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AgentBudget

Real-time dollar budgets for AI agents

Details

External ID
47133305
Source
HN
Company
—
Product
AgentBudget
Website domain
github.com
Launched
Feb. 24, 2026
Cohort
—
Upvotes
7
Upvotes percentile
0.38207547169811323
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

Hey HN,I built AgentBudget after an AI agent loop cost me $187 in 10 minutes — GPT-4o retrying a failed analysis over and over. Existing tools (LangSmith, Langfuse) track costs after execution but don't prevent overspend.AgentBudget is a Python SDK that gives each agent session a hard dollar budget with real-time enforcement. Integration is two lines: import agentbudget agentbudget.init("$5.00") It monkey-patches the OpenAI and Anthropic SDKs (same pattern as Sentry/Datadog), so existing code works without changes. When the budget is hit, it raises BudgetExhausted before the next API call goes out.How it works:- Two-phase enforcement: estimates cost pre-call (input tokens + average completion), reconciles post-call with actual usage. Worst-case overshoot is bounded to one call. - Loop detection: sliding window over (tool_name, argument_hash, timestamp) tuples. Catches infinite retries even if budget remains. - Cost engine: pricing table for 50+ models across OpenAI, Anthropic, Google, Mistral, Cohere. Fuzzy matching for dated model variants. - Unified ledger: tracks both LLM calls and external tool costs (via track() or @track_tool decorator) in a single session.Benchmarks: 3.5μs median overhead per enforcement check. Zero budget overshoot across all tested scenarios. Loop detection: 0 false positives on diverse workloads, catches pathological loops at exactly N+1 calls.No infrastructure needed — it's a library, not a platform. No Redis, no cloud services, no accounts.I also wrote a whitepaper covering the architecture and integration with Coinbase's x402 payment protocol (where agents make autonomous stablecoin payments): https://doi.org/10.5281/zenodo.187204641,300+ PyPI installs in the first 4 days, all organic. Apache 2.0.Happy to answer questions about the design.

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Observability & eval
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
real-time budget management for ai agents
Manually corrected
False

Could you build this?

Yes It is a client-side SDK wrapper around LLM client calls (like OpenAI or Anthropic) that tracks token counts, applies pricing arithmetic, and throws exceptions when limits are exceeded.

Discussion

8 comments analyzed.

Competitors mentioned: Apiosk (server-side x402 gateway for API monetization), Simplio.dev (AI gateway with multi-provider routing for cost optimization), Veronica-core (hierarchical budget tracking with parent-child relationships)

Concerns raised: Deduplication problem in dynamic pipelines with runtime call graphs, Cost non-linearity from fanout and retry compounding, Heterogeneous service costs (different models/pricing per step in RAG), Hard to track per-user-action/outcome costs vs just per-call costs, Blocking enforcement vs eventual consistency tradeoffs

Feature requests: Per-step/tool budget granularity, not just per overall run, Per-token budgeting support, Integration with provider predictive alerts (e.g., OpenAI API), x402-aware budget tracking with automatic on-chain settlement recording, Retry ratio trend tracking (429/timeouts) for cost spikes

Competitors

Other products that read as similar to this one — 229 launches clear the similarity bar, closest 8 shown.

Attention rank: #150 of 230 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 116 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a observability & eval tool for Media & entertainment yet.