfer test. Saved locally across language editions.
Open notebook / export / clear →The mathematical review scope is recorded per lesson. It does not establish empirical paper reproduction; report suspected errors in your notes. Review scope